Web Analytics Archives - Online Metrics

22 Tips to Get Up-to-Speed with Google Data Studio

Paul Koks — Tue, 13 Jun 2017 07:00:23 +0000

Google Data Studio (now Looker Studio) is a great tool in the arsenal of Google. In this blogpost I will reveal dozens of tips on how to work the most effective.

For some people and in some circumstances you still want to build your dashboards in Excel or Google Sheets. At the end it might give some more flexibility.

However, the downside is that not every marketer or analyst has the skills required to build those complex formulas and visualizations in Google Sheets.

This is where the true power of Google Data Studio steps in. It let’s you create, visualize and share your reports and dashboards in a much easier way.

Tip: my friend Giannis at Data Bloo has created dozens of useful Data Studio aka Looker Studio templates, make sure to check them out.

In this post I am going to share my best tips in working with Google Data Studio and how to get the most out of it.

How to Use Google Data Studio

Step 1: Connect to your data sources.

Data Studio allows you to connect to a growing number of data sources. Read this post if you want to learn how to connect it to GA4.

At the time of writing there are 12 data connectors available:

In addition to only linking to your Google Analytics account, there are many other ways to leverage the real power of Google Data Studio.

Make sure to properly set up calculated fields (if needed), use suitable formatting and clean up your data before proceeding to the next step.

Step 2: Visualize your data.

Now it’s time to fill your canvas with beautiful charts that convey the story you want to share with your audience.

It’s even possible to collaborate together on a project! Many of you will already be familiar with this option in Google Docs or Google Sheets.

Step 3: Share your project.

The last step is to share your beautiful charts and visualizations with your colleagues or clients.

Make sure to think about with whom to share and on which access level.

In 2016 this new product was introduced with limited features. But now most of you are able to create an unlimited number of reports for free. This is extremely powerful for agencies who are working for multiple clients or if you have extensive in-house reporting needs.

Did you know that a ton of new features and enhancements are added all the time? You might want to keep track of the release notes of Google Data Studio.

Ok, let’s dive into the tips so that you can get the most out of Google Data Studio.

Tip 1: Define the Requirements

A downside of Data Studio is that it is so much fun to work with. :-)

It means you start buiding, experimenting, changing… and then you think, what does my audience actually want to see and accomplish?

Make sure to ask the right questions before you dive into Google Data Studio to stay away from getting overwhelmed by all that is possible.

Sit down or at least interview your stakeholders first, before you start creating any fancy visualizations.

I know you are smart enough to come up with some great ideas, but make sure to let your audience provide their valuable input as well.

If you do so, you will get the project done much more quickly and end up with a report that produces the actionable insights your audience is craving for.

Tip 2: Watch Data Studio Tutorials

Every solid tool will provide you with some decent tutorials to get started.

The same is true for Data Studio.

On this page you can learn a lot about important features of this product. It takes just a few hours to get up-to-speed with the basics.

Further, make sure to check out Measureschool’s video on “How to build a Dashboard with GDS”:

Tip 3: Explore the Template Gallery

The Google Data Studio template gallery is another great place to visit if you want to see and find out how great dashboards are built.

There is no better way to conquer a new tool than by looking at examples, listening to tutorials and practicing! Yes, it’s the great combo that does wonders.

Tip 4: Duplicate Your Page

In Data Studio there are two easy ways to add multiples pages to your report or dashboard:

Add a new page
Duplicate your page

For the sake of this tutorial I have set up a very simple report based on the data of Google Merchandise Store.

Here is what happens:

Option 1: Add a page.

Your second page is empty and you have to start from scratch again. This includes designing a header and footer for your page.

Tip: you can overcome this by using the make-report level feature. Will explain more about this feature later in this post.

Sometimes this can be your preferred option, but at times you might want to re-use multiple objects.

Option 2: duplicate a page.

As you can see, the header including charts and other visualizations are copied into the second page of your report.

You can keep all the items that you need and get rid of the rest. This is very handy when building out complex, multi-page dashboards with a similar look and feel.

Tip 5: Name Your Pages

On default, your page get’s the name page 1, page 2 or copy of page 1 etc.

Since you have the option to rename your pages, I definitely recommend to do so. It’s an extra indication of what’s actually on a particular page of your report or dashboard.

Here is a quick example:

and in “view” mode it looks like this:

Tip 6: Add Filter Controls

Another great, must-use feature in Google Data Studio is the filter control.

It is shown in the top right corner of your canvas:

You can choose:

Which dimension to use in your filter control.
Which metric to use and whether to show values or not.
How to sort the filter control.
All kind of styling options.

Here I have selected the default channel grouping:

Further settings include:

Sessions as my metric.
Sorting by number of sessions.
Style: expandable and compact numbers.

I recommend to test the different options and see what works for you and your dashboard.

On default the filter control works on all the charts and tables on the page. However, you have the option to limit the scope to one or more objects on the page.

Tip 7: Group Your Objects

There are dozens of reasons why you would want to group multiple objects on a page.

One of them is that you want a filter control to only apply to one or a few charts on your page.

Two ways of accomplishing this.

Hold you left-mouse button and hover over the objects you want to group.
Hold the control button and select the objects you want to group.

Then you need to hit control+g to group the objects.

Let’s say you group one chart and the filter control:In the example above the purple objects are grouped and the red one is untouched.

You can see the graph displays far less traffic (only Display) compared to the Scorecard.

Then if you decide to ungroup certain objects you simply have to select one of them (that belongs to the same group) and hit control+shift+g. Everything is back to normal then.

You could also use this filter to apply the date range control to a limited number of objects. Or you could use it to simultaneously modify the styling of multiple objects. Grouping is a very useful feature.

Tip 8: Use Object Filters

This option can be very handy if you want to apply a filter to just one of your visualizations.

Step 1: select visualization.

Step 2: go to table properties > data > filter.

Step 3: create the filter that you need and apply it to your visualization.

Things to keep in mind:

The general filter control will override your specific filter.
You can use the grouping feature to overrule this.
Specific filters can be re-used on other visualizations.
You can review all filters under Resource > Manage filters.

As you can see you can also create a filter here and apply it to your visualizations later.

This is the same as in Google Analytics where you can create a repository of filters in the admin account section.

Tip 9: Copy Your Visualizations

You can save a lot of time by simply copying your visualizations.

This is very handy If you want to apply a common style on multiple objects.

It’s very simple:

Select the object that you want to copy.
Hit control+c.
Hit control+v.
Change the visualization type and other settings if needed.

I have found this one to be a huge timesaver.

Tip 10: Add Segments

Just three months ago Google released the new option to apply segments to your visualizations.

You can use all system and custom segments that you have created in Google Analytics.

A few things to note:

You can apply a segment to one or more visualizations.
You can manage segments via Resource > Manage Segments.
Turn segment synchronization with Google Analytics off and on (default = on).

Read this beginners article on Google Analytics segments if you are not familiar with this feature yet.

Please note that in Google Analytics and Google Data Studio sampling could impact your data if you apply segments. Read this article to learn more about data sampling.

Tip 11: Learn Shortcuts

As with many tools online, it can be very helpful to memorize the most important shortcuts.

Here is a list of 10 shortscuts that are very useful to know:

Copy: Ctrl+C.
Paste: Ctrl+V.
Undo: Ctrl+Z.
Redo: Ctrl+Y.
Select All: Ctrl+A.
Select None: Ctrl+Shift+A.
Group: Ctrl+G.
Ungroup: Ctrl+Shift+G.
Refresh Data: Ctrl+Shift+E.
Home: First page.

Tip 12: Make Use of Back and Forward Arrow

You can use four menu functions to realign objects.

This works pretty well, but sometimes you want to move one of your objects one or two spots to the right or left.

I have found the keyboard arrows (left and right) very effective in this case. It’s much more easy than using your computer mouse.

Tip 13: Change to Report-Level

By default, every component you place on a report is a page-level object. It only appears on the original page on which you place it.

However, sometimes you want your filter control to appear on every page of your report. You can acoomplish this by making it a report-level object.

To do this:

Edit the report.
Select the filter control (or other component).
Select the Arrange > Make report-level menu.

Your filter control will now appear in the same location on every page of your report.

The same as that you make an object report-level you can later undo this and turn it back into a page-level object.

Tip 14: Use Different Colors

Color styles help guide the eyes.

Don’t overdo it! But using just one color in your entire dashboard or report might not be your best option.

Here are some general guidelines of what I have found to be effective:

Use two to six colors max.
Use colors to clearly show what are the most important visualizations on a page.
Use colors that match your brand.

I recommend to check out this article to learn more about how to effectively use colors in your report.

Tip 15: Use a Diversity of Charts

You don’t have to use all charts that are available, but make sure to not just use one!

Chart diversity is one way to enhance the effectivity of your dashboard.

Quick tip: you can easily change the chart type after you have build one visualization.

Tip 16: Use Header and Footer

One smart way of filling up your header and footer is by adding report-level objects.

These could include:

Filter controls.
Logo.
Other relevant information for your audience.

Tip 17: Preselect Date Range

Most of the time you want to include a date range selector in your report.

In “edit mode” you have the option to preselect the date range for your audience.

Here is my rule of thumb:

Always select rolling dates unless you want to show your report data with a fixed timeframe.
Select “Last week” if your audience always accesses your dashboard at the beginning of a new week.
Select “Last month” if your audience always accesses your dashboard at the beginning of a new month.
Use a different preset if your audience has other, specific needs.

Tip 18: Change Field Names of Data Sources

You should have a careful look at field names as they are re-used in many objects that you create.

Here is an example (in view mode):

Step 1: go to edit mode.

Step 2: go to “manage added data sources”.

Step 3: click on “edit”.

Step 4: use the search box to filter on dimension.

Step 5: change the field name into “Channel”.

And now go back to view mode.

Another useful way to leverage this is by modifying the goal names in Google Analytics. They take up a lot of space on default so you might want to do that as well.

Tip 19: Add Google Analytics Tracking Code

Adding a Google Analytics tracking code is a great feature if you want to track the behavior / activity on one or more reports.

It was added in a new, recent release of Data Studio.

You can make this useful in different ways. Two examples:

You create an individual report and want to track usage. Create a new GA property dedicated to that report.
You publish a lot of reports and want to track them all in one place. Again, set up a new property and use the GA code across multiple reports.

Tip 20: Use Calculated Fields

If you are on the free Google Analytics account, you can set up five calculated metrics per Google Analytics view.

Calculated fields in Google Data Studio helps you to create a great set of additional metrics which you can use in your newly built reports!

I recommend to watch this video to learn more about this powerful feature:

Tip 21: Create a Template of Your Report

You might have the need to create additional reports that are similar to the original one.

It’s very powerful to create a copy of your report so that you use it as a template.

A new report is created after you click “create report”.

Tip 22: Leverage the Power of Google Sheets

Last, but not least, make sure to try out Google Sheets as one of your data connectors.

In my recent post about powerful Google Analytics tools, I explain about Google Sheets add-ons that bring a tremendous value in your reporting efforts. You should check it out to learn more!

The beauty is that you can connect several different data sources to Google Sheets and then connect Google Sheets to Google Data Studio.

I might write an entire post on this so that you can learn how to leverage this in your unique situation.

This is it from my side! Let me know in the comments if you any further tips or questions. It’s an amazing tool and new features will constantly be added!

The post 22 Tips to Get Up-to-Speed with Google Data Studio appeared first on Online Metrics.

42 Analytics Experts Share Their Best Strategy to Define Actionable KPIs

Paul Koks — Tue, 04 Oct 2016 07:00:52 +0000

Key Performance Indicators (KPIs) are probably one of the most over-used and little understood terms in business and analytics. This expert roundup post features a ton of analytics experts and demystifies how to come up with the best KPIs for your business.

“You need to define success before you can know if you’ve achieved it.”
~ Richard Branson

It’s great to read these “KPI example” posts. They can inspire you to come up with a solid set of KPIs.

However, your business, stakeholders and clients are unique and so are your KPIs.

Over the last weeks I have talked to dozens of experts to really dig deep into this topic.

Take your time to read and implement the strategies of the Analytics experts in this post. And I am 100% convinced that you will find the metrics and goals that matter most for you and your business.

A big thanks goes to the experts that have shared their knowledge and experience in this post. I wouldn’t have been able to accomplish this without them.

Let’s dive in…

And for your convenience, a direct link to your favourite expert:

They have all answered the following question:

“What is your number one strategy to define actionable KPIs?”

Without further ado, here are the experts…

Adam Singer, Analytics Advocate Google

“Number 1 way to getting actionable KPIs is starting with the end objective in mind and backing out what metrics accomplish this from there. I think most marketers understand this by now (certainly analysts do). More importantly, I think, is to make sure your tactical mix actually aligns directly with improving the metrics that matter for your brand. So, if you’ve determined that opt-ins to your email list are an important KPI for your brand, make sure you’re not off chasing “the tactic du-jour” that your CMO or HiPPO is excited about and stay vigilantly focused on what’s improving your goals. I’d seen time and time again as a consultant marketers lose focus and get shiny object syndrome with something new and exciting and stray from their plans. Then, at the end of the quarter or year when reviewing all our tactics and results it wasn’t a surprise why goals weren’t hit. Incidentally, this type of review will also help you tighten up your tactical mix.”

Alex Clemmons, Associate Director Analytics & Insights Cardinal Path

“Less is more – you really only want a few KPIs as the more you have the harder it becomes to know what you should pay attention to and what’s just noise. Once you’ve got the most important ones nailed down you need to be able to give them context in order to explain why they changed.

The contextual piece comes from segmenting your KPIs. For example – knowing your revenue per visitor has increased is great but knowing it was driven from new customers who clicked on a specific specific paid search keyword is better! The knowledge gained from this may allow you to alter bid strategies and thus take action on a change in your KPI.”

Amir Tohid, Co-Founder and Managing Partner Analytics Effect

“The most fundamental aspect is to understand business goals and objectives which are vital for identifying the KPIs. Every company has its own specific objectives.

I start with establishing Goals and Objectives by following the SMART principle and divide it in two categories, Short Term and Long Term.

Next step is to Identify Critical Factors which leads to success. Basically, those factors are the key activities that an organization should focus on to meet their business goals and objectives in a solid timeframe. Measures of success has to be defined for each organization.

KPIs can be extracted from those critical factors. I focus on what has changed overtime and choose metrics that help me to achieve the goal.”

André Mafei, Founder Upmize

“Ok, so, let’s start with “Why to define actionable KPIs?”, to improve the business performance, right? But the most common problem I see in my clients is not the lack of looking at some important metrics. They know that sales, ROI, profit, etc, matters. So why they have problems improving the business performance? Usually due to a lack of rich integrated data and faster tools to analyse the data. What causes them to take a long time to put data together, get insights, take action, then put the data together again to see the result of the action.

So my strategy to help my clients improve their business is by integrating the systems, building the initial reports and training their team on how to build reports by themselves. Some of the common tools I use: Tableau, Google Analytics, Google Tag Manager, Pentaho ETL.

But if you really have a team that is still not sure about their KPIs, do this: learn about their business, ask them what indicates if things are going well (KPIs), discover which numbers are necessary to calculate the KPIs, measure these numbers with a integrated system for faster analyses.”

Andy Crestodina, Co-Founder & Strategic Director Orbit Media

“Step one is simple, but most people miss it. The key is to connect your KPIs to your business objectives. Doing this will force you to ask yourself some simple, but tough questions about the metrics you may have been measuring:

Why do we want more Facebook followers?
What is an email subscriber worth to us?
Do visitors from Twitter ever turn into leads?

A lot of marketers want things, but they don’t know why they want them. If you’re chasing metrics that aren’t aligned with your business goals, as yourself of those are “ego metrics.” Ask yourself if your goal is profit and success, or just fame and glory.

It would be nice to be famous, but you can’t eat fame.

Focus on KPIs that support business objectives. That’s how to pay the bills.”

Anna Lewis, Founder Polka Dot Data

“In summary: dig deep, dig deeper, then filter it to find what will make each team most successful.

I always ensure I dig as deep as possible to uncover all the potential KPIs, across the business, throughout all teams and however large and small. For some teams the KPIs are much more specific than others, so it’s very important to find all the best KPIs and then align them to the relevant teams where the data will both matter greatly to success and be something they can affect.

Once you’ve aligned the KPIs throughout the business, ensure everyone knows who has what KPIs and what can be done to affect them. This ensures accountability which helps drive action and results. If you focus on one team alone, you may find KPIs are missed, thus key data is ignored and nothing actioned as a result. Alternatively, too many people are trying things at once to improve a KPI and you end up not knowing what actually caused the impact. The final issue to avoid is setting KPIs that are very hard to have any impact or control over, this makes them a lot less actionable and they do not provide any motivation to the team to drive things forward.”

Caleb Whitmore, Founder Analytics Pros

“Before getting to KPIs, you need to back all the way up to the ‘why’ for your business and determine what the most important questions are that you need to answer. Getting to these ‘right questions’ is the hardest – and most important – part of analytics. Once you have the right questions, you’ll be able to collect the best data to answer them, and work your way up to the KPIs that are the tips of those data icebergs.”

Carlos Escalera, Founder Ohow.co

“To be able to define the right KPIs, it is essential to have a clear answer to the following questions:

What is the objective(s) of the project, company or campaign?
Is it possible to measure it?
What elements can affect its achievement?

Once the objective(s) is clear and you know it is possible to measure them (generate more traffic, promote social channel, sell more products, engage readers), you can start thinking about the KPI(s) you will use to evaluate them. The first thing you need to have in mind is that all KPIs are metrics (measurable), but not all metrics can be a great KPI.

Make a list/table of all the candidates ($10k, 1k followers, 100k visitors) that your heart think will make a good KPI and answer the following questions for each of them:

What unit will you use? (Will it be visitors or returning visitors, Followers or Shares, Revenue or Profit)
Can you measure it?, Do you have the tools to measure it?, Which tools are you going to use?
Is it relevant to the project?, Will it help make decisions based on it?
Is it realistic and achievable? (Being achievable doesn’t mean that you should put a low threshold, on the contrary, you should think about the best possible outcome)
Is it possible to follow its evolution? What would be the timeline to follow?

Once you answer these questions, discard the ones that didn’t satisfy you, and write the new ideas (most of the time this process helps you generate new KPI candidates.) and continue with this process until you are happy with the result.

There are no general rules for choosing a good KPI. It is a process that you will have to do each time, and the outcome will depend on the project, but answering these questions will help you speed it up and get much better results.”

Chris Meares, Vice-President MaassMedia

“When first engaging with clients on a new project I always start out by asking them to define the mission of their digital presence; what do you want your customers to accomplish on your digital properties? The answers that clients provide can vary wildly, and occasionally I get a dumbfounded look in response to the question because the client isn’t 100% sure. The reason I ask this question is to understand what data needs to be collected on digital properties and what the key performance indicators (KPIs) will need to be in order to measure success of their digital properties.

In order to create “actionable” KPIs, you need to have a complete understanding of what you want your users to accomplish on your digital properties. For example, an ecommerce company may have a goal of selling a product. However, beyond that, perhaps there is a support section surrounding the products that users can access to better solve their issues. The KPI for the support section is going to be completely different than the checkout process. The key to having actionable KPIs is understand the different types of success that can occur on your site, segmenting your users by those different use cases and then creating KPIs that tie directly to the successes for those use cases. In addition, each KPI should have a target that you are attempting to reach, such as a 5% increase in sales for a particular product. By having KPIs that map directly to use cases and success on your digital properties and setting targets to reach for those KPIs, you can set up your organization for digital success.”

Damion Brown, Principal Consultant Data Runs Deep

“A KPI isn’t going to be actionable if it isn’t defined properly. So the actual process of how you go about the definition is very important.

It’s a bit like that Abraham Lincoln quote, “Give me six hours to chop down a tree and I will spend the first four sharpening the axe.”

The more time you spend getting the definition of a KPI right, the more actionable it is.

Start out by thinking about the moments that matter for your business. Get a marker and a sheet of A3 and literally draw out the journey that customers take from initial awareness, through consideration, to purchase and then post-purchase.

When you’ve got your map, look for the key moments, the pivot points where really significant changes happen. It might be when someone downloads a whitepaper, signs up to an EDM, or views specific information.

These are the points at which you change in the mind of your audience.

Your KPIs need to be based on these points, and only these points. Setting goals and objectives that focus on a small number of well-defined KPIs is your sure route to staying actionable.”

Daniel Waisberg, Analytics Advocate Google

“There are two fundamental techniques you should use when defining your KPIs.

The first one, clearly described by Allison in her meaningless KPIs rant, is segmentation; there is no value in having any KPI if it is not segmented by your main audiences, personas, etc. When you use segmentation right, even the plainest KPIs (bounce rate, subscription rate, Ecommerce Conversion %) will become useful. Great segments to start with are: New vs. Returning, Acquisition Channel / Campaign, and Device Category.

The second one can be described as: do not stick to default metrics. For many years Google Analytics provided a closed set of metrics, which led many analysts to adapt their needs to fit those metrics, instead of adapting the metrics to fit their needs. Now, with the capability to create calculated metrics in Google Analytics and calculated fields in Data Studio, those days are over.”

Dave Chaffey, CEO Smart Insights

“My recommendation is that businesses need to create a structured KPI framework based around the marketing funnel or customer lifecycle. This is still a huge gap for many businesses we work with when training or consulting.

I developed the Smart Insights RACE Digital Planning framework to summarise the key online marketing activities that need to be managed as part of digital marketing. RACE covers the full customer lifecycle or marketing funnel from: (Plan) > Reach > Act > Convert > Engage.

Here’s an example of typical KPIs for which we have a Google Sheets Dashboard pulling data from the Google Analytics API:Here, the KPIs are all available in Google Analytics for an Ecommerce business, but depending on the type of business, additional measures around engagement and value are useful too.

Our framework includes measures across audience Volume, Quality, Value and Cost. It’s important to include all of these since the default amongst businesses is to only include Volume.

So the starting point to creating a dashboard like this is to think that when you get a visit to the site, what are the outcomes you’re looking at in terms of people engaging with content? Then the outcomes, such as a lead, a contact, a download, how you’re tracking those? Then to customize Google Analytics so you can not only record those outcomes but the value of them.

For example, I was working with a travel business and what they were able to see is that when someone downloaded a brochure, that was worth say three pounds for that download. Once you’ve got that value defined, at that point you can work backwards to see which media and which content is driving those downloads. Then that gives you a way to optimise and improve your ROI.”

David Kamm, Founder & Principal Consultant iBeam Marketing Consulting Services

“My top advice for defining actionable KPIs in the context of digital marketing is to work closely with the management and leadership teams of the organization to make sure there is good agreement on what is being measured and how it impacts the business. The closer the connection between an individual marketing KPI and a financial performance variable (e.g., revenue), the more useful it is for business managers who aren’t immersed in analytics and metrics on a day-to-day basis. Indirect KPIs can also be very useful if their connections to business goals are clear.

When there is good executive-level support for the chosen KPIs, it’s much easier to secure budget and other resources for the “actionable” part: creating and adjusting campaigns, creating and modifying marketing content, adding new systems and support roles, etc. This approach also helps prevent “KPI Overkill” by limiting the key metrics to just those that are truly important to the business and the management team. The analyst team will always want to look at lower levels of detail, of course. But just because some of the sub-metrics are interesting and useful to analysts does not mean they should be included as KPIs.”

Dean Levitt, Founder Teacup Analytics

“For any key performance indicator to truly matter, and to drive action, it must be tied directly to revenue. If a KPI has a bearing on the bottom line, then it will, by default, be actionable.

It is worth mentioning that for a KPI to be actionable, it must be coupled with a reasonable goal or target at which to aim. With the ability to state where “success” is, the KPI has context and becomes actionable. Without a target, whatever you’re measuring is not an indicator but rather it is simply a metric.

If the KPI indicates poor performance, there is urgency and motivation to take corrective action. Similarly, if the KPI indicates that goals are being reached, it’s easy to justify taking further positive action. So an actionable KPI is a revenue-centric metric (or metrics) with a clearly defined target.”

Dominic Hurst, Digital Services Manager Liverpool John Moores University

“For me, we need to take this back a step. Having actionable insights is great, but having people to action them (more so want to action them) is my top strategy. A team unity, collectiveness and will to succeed needs to be planted at the start. This way the team are bought into achieving goals even setting the goals and respective KPIs.

At LJMU, Digital Services collaborate with colleagues throughout the organisation so we act as “one” when it comes to creating and defining measurement models. Whilst our measurement/ insights analysts guide colleagues through the creation process, it is very much led by those who work in the area where the goal relates too. Again creating buy-in and a will to achieve targets and action insights.

Finally we need to keep things real. Real in the sense of logical to all those who see the measurement models/ insights but also real in the sense of thinking of users. This approach is typified by Government Digital Services/ DWP and their “metrics that matter”.

Doug Hall, Director of Analytics & Conversion ConversionWorks

“Interesting question this. Especially the “actionable KPI” part. The differentiation between metrics that are actionable and those that are not is fundamental to the answer.

If you can take action based on the metric value or observing a change in the metric over time then this is a prime quality of a KPI. If a metric is not actionable, then it’s not a KPI. It might still be useful to the business in some way but if there is no action to be taken, there is no opportunity for optimisation – the number has less value to the business as it doesn’t drive change and we’re all about change, right?

Now take a closer look at the KPI in terms of actionability and (drum roll for the big score) IMPACT.

Actionability – low hanging fruit or a 12 month project? How quickly can you make change based on the KPI insights? Consider the timescales involved as a measure of prioritisation. Also, effort – as in can you make change at all? Do you need a tweak to a process to make change or do you need to reorganise the whole business? Consider the effort required to make change to qualify a KPI.

Timeliness comes second to impact. The expected impact on the business based on making change using insights from the KPI is often the deciding factor in choose the best KPIs. If a number or how a number changes can make a double digit percentage difference to your bottom line, this is going to drive your business like nothing else. Here is your gold. Cherish these numbers.

Bonus – how often should you review your KPIs? Analyst answer – “It Depends!”. Lol. But seriously, if you make a big impact change, time to review the KPIs. Find side effects of change. Remain fluid and prepare for change in your instrumentation. Don’t just sit on the same KPI suite blind to alternative, and potentially better, instruments to guide and drive your business.”

Egan van Doorn, Founder eganvandoorn.nl

“If you want to be your KPIs actionable make sure that they connect to the organizations overall business goals (duh…), but also make sure that the KPIs that you’re reporting on are the numbers that keep your boss awake at night. The numbers on which your bosses bonus depends on is a great starting point for those. Drill them down into short term tactical KPIs that make clear on a department level what the teams contribution is regarding the overall business outcome (read: the bonus of your boss). Every marketing activity or on-site optimization will now be evaluated against goal impact!”

Eric Fettman, Analytics Instructor & Coach E-Nor

“Often, it’s dimension swapping and constituencies that make your KPIs actionable.

Dimension Swapping: By this, I just mean evaluating your KPIs against different dimensions and dimension combinations. If you’re using Google Analytics, access the Mobile Overview report. Surprised to see how few visitors are submitting leads on smartphones? Don’t assume that this low conversion rate is endemic to smartphones; instead, apply Operating System as a secondary dimension. You might be even further surprised to see that your CR is much lower on iPhone than Android, but you’ve started to construct a meaningful story, and you can dig further by checking conversion rate for specific devices in the Mobile Devices report and applying Screen Resolution as the primary dimension in the Browser & OS report.

Constituencies: Create segments that map to your audience constituencies, and always evaluate your KPIs within these segments. If you run a job freelancing site or app, evaluate your “post a job” goal only for those audience members who are there to post a job. How do you create the segment? Often, it’s a user’s own behavior that indicates the constituency: users who access the “post a job” page or screen are telling you the constituency they belong to, and you can create a “behavioral” segment accordingly. Now you’ll be able to see that the conversion rate for this goal within the relevant segment is 5% instead of 1%, and that overall conversions are 50% higher than this time last year, not 10%. It’s the segmentation that facilitates the insight and prompts further analysis and action for optimization and ROI.”

Eric Siegel, Founder Predictive Analytics World

“To make the most actionable KPIs, turn them on their head: one KPI per individual, each a probability. Millions of such KPIs are what you get from predictive analytics, e.g., the chances each customer will buy, each suspect will lie, each patient will die, each debtor will default, each voter will be persuaded, etc. It does not get more actionable, since each such probability – better known as a predictive score, the output of a predictive model – directly informs the way in which to treat that individual, such as whether to call, mail, approve, test, diagnose, warn, investigate, incarcerate, set up on a date, or medicate.”

Eric Siegel is the author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (www.thepredictionbook.com).

Feras Alhlou, Co-Founder & Principal Consultant E-Nor

“Measure what matters most” should be a guiding principle as you’re defining your KPIs. “What matters most” will vary from one function to another, from one stakeholder to another, and it’ll also vary based on the level of maturity and sophistication of the analytics implementation and practice an organization has.

Some practitioners and consultants take the easy route and end up reporting on vanity metrics or all user interactions. Instead, take the challenging road. Build a measurement roadmap with a focus on business objectives and KPIs, then socialize the roadmap and its benefits within your organization to get buy-in from decisions makers and colleagues. Align your resources (technology, process, people) to execute on this roadmap, then share wins and share them frequently!”

Franck Scandolera, Founder webAnalyste

“What is an actionable KPI? An insightful indicator giving sufficient reason to take action. An actionable information specific enough to monitor an attribute of business performance.

So, my first strategy to define actionable and insightful KPIs is to understand the needs, the objectives and the attributes of the business activity to achieve their objectives.

The generic KPIs can’t be actionable. A marketing specialist or a CEO needs specific KPIs to monitor different facets of the business, during the particular time period, before making an important decision.

After the understanding phase is relatively easy to translate these goals in measures and data.

The other important face of actionability is the context of data visualization to tell the right story.

One figure says anything else what it represents. The context can be found, in comparison through time or item, in the relationship or distribution between dimensions.

For me, the best actionable data visualization is the time series and deviations, useful to anticipate the trend of KPIs.

In summary, an indicator must be insightful and actionable, for that, it has to be SMART (Specific, Measurable, Achievable, Relevant, Time-related) for helping an activity to achieve their business objectives. But in prior, it’s crucial to understand the business objectives.”

Himanshu Sharma, Founder Optimize Smart

“My number 1 strategy is the ‘ask question’ strategy which I explained in detail in this article: One tip that will Skyrocket your Analytics Career.

In short, I ask the client, how do they define their KPIs and why did they select those particular KPIs. The ‘why’ is very important. The goal here is to first understand their perspective, their reasoning and get an insight on why things are the way they are and not to jump to any conclusion or start making recommendations. I start my analysis with an open mind and without any prejudice.

I truly believe that my client knows a lot more about their industry and target market than I ever will. And I am here to help and not to dictate them how to run their business. When you have this type of mindset, you don’t talk like “experts”. You talk like a “clueless” person who is learning the trade.

When you talk like a clueless person, you ask a lot more questions. When you talk like an expert, you ask less questions. Your pride always stops you from asking enough questions and you are more likely to end up figuring out everything on your own, which is futile and waste of time and certainty does not conform to agile analytics methodologies.

I use my client’s years of knowledge and experience to fuel and speed up my analysis. I ask tons of questions. I keep asking questions until my client is no longer able to answer. When the client is no longer able to answer, then I start my own research to get answers to those unanswered questions, because then my analysis really matter. There is no point in spending hours and days, digging out information and insight that are already known to your client.

Once I have acquired all the knowledge I can, from the client then I match my client’s understanding about their business with my own understanding of their business, to determine “gaps”. These gaps are the conversion issues and my goals to fix. Once I have identified the conversion issues, then I determine whether the client’s chosen KPIs are a best fit to measure the performance of these goals. It is a long process. KPIs are often the result of weeks or even months of analysis and research. It is not something which can be delivered on day 1.”

Jacob Knettel, Digital Strategy Manager PFSweb

“When it comes to KPIs, I have found that the most actionable metrics are those that have either a goal or forecast to compare against. I have been in several analytics meetings where a KPI like average time on page is thrown up on a screen, but the audience has no idea if 50 seconds is a good or a bad time for how long someone is spending on a page. For an analyst to truly add value, he needs to use KPIs that he can speak intelligently to their performance and be able to further derive actionable insight from that KPI. Without a goal or forecast to compare against, the analyst is essentially driving blind and using his or her gut reaction to speak to business success or failure. If you can’t get your hands on a goal or forecast, either find benchmark data from similar websites in your industry (IBM, Adobe and Google all have benchmark features you can take advantage of) or choose a new set of KPIs.”

Jacques Warren, CEO KWANTYX

“Evaluate people (i.e. pay, promotion, heck, keeping their job!) on the KPIs, and pay them to behave accordingly. You do that, and they will care about the KPIs, the dashboards, and your analytics.“

Jeff Sauer, Founder Jeffalytics

“My #1 strategy for defining actionable KPIs is to get with the business owner and understand what they really care about. Are they interested in growth or sustainability? Are they interested in profit or market share?

Once we really understand what people are looking for in their business, you start to brainstorm Key Performance Indicators that they can use to measure the most important items.

Then comes the fun part – what I call the four T’s of analytics. After establishing KPIs, you need to get aligned with your targets, tactics, teams and tools. In that exact order.

Set targets around these KPIs that the business agrees with. Pull in tactics that can provide proven results that hit targets. Build a team and accountability for the people running the process. And last, evaluate tools that you can use to measure target performance.

Add it all together and you have not only defined actionable KPIs, you have defined a plan that is aligned with the goals of the business executives and their marketing and analytics functions. Anything else would be uncivilized.” :-)

Jente de Ridder, Web Analyst Humix

“When I start working with a new client, I don’t ask them: what are your KPIs? Experience has learned me that people often focus on the wrong metrics or just don’t have a clue at all.

Therefore, I start by organizing a “Goals Exercise”. The set-up is rather simple: get the important stakeholders together in a room for 2 hours. Hand them out a bunch of Post-Its and make them think about the purpose of their job.

Some example questions that you could ask:

What outcome of your actions do you consider as success?
- E.g.: When my display campaign brings new visitors to the website
How do these outcomes benefit the company?
- E.g.: It’s an opportunity to acquire new clients
What is blocking you to achieve this outcome?
- E.g.: I’m lacking the skills to design appealing visuals

Make sure to stay away from management speak and bullshit bingo during the Goal Exercise. It works best if everyone writes down ideas in their own words.

Cluster those ideas into groups with the same underlying thought. These are the objectives that the organization should be focusing on.

I always end the “Goals Exercice” with asking the stakeholders to prioritize the objectives. This will spark a lively discussion! But in the end, you will end up with an overview of the business objectives that’s aligned and prioritized across different departments.

Then, it’s up to me to translate those objectives into actionable KPIs (e.g. % of new visitors per campaign) and define corresponding benchmarks and targets.”

Jim Sterne, President Target Marketing

“Start at the top!

What’s the one thing your executive team has been harping about lately? Are they all about growing the top line, saving money, expanding into new territories, launching new products? Chances are: all of the above. But what is their hot button? Start there and drill down.

At some point, you’ll get down to conversion rate, shopping cart value, opens and clicks but stay focused on solving business problems for as long as you can. (In between, don’t forget about those classic customer metrics of recency, frequency and monetary value.)

Find more ways to move the business needle and executives will seek out your insights.”

Jordan Louis, Web Analyst & Developer jordanlouis.ca

“Key performance indicators must be relevant to your business and the purpose of your website in it. If you’re in ecommerce, your KPIs should include metrics that relate to the art of selling things.

Dig deep with your KPIs. While many people just simply count their sales revenue, you can unlock some really useful insights that will help you optimize your business by relating one metric to another.

“Revenue per day” tells you whether there’s a particular day of week that customers buy the most on. That information could help you improve sales by running ads or promotions on slower days.

“Revenue per sale” tells you how efficient your website is at making sales. Each order costs you: buying advertising, staff to pack boxes, postage, etc. The more a customer buys in one order, the further you can stretch those costs.

Averaging out how much each customer has spent since they first visited your website tells you how much you can expect to sell to each customer. By comparing that to how much it cost you to attract each customer, you can predict how much you’ll earn with each marketing dollar spent.

Well-planned KPIs are a huge competitive advantage.”

Judah Phillips, Founder & Principal SmartCurrent

“Creating effective KPIs starts with defining the business questions that need to be informed by KPIs. It sounds so obvious, but in practice, it’s not. I’m not talking about a simple question that can be answered with data, like “what’s our weighted bounce rate by landing page by channel?” That’s not a business question. I’m talking about creating a question that drives the eventual analysis and outcome and, when answered, can help people make a decision that improves business performance. For example, “Which landing pages should we continue to use and why?” is a more helpful business question. And, sure, you could use weighted bounce rate to help frame a data – informed answer to that question. Simple, absolutely – in concept. But in reality, stakeholders may not know what questions to ask, so the better analyst in all of us should help them figure out what to ask – and then how to collect, measure, govern, and manage the resulting KPI data and eventual analysis that provides a factual answer.”

Jules Stuifbergen, Freelance Growth Marketer Stuifbergen.com

“To find actionable KPIs you should start with the action you’re going to take, and follow through from there. Formulate them like a “promise”, and commit to them as a team. Then, look at the KPI and reverse your thought process: what actions are influencing the KPI value?

Examples:
I will do more radical A/B testing when I see an upcoming local maximum which can be measured by metric Monthly Growth Rate changing to below 4% for 2 months in a row.

Growth Rate increases when you test more, better, more effective, do more research, etc.

I will stop advertising on facebook when it’s not profitable anymore which can be measured by metric Monthly Return on Ad Spend (ROAS) becomes negative.

ROAS can be increased by better targeting, cheaper CPM, better landing pages, etc.

This way, you’re putting actions first, and use KPIs as a true action monitor.”

Julian Juenemann, Founder MeasureSchool

“Being curious. Like in any Digital Analytics process we start by asking questions. Lots of them. When it comes to KPIs you first want to deeply understand the business needs, wants and outcome before attempting to slap a KPI on it. My favorite question still is “so what?” (by the infamous Avinash). “The KPI went up” So What? How will it change your organizations behaviour? What action will you take? If there are good answers to your question then the KPI will facilitate insight, action and maybe even change within an organization. So always make sure to stay curious when defining actionable KPIs.”

Manoj Jasra, Director of Digital Shaw Communications

“The most important strategy from my perspective is defining KPIs that are aligned to your organization’s overall KPIs / goals. Furthermore I have found success with taking these top-line KPIs and breaking them further down so that each person on my team truly understands the work they do and its impact to the overall organization’s success.

For example:

Overall Organization: EBITDA / Revenue / Free Cash Flow
Digital Organization: Online Channel Revenue / Online Revenue Mix / Online Channel Cost of Sale
Digital Manager: Cost of Acquisition / Conversion Rate / Revenue by Product
Digital Lead: Landing Page & Campaign Performance / Conversion by Desktop vs. Mobile”

Marco Pasin, Founder Analytics for Fun

“An actionable KPI should reproduce the most important objective of a business in a number. This way decision makers can quickly see if they are succeeding or not. To define a great KPI you need to UNDERSTAND the business or micro area you are measuring. Ask stakeholders, let them think and together figure out the best indicator tied to success. A sudden change in the KPI should create an alert and call for further analysis like segmentation.”

Michele Kiss, Senior Partner Analytics Demystified

“There are three main criteria I use when helping clients define their KPIs.

1) There can only be a few (“Key”)

If you start listing 10 or 20 different metrics, we have lost the “Key” from KPI. To constitute a KPI, it must be one of just a few select metrics that really matter.

2) It must matter if the numbers change (“Indicator”)

A spike or decline must indicate that there is a problem (or an opportunity) and spur “diagnostic mode” to find the cause. A metric that fluctuates constantly, without concern, or a stable metric that never changes – those are not KPIs.

3) You need to be able to do something about it (“Performance”)

A KPI must reflect your performance. If a metric is wholly dependent upon market forces, it is not a KPI. If a metric is out of your company’s control, it is not a KPI. (For example, you can affect revenue, but not the taxes you charge customers!) A KPI is something that you can take action upon, and that responds to your actions.”

Mikko Piippo, Analytics Consultant & Partner Hopkins Inc.

“You can never find great KPIs if you let Google Analytics limit your vision.

No matter how many Google Analytics reports you look at, no matter how you slice and segment the hits, sessions and users, your vision is too limited. You can torture the analytics reports for hours and you still can’t decide whether you should use Net Promoter Score, percentage of goods returned, number of telephone calls answered, churn or task completion rate as KPIs.

Choosing the KPIs of any organization is a strategic decision. As such we should facilitate the process of choosing them instead of trying to define the KPIs without client participation. We should also remember that the KPIs differ from department to department. Too often, the KPIs implemented and reported by web analysts are based only on the needs of marketing and sales.

So the first step for finding great actionable KPIs is to log out from Google Analytics, buy stacks of Post-it stickies and pens, schedule a series of interviews and workshops, and show your management consulting skills. It won’t be easy, but it is necessary before you can even dream of convincing the C-level to choose a set of KPIs.”

Mikko Piippo is Analytics Consultant and Partner of Hopkins Inc., Helsinki. He also blogs about Google Analytics at MikkoPiippo.com.

Paolo Zanzottera, Product Manager & Board Member ShinyStat

“In my opinion the number one strategy to define and choose your actionable KPIs is linked to two main questions every analyst and digital manager (in every digital niche) should ask before starting any digital project and investment.

#1 Question, the most important, is “Why?”: WHY am I doing this PPC campaign, WHY am I posting on Facebook, WHY have I built this website?

When you ask WHY, you’re forcing yourself to write down some objectives and goals. Try to transform the WHY answers from text to numbers: WHY am I posting on Facebook? ANSWER: I want to start a new conversation with my students to increase their knowledge and I want to create relationships with them that last longer than their university career —> This is a long and comprehensive text answer, now transform it in numbers —> I want to receive an average of 25 comments on every post from my students and I want at least 10 unique students commenting on my post. Now I like it!

So in this case I should use as KPIs #comments per post and #unique answers per post.

#2 Question: may I influence the KPIs I’ve fixed with Question #1? If you sell ice-creams you like hot and sunny days and you don’t like when it’s raining with 4°C: you know you will sell less ice creams that day, but you can’t influence the weather (not for the moment at least), so weather conditions will never be “actionable”.

In digital many times we can influence our KPIs. In this case you’ve found “Actionable KPIs”: in the example above: if I send a newsletter to the students with the link to the Facebook posts we can improve # of comments and # of people engaged. If I publish an abstract of the FB post in the University Intranet Learning Platform I can change those numbers.

An actionable KPI is a number intrinsic to the WHY of your digital project that you can directly AFFECT. An actionable KPI is “An answer to the WHY that we can CHANGE”.”

Pere Rovira, Director OneTandem

“There are no actionable KPIs without actionable objectives. So, the first thing is to create an actionable objective. For instance, many clients tell me that their objective is “To increase sales”. The problem with such an objective is that I have no clue what to do next. Should I just increase Adwords budget and hope to sell more? I don’t have context either. What does it mean to “increase sales”? When is it enough? It is very difficult to start thinking of actions if I don’t know what I want to achieve.

So I ask the client to change the way the objective is described. For instance, we might rephrase it as “Increase monthly sales by 10% compared to previous year, focusing on average order value”. Hence, I know that I need to measure two KPIs: monthly sales and average order value (AOV). I also have a target for each KPI: last year’s monthly sales and AOV. Therefore, I know what I want to change, and where I want to get. And this is to me an actionable KPI, forcing you to go from A to B.”

Petri Mertanen, Director Digital Analytics Annalect Finland

”There are so many good answers already from my peers. The very first question usually is: what should the visitors do on our website and how much money do these actions produce for the company? This is the final step of the conversion path. However, my tip is regarding the engagement part of the KPIs. I tend to ask from clients: what is the most important element on your website, home page or landing page, that visitors should click? When you tag and measure that element, you are able to create a segment of visitors who clicked and evaluate if those visitors converted better than those visitors who didn’t click. This is the first step of conversion path analysis and an important step towards conversion rate analysis. In addition to the click data, qualitative data (like heatmaps) is very useful for getting insights. With quantitative and qualitative data, you should easily get new testing ideas for the page.”

Rod Jacka, Managing Director Panalysis

“KPI is one of the most overused of all business acronyms and it is used very loosely. For something to be treated as a Key Performance Indicator it must have a direct relationship to the overall business outcome. For the KPI to be actionable it must be clearly understandable and that any changes in the indicator can be traced to one or more causes.

All too often we see businesses using very poorly thought out KPIs. The result is a lot of wasted time and unnecessary angst. (Hint: Never use bounce rate or total users or sessions as a KPI. They are important but they are not KPIs).

My number one strategy is as follows:

Identify the business outcome that is to be measured. (e.g. total profit)
Identify and rank all the possible influences on this (e.g. cost of goods sold, customer acquisition cost, etc)
Identify the top influencing factors that you can control.
Use statistical tools to identify if there is a relationship between these and the business outcome. (e.g. correlation matrix, regression analysis, etc)
Pick the most important ones that are both controllable and have a relationship.
Document the actions that can be taken if the KPI changes.

If you can’t control it and there isn’t a strong relationship then it is probably not worth treating as a KPI.”

Sameer Khan, Founder KeyWebMetrics

“My #1 strategy has always been and will always be to tie the KPIs to the business objectives. Business objectives should define the company’s strategic outlook and the underlying performance metrics. This will set the business for success as the leaders can rely on the KPIs measure the performance of the business and it’s progress. KPIs that are not tied to business objectives must be deleted or de-prioritized.”

Stéphane Hamel, Digital Analytics Thought Leader & Faculty Chair, Digital Analytics, SimpliLearn / Market Motive

KPI Traceability – “Traceability in the food industry refers to the ability to track all stages of production, processing and distribution. Closer to our field, traceability of data refers to the ability to track the origin, transformation and usage of data, especially when it relates to privacy.

Conversely, if you can’t trace a metric back to one of Revenue, Costs, or Satisfaction, it’s not a good KPI, as shown in the simple chart below:

Note that “Satisfaction” relates to customers, but also to investors, managers, government, or even employees – ultimately, they all have an impact on the sustainability of the business. In my workshops, I talk about Critical to Quality (CTQ). For example, if the strategy is to increase profitability, we can work on increasing revenue, or reducing costs. Metrics such as Qualified Sessions, Conversion Rate, Number of Transactions and Average Order Value would tie back to Revenue, while Cost of Goods, Transaction Fee, Returns Ratio and such would relate to Costs. From a tactical standpoint, I can’t possibly work on everything, but I can easily develop a few tactics to influence those underlying metrics.”

Tom van den Berg, Analytics & Optimization Expert Online Dialogue

“KPIs are more or less the most important subject to meet about in every company (especially big corporates). Every department has it’s own KPIs and they differ a lot between departments. Most of the times they are conflicting as well. For me the best strategy is to have a couple of clear KPIs which are set in the top of the organisation. Everybody in the organization is working together to improve these KPIs, instead of working against each other.

These KPIs should be SMART (specific, measure, attainable, relevant, time-frame) and used for a longer time so it possible to see an improvement.

And don’t forget your customers instead of only looking to numbers or percentages…”

———-

By now you are probably overwhelmed by this wealth of knowledge!

I hope you have enjoyed reading these awesome strategies as much as I do. What is your main takeaway?

Don’t forget to leave a comment and please share the post if you like it.

The post 42 Analytics Experts Share Their Best Strategy to Define Actionable KPIs appeared first on Online Metrics.

49 Analytics Experts Share Their Best Strategy to Turn Data into Actionable Insights

Paul Koks — Tue, 07 Jun 2016 07:05:24 +0000

“When you have mastered numbers, you will in fact no longer be reading numbers, any more than you read words when reading books. You will be reading meanings.”
~ W.E.B. Du Bois

Numbers and meanings are similar to data and actionable insights.

Data is great, but data by itself is not enough.

Big data is awesome, but it can easily lead to data overload.

We live in a world where the number of data sources available is growing every day.

You need to find the best way to make your data insanely useful. This to improve your online objectives and business goals.

I have been busy connecting to over 100 Analytics Experts around the globe, making a mess of my email box and in spending dozens of hours to collect the answers and compile the post.

An AWESOME experience! :-)

It doesn’t matter whether you run your own business, are a digital marketing consultant or analyst. Either way you will benefit from reading and implementing the awesome tips and strategies from the experts shown below:

They have all answered the following question:

“What is your number one strategy to turn data into actionable insights?”

Without further ado, here are the experts…

Alex Clemmons from Cardinal Path

“It all starts up front: on day one of the project everyone should ask themselves “what questions do we need to answer in order to succeed?” From there you can determine the data you need to collect to answer these questions. Additionally, since you’re asking this question on the first day you give yourself enough time to properly capture that data before your project launches.

Build a measurement strategy to capture this and then treat it as your analytics roadmap through the entire project. That way once it’s time to actually run your analysis you’ll have a blueprint for where to start and have the confidence to know that you already have good, clean data to base your hypothesis on.”

Amir Tohid from Analytics Effect

“In my opinion, first of all companies should have a clear understanding of what they want to achieve and what are their business goals. My approach is to always start with “small data” which makes it easier to produce insights fast. Filtering, grouping and segmenting the data plays a very important role.

During analysis stage, I always focus on trends, not data itself. The best insight comes from looking at trends especially when they change direction and I compare time ranges such as week over week, month over month etc. Moreover, I also search for strong relationships between variables or correlations.

This is a practice and this has to be done over and over again to improve the desired outcomes.”

André Mafei from Upmize

“My strategy to turn data into actionable insights is to integrate data sources for better and faster business decisions.

Data warehouses should do this, but one of the problems is that to integrate new data sources and to build new reports it is necessary the help of IT, what causes overload, then teams quit waiting and create their own solutions, ending in several “data silos” (nice name for “data mess”).

Another problem is the cost for large amounts of data, what made online companies like Google and Facebook invest in creating new big data solutions like Hadoop.

So the solution is to integrate traditional databases and big data solutions into a unified place where you can control:

1) Collection (integrations, elasticity),
2) Management (data quality, governance),
3) Analysis (data exploration),
4) Data solutions (automation).

Tip: research about data lake and CDO (Chief Data Officer).”

Andrey Osadchuk from BizTech Enterprise Solutions

“Make sure that the insights are aligned with the business requirements and primary KPIs of the decision makers. The analysis should be focused to help businesses reach their goals. Work on a single problem at a time. Build a story and talk to those whose KPIs it affects. While for one audience a positive expression like “you will get extra $ if” works best, for the others consider a negative scenario “you will lose $ if”. Start with small actions, break complex ones into pieces and proceed with them sequentially. The insight can be called actionable not earlier than the first action is completed.”

Andy Crestodina from Orbit Media

“First, don’t confuse reporting for analysis. Looking at reports isn’t the same as finding insights and taking action.

This is what reporting looks like…

The line goes up, you smile! The line goes down, you frown.

But analysis means more. It means…

Asking questions and finding answers in the data.
Forming hypothesis, testing and measuring results in the data.
Understanding the meaning behind the numbers and lines and taking action based on that new understanding.

Most people who say they “use Analytics” are really just looking at reports.”

Ani Lopez from Dynamical.biz Consulting Inc

“Obviously ‘actionable’ is the key here, especially when ‘insights’ is such a buzzword in the digital analytics industry. Data can be transformed into many things, shiny useless things for the analyst’s self indulgence or solid profits for the company.

To make data actionable, business goals have to be the true north in your compass while working at any given point of a measurement strategy but more importantly when you dive under an ocean of data trying to come up with hypothesis to validate as it’s easy to overlook the context and the objectives.

In practical terms, print them in big bold letters and place that paper somewhere in front of you.

Different questions are if stakeholders provide clear business objectives and if they have the vision to take action upon analysts’ recommendations but that’s a nightmare to debate another day.”

Annemarie Klaassen from Online Dialogue

“My number one strategy to turn data into actionable insights is to ask yourself what you are really looking for. If you don’t have a clearly defined and specific question you certainly won’t get a clear answer either. If you ask generic questions, you will get generic answers which aren’t very actionable. Ask specific questions and you will get specific actionable data!

Say for example that the question you need to answer is: “how well is our website performing”?. This is a very generic question and being an analyst you’re prone to dig deep into the data and come up with all kinds of metrics and graphs: you make a graph of the bounce rates over time, you analyze the page load time, the number of conversions (micro and macro), the revenue per product category per traffic source and so on. All the metrics indicate some form of performance, but none will tell you the exact answer. A better actionable question would be: “which product categories are underperforming in comparison to last year and can this be explained by certain traffic sources or marketing campaigns?”

Ben Adams from The Wharton School

“What is the question you’re trying to answer? As a data scientist, you should always start out with a question. Once you have a question (or set of questions) then ask yourself this: how is my behaviour going to change – how is my organization’s behaviour going to change – as a result of the answer? It may be great to say “75% of our customers are on the East Coast” but are you going to do anything differently knowing that number? How about: “75% of our paying customers are on the East Coast, and we send 50% of our mail to the West Coast.” Now you’ve got a behaviour change ready, based on data.”

Brian Clifton from Successful Analytics

“A company’s ability to satisfy the needs of a website visitor depends on two important factors:

1. Visitor expectations, discerned from how they got to your content— what search engine, campaign ads, or social conversation drove their decision to seek you out.

2. User experience, how easy it was to use your content, to navigate around and to engage with you (contact you, purchase, subscribe, give feedback).

It is your organisation’s ability to manage, analyse, and improve these two factors that determines your digital success (or not). The key is to think in terms of insights—not data.

When Paul came to me with his question, I thought long and hard about how to answer it. Essentially there is no single strategy or silver bullet that an organisation should focus on in order to gain insights (its why I write books on the subject!)

Producing insights requires an understanding of your business and its products, your value proposition, your website content, its engagement points and processes, and of course its marketing plan. Your analytics tool provides the data (and lots of it) that enables you to assess these. However, people—not machines—build insights. Smart people are required to sift through the noise to find the useful data, translate it into information to explain what is happening, then build stories of useful knowledge for the organisation—the insights.

This process is a detailed one by necessity. Building an environment where you can trust your data, understand it, and make important decisions based on it requires a deep level of immersion, not a superficial scan of reports. It also has a breath that, if it is to be successful, it must involve numerous people at senior levels of your organisation. In other words, it’s a “team” effort. In most scenarios this means combining your internal business experts with the expertise of external analytics specialists.”

Brian Clifton (PhD) is the best selling author of Successful Analytics: Gain Business Insights By Using Google Analytics and the series Advanced Web Metrics with Google Analytics. He was Google’s first Head of Web Analytics for Europe (2005-8) and built the first pan-European team of product specialists. A legacy of his work is the online learning centre for the Google Analytics Individual Qualification (GAIQ).

Carlos Escalera from Ohow.co

“The key for turning data into actions is learning to interpret what it is trying to tell you. For instance, one of the (many) steps of my daily strategy is the deep analysis of the bounce rate. This critical and often misinterpreted metric, besides helping me measuring experiments and improving the user experience which are common scenarios for any analyst, also had helped me find broken code on my site or even generate new ideas for posts. A couple of examples:

If you’re a fan of plugins, especially if you like to tweak them as I do, occasionally things can break, due to updates or incompatibility with new plugins. If the broken plugin is not used widely on your site, it is hard to detect it. Here is where the bounce rate comes to the rescue; sudden changes can help you detect broken parts on your site and repair the damage to stop the leak of readers/customers.

Now, bounce rate and generating new ideas for posts may sound weird, but it actually works. When an old post starts leading more visits than usual out of nowhere but at the same time the bounce rate increases, it means that initial purpose of the post doesn’t fulfill the need of the new readers. This behavior instead of a problem frequently indicates an opportunity, sometimes to update old content or create a new post where you can redirect that audience.

Just recently, I used these in one of my articles talking about the last year update of mobile friendliness, on which I only had to adapt the introduction to get people looking for fresh information about the topic to stay and read.

In these cases interpreting the data, rather than just seeing the numbers as more, less, high or low, helped find opportunities that otherwise would have been hard to see.”

Charles Farina from Analytics Pros

“In order to drive the action in “actionable insights” it’s critical that your data and insights are relatable. Many analysts are unable to drive action, because they never tie their findings to business impact. Insights start with the question you are answering. That question is the key to driving action. Start with this question, measure the loss/gain caused by your finding, and then answer the question by recommending your actions. The easiest path for most analysts to actionable insights is through a solid optimization program they can plug into.”

Chris Meares from MaassMedia

“Data by itself does not lead to actionable insights. First one has to understand the business questions that are trying to be solved as on organization. This could be as simple as which marketing channel drives the most revenue or as complex as measuring the lifetime value of consumers that download a company’s app. Once the business questions are known, we can then understand which specific data needs to be collected and analyzed. Through this data analysis we can begin to create hypotheses to answer specific business questions and test our hypotheses to gain actionable insights.”

Damion Brown from Data Runs Deep

“I’m going to kind of steal an idea from Simon Sinek and say that for truly successful insight, you need to Start With Why.

There’s a temptation as an analyst to focus on things like new report features or stuff that’s “interesting” – and as many have said, the word “interesting” is probably the most pointless word in the web analyst’s lexicon.

By starting with the Why, you’re aligning the process to the organisation’s most important outcomes, and you’re not getting distracted investigating tangents and disappearing down rabbit holes.”

Daniel Waisberg from Online Behavior

“Make it interesting. As with anything in life, boring stuff is more likely to be ignored. A smart analysis can have powerful and actionable insights, but if it is not presented in an interesting way it won’t be “heard”. I’ve written about creating data stories in the past, and with the launch of Data Studio for everyone, that became easier and more effective! So next time you find yourself creating a report full of tables and pie charts, think a little harder and try building clear visualizations that communicate the data in a more understandable way.”

David Kamm from iBeam Marketing Consulting Services

“My top strategy and guidance for turning analytics data into actionable insights is to be very clear about how specific metrics being tracked contribute to one or more business goals of the organization. If these connections to desired outcomes aren’t clear to all involved, and/or aren’t direct enough, then the movements in the data won’t mean much and these metrics will just contribute to ‘analytics overload’.

When metrics are both insightful and actionable, the team monitoring them can learn something new by watching the data; something they didn’t really know before. And the team can make real-world marketing adjustments based on the data (e.g., new content or campaign changes), with reasonable confidence that these changes will impact the metrics that matter.

So it’s about measuring the right things based on business goals, and understanding how potential changes are likely to drive these metrics in a positive direction.”

Dean Levitt from Teacup Analytics

“All analysis can be boiled down into three possible possible actions. You could do nothing, for example if a channel is insignificantly small. You could optimize, if a channel is not converting well. Third, you could grow a channel that is performing well.

Take a look at any channel or segment and you’ll notice that everything falls into one of these three categories. Assuming a channel doesn’t fit in the “do nothing” group, once you know whether to optimize a channel or to grow it, deciding on the right action can be as simple as using Google to ask, “how do I grow organic search.”

Dominic Hurst from dominichurst.com

“For me the key in turning data into actionable insights revolves around setting an underlying digital goals framework from your organisations objectives.

Straight away you can focus your time and effort on dimensions and metrics that really matter. No more top pages or aggregated metric dashboards that are meaningless never mind insightful.

The extra time comes in handy though as you now have the time to dig deep, segment and filter your data, uncovering the true insight behind a number.

But it doesn’t end there. Because you have a goal at stake, a goal management is aligned too; your insights have impact and become actionable. For example you might uncover that a drop in a goal is linked solely to mobile and fell on a certain date. Working with developers you can find out how a recent release broke the responsive view. Now showing the metric and this insight gives management an immediate action to take.”

Doug Hall from ConversionWorks

“Remember, you’re working for the user.

It’s so easy to get into a cynical and wrong frame of mind:
– What’s converting?
– How do I get the user to do what I want?
– How can I better monetise users?

Yuk. No. Wrong! Users aren’t meat that you shove into the top of a grinding machine to produce conversions. Users are your customers and your site needs to deliver what the user wants.

Great sites aren’t great because they make loads of money, great sites make loads of money because they are great.

Users are the judge of the greatness of your site so your data is your users telling you how to make your site better for them. Embrace these insights, deliver for your users first and business success will follow.”

Egan van Doorn from eganvandoorn.nl

“Choose your metrics wisely, make sure that they connect with the goals of your organization and educate everyone working with the data how these metrics contribute (or add up) to the main KPI. The ones receiving the data should be able to influence the metric within their responsibilities for the site, marketing or product. Next up, always… ALWAYS report against target. Setting up targets for every metric in your KPI chain indicates that you thought about the implication and attribution of a specific metric in reaching your overall organization goal(s).”

Eric Fettman from E-Nor

“People: invest in people who have passion for both analytics and end-user experience. While our industry has evolved tremendously, and while the new generation of marketers is now more data-aware than ever, we’re still not dedicating enough resources to turn data into action. Organizations that are achieving positive impacts are those that put data-driven, customer-focused problem solvers behind all digital transformation initiatives.

Process: closely aligned with the previous thought, and as is true in so many industries, process and consistency are what keeps the lights on. At the implementation phase of a Web or mobile analytics platform, are you completing the audit and QA necessary to address all potential gaps and flaws in your data capture and integration? For inbound email, SEM, banner, remarketing, paid/non-paid social, and SMS campaigns, are you taking the little bit of extra time necessary to tag your inbound links, and in way that populates your acquisition data as a smooth, unfragmented, understandable hierarchy? At even a more basic level, are you maintaining a timeline with specific dates for these marketing campaigns, as well as for design and development changes and fixes, planned (or unplanned) downtime, and any other factors that you need to remember so you can coherently interpret your data one or two or six months after the fact?

Success: it’s a worthy mantra: focus on success. Define your success early on, re-evaluate your definition of success periodically, and make sure to focus your analysis on success. At which stages are users dropping out of your conversion funnel? Which marketing channels are generating the greatest Ecommerce revenue, both for last click and assists? Consistently drive towards improvement for a small and very deliberate set of KPIs, through analytics, testing, and also qualitative inputs: this is the catalyst for long-term, bottom-line benefit.”

Eric Siegel from Predictive Analytics World

“The most actionable win from big data is predictive analytics, since each of the millions of per-individual predictions it generates directly inform the treatment or action taken towards that individual – such as whether to call, mail, approve, test, diagnose, warn, investigate, incarcerate, set up on a date, or medicate. This is the form of information technology that’s transforming all the main activities organizations do, bolstering the effectiveness of our largest-scale operations.

“Predictive analytics applies across sectors and functions – it targets marketing, streamlines manufacturing, drives fraud prevention, improves financial decisions, optimizes social networks, empowers spam filters, fine-tunes law enforcement investigations, improves healthcare decisions, and optimizes political campaign activities.”

Eric Siegel is the author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (www.thepredictionbook.com).

Franck Scandolera from webAnalyste

“As an expert on data implementation, my first strategy to turn data into actionable insights, is to collect actionable data, like the most useful attributes of the traffic source, of the content, of the product, of the customer, of the visitor, of the functionality to analyze the factors (independent variables in predictive analysis) and the segments (characteristics of cluster analysis) that affect the conversion.

Foremost, the actionable data should be valid and reliable, the measurement of the phenomena must be correct, and that one time or thousand times in the context given.

As an expert on data analysis, my first strategy to turn data into actionable information is to get a good understand of the business answers researched. Once you are at the end of the story, it’s easier to determine the best data set (dimensions and metrics), the appropriate techniques for analysis (simple, transparent and replicable) and the best visualization to tell the story of “what is important and why you should care”.

As an expert on conversion optimization, my first strategy to turn data into actionable information is to explore conversion funnel data to understand patterns and trends, and detect anomalous data (outliers) or UX error data (404, JavaScript errors, CMS error messages). In addition I listen to the voice of customer through the web and check for some heuristics/persuasion problems of user interfaces. Finally, all of these insights allow me to develop optimization assumptions.

In summary, actionable insight = good understanding of the business questions + good, valid and reliable data set + good data visualization + good story.”

Himanshu Sharma from Optimize Smart

“I have no number 1 strategy as such. I follow a process. In that process I create strategies, which vary from business to business. So there is no one size fit all strategy. Moreover, I do not use strategies to turn data into insight.

For that I rely on my data interpretation skills (maths and statistics). My strategies are largely geared towards ‘getting things done’ (like convincing the client for carrying out a test) which I think is the most important and challenging aspect of providing consultation and solving customers’ problems.

Everyone has got data and everyone has got their own personal data driven insight (aka opinion). Different people can interpret the same data differently. It all depends upon the context in which they analyse and interpret the data. The one who has got superior understanding of context, will interpret the data more accurately.”

Jacob Knettel from PFSweb

“The key to turning data into actionable insight comes from knowing the true business goals for the client or brand you are working for. When the analyst knows these goals (whether macro or micro), he can focus you his measurements, insights and recommendations around improving these goals. This creates a beautiful harmony between the analyst and end-user, where the analyst feels empowered because he/she knows that what they are researching is going to be meaningful for the business, and at the same time, the end-user gets the information they actually need to make smart business decisions.

Without knowing the business goals, an analyst can spend hours mining for gold, when at the end of the day, what the business really needs is silver.”

Jean-François Belisle from Flatbook

“The number one strategy is to truly understand the “customers behind the data”. Thus, you need to be fully-aligned with the business unit experts. You need to meet them, to lunch with them and to challenge them. They are the ones who have the best “feeling” about the customers that generate your data since they are the ones who interact with them. This is why client representatives are often a golden mine of information about a company’s customers. They are not data experts, but they are the ones who can tell you why you have some strange results and then you can take these insights into account for your analyses. To conclude, “truly understanding the customers behind the data” is what makes the difference between a good analyst and a great analyst and in many cases it makes the difference between “being listened” versus “being indispensable” in an organization.”

Jeff Sauer from Jeffalytics

“The first thing I do with any set of data is establish context with what I am seeing. What do these numbers mean? Are they important? Does it affect the way we do business? Once this is established, I use the important data to establish our baseline performance. This is the stake in the ground for how we have been doing to this point.

Now, as a marketer, my focus turns to growth. Growing beyond our baseline to continuously improve upon these efforts. This involves setting targets and establishing a plan for getting more. Then it’s all about working the plan (and checking back with your data to make sure things are working as planned.)

While I don’t really use the term actionable insights anywhere along the way, this entire process of continuous improvement can be summarized as using data to take action.”

Jim Gianoglio from LunaMetrics

“The biggest problem I see in organizations is the assumption that having a lot of data will automatically reveal a panacea. They think if they can figure out how to manipulate the data in just the right ways, or use the latest big data tool or service, then actionable insights will just begin to appear.

The best strategy to get insights comes before the data collection, tool selection, or analysis. The number one strategy to get insights is to ask the right questions! Exploratory analysis is important (and fun!), but trying to get insights that way is like going to the grocery store hungry and without a list. You end up putting everything in your cart, whether you need it or not. If you have a focused, business-critical question that needs to be answered, then that informs the data collection, analysis and visualization that will reveal the most important insights.”

Jim Sterne from Target Marketing

“If I can only pick one strategy to, it would be to clearly and deeply understand the problem to be solved. A talented tea leaf or tarot card reader will engage you in conversation and use the tea or the cards as a tool to find out what you feel is important – and have you create the ‘fortune’. The difference with analytics is that there actually is something of value inside the crystal ball. That information has value when it is turned into insights based on the conversation with the ‘client’. Those insights will be actionable because the client will share ownership.”

Joel Davis from Google Analytics Demystified

“Don’t focus on or obsess about any one particular metric. While each individual metric has the potential to provide important insights and direction for strategic decisions, it is only when you understand the overall pattern of responses that you obtain the deepest insights. One way to uncover overall patterns and interrelationships among metrics is to view each individual metric as if it were a piece of a jig saw puzzle… How does the insight from each metric fit with what is learned/revealed from other metrics? How does simultaneously viewing two or more metrics provide a different perspective than viewing each metric individually? Is the pattern of response the same or different across different but related metrics? Finally, once the pattern across metrics is established, the last – and most important – task is to identify what pieces are missing and determine why the observed pattern is occurring.”

Jordan Louis from jordanlouis.ca

“When you’re looking to turn data into actionable insights, you’ve got to make sure you’re aware of the context within which that data was collected. You can’t take action on data if you don’t know what it means or why it is significant. If I’m reporting and analyzing data from a national census, I’m going to treat it differently from sales and advertising data from an e-commerce website because the data in each case is talking about different things. However, you can and should use one dataset to inform the action taken on another, such as using the average income by postal code from the census to better target your advertising efforts, then measure the effect this has on sales per advertising dollar. Just be sure not to get confused: data will tell you different things depending on where it’s coming from. A smart analyst appreciates the context.”

Julian Juenemann from MeasureSchool

“My number one strategy: Applied segments. Digital Analytics comes down to segmenting, segmenting and segmenting again to understand the user behaviour. Once you have identified a profitable segment it is time to take action. Retargeting and targeted Emails are my first choice to get from data to action. It is simpler than ever to user your GA advanced segments to build a Remarketing list or tag your email subscribers with the help of Google Tag Manager. The positive effects will be visible to the bottom line in no time and you will have proven the ROI of your analysis.”

Julien Coquet from juliencoquet.com

“The first strategy I apply is the actual data collection strategy, which is too often overlooked. This implies playing the role of the “analytics midwife” in workshops with digital marketers in which the goal is to get them to express their measurement requirements: what kind of information they want to collect about their content, campaigns and visitors.

This may sound like Analytics 101 but in reality most marketers usually start collecting useless data before resorting to contacting me because their data is rotten.

From the requirement gathering phase, define your tagging plan, which can be translated into actual tagging via “manual” JavaScript or via a tag management system such as Google Tag Manager.

But that doesn’t stop there: once technical partners implement your tagging, you need to verify that the decisions you make based on digital analytics data are supported by quality data – otherwise you will fail even harder.

The best way to ensure your data is collected properly is to apply data quality processes for digital analytics quality and automate data verification as much as possible.”

Kevin Anderson from ING

“A succesful analytics program needs a solid KPI framework. A KPI framework gives an overview of what the organization is trying to achieve and ties that to how we will be measuring this. This exercise will push all investments in people, tools and processes in the right direction. And most importantly it will need a continual dialogue between management and data analysts. So my number 1 strategy is: start with a set of KPI’s.”

Lea Pica from Leapica.com

“The #1 tip I have for turning simple data into actionable insights is to go the extra mile to answer all of your stakeholder’s questions along the insight spectrum. This means more than just plopping numbers in a chart, slapping a title like “Campaign Results” on it, and walking away. Nope.

This means developing a keen intuition of your stakeholder’s aspirations and challenges. Visualizing the data in a way that promotes cognition, not confusion. Clearly articulating your specific data story with as much what, how and why behind it. And finally, extending your added value by attaching recommendations that are aligned with the data story, assigned to a specific owner, and time-bound for accountability.

With this framework, you will supercharge your credibility and indispensability that go well beyond crunching numbers at your desk!”

Manoj Jasra from Shaw Communications

“I will answer this question with a slightly different lens: Having worked in large organizations over the past 9 years I would have to say the key is to build a culture that sees data as the epicenter for their digital strategy. Without this it is very difficult to consistently prioritize the value of data analysis in order to achieve actionable insights. In order to build this data-driven culture it takes: hiring the right talent who can decipher data and are passionate advocates, having a sound analytics implementation and finally championing/educating the value of insights and their impact to all levels within the organization.”

Marco Pasin from Analytics for Fun

“Segmentation! By grouping together visitors/clients that have some attributes in common I can really start digging deeper. Choosing which segments to study of course it depends on what is the business question I am trying to answer (I always define it clearly before starting any analysis!). Tools like Google Analytics have some powerful segments already built in (mobile vs desktop, converters vs non, etc.), or you can set up your own. And most data is ready to be analysed. But sometimes things get a bit harder like when I have to join online behavior data with customer databases or when trying to solve more complex data science problems. In these cases, before performing any segmentation, I need to design, clean and prepare the final dataset. Cleaning data is a critical step without which you might ruin your entire analysis.

Using meaningful data visualizations allows me to spot patterns and get insights on segments faster than just looking at tabular data. I use a lot of viz to explore, understand and present segmented data.

If you want to take action on your data, go for segmentation!”

Mike Sullivan from Analytics Edge

“Start with a hypothesis and a willingness to change if the data validates your hypothesis. Too many people jump into an analysis and expect the data to ‘talk to them’ if they look at it long enough, but if they actually see something, they aren’t willing or able to do anything with the observation. Start the analysis when you are looking for something to change or improve, then segment by as many different dimensions as possible. Note all your observations, even the negative or neutral ones. Most importantly, act on the results.”

Mikko Piippo from KliKKi

“A strategy I use very often is simple: First I split the data using a primary and a secondary dimension. In the second step I visualize the data as a heatmap. Very often this is enough for getting something out of a large matrix of numbers.

This strategy – or method – can be used in countless ways. For example, create a colored heatmap with days of week on the X axis and hour on the Y axis. Fill the matrix with conversion rates or number of conversions.

Excel and Google Sheets are the easiest tools for creating heatmaps. The visualizations are not pretty, but they are more than adequate for exploratory analysis and convincing the client.”

Quentin Laveau from Booking.com

“Always start by segmenting your data, it will give you the “WHERE on your website users are leaking” and “WHO are those users” (i.e: Returning users coming from Paid Search landing on Product page). Raw data will become Information once you understand the context and relationships between different segments.

Then, back up your clickstream data with qualitative analysis (session replay, heat maps, customer feedback). It will help you understanding the “WHY they are leaking” and “WHAT you need to change”. You have reached the Knowledge step, when your information has meaning and purpose.

Now, synthesise the knowledge by writing a hypothesis: If ___Then ___ Because ___. That’s the Understanding step, where you’re now able to take actions based on your data.”

Şahin Seçil from Frosmo Ltd.

“As you know, “Data is only valuable if you can translate it into actionable insights.” On this point, my question is: Which report can give actionable answers about conversion?

The answer is a “landing page report.” It sounds easy, right? You don’t need to create complex reports to start to define your customers. Cohort reports, CLV reports, User-ID reports, etc. can give valuable information but you should be an expert in creating and analyzing these reports.

Let’s start with checking out the top 10 top landing pages. If some of the landing pages’ conversion rates are lower than average, you should think that the users can’t get enough of the information that they are looking for. Your content can be related to your products or services, but maybe your digital marketing campaign targeting is not true. For instance, if the Adwords campaign targeting is not related, your landing page conversion rate will be worse too, or your website modules aren’t as useful as you think. Or maybe you can consider showing different content for returning visitors. Consequently, you can segment these users by checking their past behaviour.

So you can start digging into your data by looking at the landing page report to improve your KPIs.”

Sameer Khan from KeyWebMetrics

“Dataset, numbers, tables and charts are all passive signals. The story behind the data is where it all connects together. The story is what drives, motivates and inspires people. I like to invest time in developing meaningful stories from data so we can drive actions across our team and cross-functional groups in the organization. Also, always remember to provide context for each dataset before sharing reports and presentation. It will save ton of emails back and forth and prevent data-confusion.”

Sayf Sharif from Seer Interactive

“It’s imperative to understand your audience. All the other aspects of your data from acquisition, to behavior, to conversions; all revolve around the users, and how you can segment based on your specific audiences. That means digging past the standard dimensions like city or source, and defining your own custom algorithms to determine segments that can produce greater insight. How do “Gold” users behave differently than “Silver” users? How does my conversion look like month to month by cohort? Etc.”

Simo Ahava from Simoahava.com

“When talking about data and actionable insights, I believe there to be only one way to consistently deliver on those fronts: by breaking down silos in the organization. You can have the best analytics partner in the world, you can have an experienced, expert developer / IT team, you can have marketers worthy of their own TV show, but if there is a lack of communication between these stakeholders all your efforts can be in vain. The journey from data to business growth starts with a healthy organization, founded on communication and not confrontation, constantly inspired, motivated, and curious about data and the possibilities it has across the entire organization. So my number one strategy is to find the pressure points in the organization and treat those before even mentioning a single three-letter acronym such as KPI, KBO, or CLV.”

Stéphane Hamel from Immeria Consulting Services

“I often get asked “how do I start?” – well, with experience comes some wisdom… I hate to reinvent the wheel and at some point in my career I stumbled upon the Six Sigma concept of DMAIC – Define-Measure-Analyze-Improve-Control. The whole methodology covers many things and offers a ton of useful data-driven tools, but just consider this:

Define the problem or hypothesis, stakeholders and scope of analysis – you know, that whole “if you can’t measure it, you can’t manage it” (attributed to W.Edwards Deming) or “how you measure success depends on how you define success” (coined by Jim Sterne) – nice statements I rarely see clearly articulated into specific action steps;
Measure and gather relevant data and conduct basic analysis to spot anomalies;
Analyze correlations and patterns, put your statistics and visualization skills to work;
Provide insight and articulate improvement options, and finally;
Control the change by keeping an eye on relevant metrics and KPIs.

Simple enough isn’t it? Now try it! This is how you turn data into insight.”

Tim Wilson from Analytics Demystified

“Recognize that the two main ways analytics can drive value are performance measurement and hypothesis validation, and those are two fundamentally different things.

Performance measurement is where dashboards live, and it’s all about the past. It answers the question: “Where are we today… relative to where we expected to be today at some point in the past?” It should be KPI-driven, objective, automated, clear, and concise.

Hypothesis validation, on the other hand, is about the future. Nothing should ever be labeled as an “analysis” that doesn’t have a clearly articulated hypothesis. And, that hypothesis should be qualified to ensure that it has the potential to drive action. I like to capture hypotheses by completing two fill-in-the-blank statements: 1) “I believe __________.” (this is the hypothesis), and 2) “If I am right, we will __________.” (this is the qualification). Having the discipline to get these statements written down and refined saves a lot of time spent wandering through the data and producing charts that are the dreaded “interesting, but not actionable.”

Todd Belcher from BlueConic

“For me, the number one strategy involves connecting data to systems (technology) or processes (people) where action can be taken or automated. This implies that some forethought has gone into customer data and marketing automation as a whole, answering questions like “What data points for known or anonymous users are indicative of interests or intents?” and “Where can we actually make use of this data?”. If the current marketing technology stack doesn’t enable any productive response to the second question for any reason, it’s time to reconsider the components of the stack.”

Tom van den Berg from Online Dialogue

“Just data is not enough. Data is valuable only if it helps a company make better decisions. Data should tell you something. If people, who didn’t saw the data before, see the data they should have the feeling: I need to take action now. Many companies are collecting and reporting on a lot of data, but are not using it to change something.

My number one strategy is: “Cut the noise and focus on the most interesting topic / highlights.” If you are reporting on data as a web analyst, focus on the most important insight you have and elaborate on this. If you explain all the graphs from a dashboard, nobody will remember. Highlight 1-3 important findings helps to focus and people will remember this.”

Yehoshua Coren from Analytics Ninja

“Turning data into actionable insights requires asking a good question. Lots of good questions. Data itself is completely passive. It doesn’t “tell you” anything until you ask a question and then seek the answer in your data. I recommend asking questions that focus on uncovering the behavioral intent of users. Formulate a hypothesis. IF I know that a user is interested in X or trying to do Y, THEN I will take such and such action. Having an direction that you are heading in advance of your digging through your data will lead to analysis that gleans actionable insights. Of course, you’ll need to be careful of bias. Remember that the answer to your question may not be something that you expected. Be open and curious. But be clear about whether you’ll be making a UI change, marketing campaign adjustment, change to copy, running an a/b test, etc as a result of the question. Bottom line, asking good questions is the key.”

Zorin Radovančević from Escape Studio

“I strongly believe only a clear internal capability improvement strategy applied to all organizational levels will yield in an ability to truly harness data and generate any kind of a competitive advantage.

Start as soon as you can. Iterate in small increments. Build the best multidisciplinary team available which should be truly savvy in the ways of your business as the entire focus should be on predicting business outcomes. Use internal IT or outsource to build a set of tools which represent a collaborative, scalable and simple to use decision support platform. Give your team free and transparent access to data. ‘Force’ them to produce simple insights as soon as possible regardless of the predicted outcome and let the modelling games begin.”

You have just read 7.000 words of incredibly useful advice that you can directly apply to your business!

I hope you have enjoyed reading these awesome tips and strategies as much as I do! So that you can improve your skills to turn data into actionable insights.

Make sure to read this post about actionable KPIs as well. It will help you define goals and metrics that matter most for your business.

Now it’s your turn. What do you think about data and actionable insights? A comment or share is very much appreciated!

The post 49 Analytics Experts Share Their Best Strategy to Turn Data into Actionable Insights appeared first on Online Metrics.

Podcast: My Story!

Paul Koks — Tue, 31 May 2016 08:26:36 +0000

Today’s post is a bit different… You’re used to consume in-depth content that helps you turn simple data into actionable insights. At least, that’s my purpose. :-)

This time I want to share a bit more about my digital analytics journey, but I promise to provide a ton of advice at the same time!

At the end of 2012 I started this website to document my knowledge and share about my passion and ideas.

It usually works like this, I come up with a digital analytics topic and write a story around it to provide as much value as I can. And when I feel good, the words just flow naturally…

In the meantime quite a few things changed. My blog has grown from zero to over 10.000 visitors a month and thousands of subscribers. And it’s really amazing and fun to connect with awesome people like you!

You might think… hey Paul, but why this post?

Last month I met Jeff Sauer (Analytics and PPC expert) at the Google Analytics User Conference in The Netherlands. We had a great time chatting together and sharing stuff. Up to then we had regular email contact, but never met in-person. Since that time we help each other a lot and he has become a great friend!

And you know what, a few weeks later I was invited for the awesome Jumpstart Podcast. Jeff’s Podcast is filled with many prominent names in the digital marketing industry. Go check it out!

Of course I was very excited to record the podcast and share my story.

You can listen to it below (I share my digital journey in a lot of detail so don’t miss it!):

Here is a short overview of the topics that we address:

How I started doing business online on Ebay when I was just 16 years old.
How I started my career as a headhunter, but got excited about Digital Marketing and Analytics.
How building affiliate sites has skyrocketed my SEO and Analytics knowledge.
How providing value via awesome content has become one of my greatest passions.
How you can grow your career as a Digital Analyst or in any other field you are passionate about.
How you can strategically grow your blog and online presence.
Why I took the leap and gave up my corporate job just two months ago.
How I see the future of Online Metrics as a blog and online business.

Hope you enjoy listening to my story and I am happy to hear your thoughts!

The post Podcast: My Story! appeared first on Online Metrics.

How to Fine-Tune Your Search Strategy with Google Search Console

Paul Koks — Tue, 15 Mar 2016 08:00:30 +0000

Do you still worry about your organic keywords not to be visible anymore in Google Analytics? You are only a few steps away from deriving great insights through Google Search Console.

I guess organic traffic is still an important channel for you, both in traffic as well as conversions.

And you desperately want to get many data insights to feed your Search strategy?

Last year I published this highly appreciated post on SEMrush about 8 Google Analytics Reports to Boost Your SEO Performance.

It’s a great read if you want to learn more about using Google Analytics for optimizing SEO.

In this post I will show you my strategy behind Google Search Console (formerly known as Google Webmaster Tools) and optimizing for SEO.

Search Engine Ranking Factors

Luckily I have a solid background in SEO as well. Have been playing around with websites and ranking them since 2009. Some of them “died” and others perform pretty well until today. :-)

Every two years Moz surveys the opinions of the brightest search marketers around the globe.

A summary of the results from this year is given below (full report can be found here):

As you can judge by yourself, links and keywords (content) signals are still a big part of your success in SEO.

A recent post on Backlinko illustrates the findings of analyzing 1 million Google Search Results. It’s a great read!

Why to Use Google Search Console

Google Search Console provides you with many different insights you can’t find in Google Analytics or any other web analytics package.

You can learn about the technical and “marketing” performance of your website.

Here is an overview of the different things that are currently available in Google Search Console:

In the rest of this article I will show you how to use the console with a special focus on Search Analytics.

Link Google Search Console to Google Analytics

First of all I recommend to link Google Search Console to Google Analytics.

After you have set up Google Search Console it’s easy to link both products.

Step 1: Click on the settings icon in the upper right corner.

Step 2: Select the Google Analytics property where you want to enable Search Console data:

Step 3: Locate your Search Console data in Google Analytics:It’s a simple process that helps you to collect a new set of relevant search data in Google Analytics.

Derive Great Insights through Search Analytics

In the following six steps I describe how to use Search Analytics for deriving great insights:

Open Search Analytics.
Select the right date range.
Select the landing page you want to analyze.
Switch to queries.
Select the metrics you want to analyze.
Interpret the data and feed your search strategy.

I will use OnlineMetrics and one of my landing pages as an example.

1. Open Search Analytics

For your convenience here is a direct link to Search Analytics in Google Search Console.

After you have selected the right propery you will be automatically redirected to the “homepage” of Search Analytics.

2. Select the Right Data Range

First a few notes here:

You can select a period of maxium three months.
You can’t include the data of the last two days.

Tip: learn how to automatically download Google Search Analytics data on a monthly basis (great article by Paul Shapiro):

Image courtesy

In my example I select the following data range: 1st July – 31th August.

3. Select the Landing Page You Want to Analyze

Now it’s time to decide what landing page you want to analyze.

Let’s assume I am interested in keyword data for this page:

Follow the steps below to get the information you need:

And now the right page is selected:

4. Switch to Queries

Now you can see all data for one of your landing pages.

The next step is to switch to query data for this particular landing page:

5. Select the Metrics You Want to Analyze

In order to best understand how things are going I recommend to select all metrics here:

Clicks
Impressions
CTR
Position

Here is some data of one of my pages:

Filtered on Clicks

Filtered on Impressions

I am sure this data is not 100% accurate.

However, it provides you with many great insights for your search strategy. In my opinion very useful for both organic as well as paid search.

Note: you can filter on country or device type as well.

6. Interpret the Data and Feed Your Search Strategy

I have plotted all the queries in a wordcloud to get a high level overview first:

It’s clear that combinations of web, analytics and certification are the most important drivers of Google impressions for this page.

I like to finish with a list of five insights from this data:

In terms of impressions and traffic, “web analytics certification” is the best performer by far.
A bunch of long tail keywords drive a small amount of traffic to my site (not all data is here).
There are quite a few queries on page three or lower that have a substantial amount of impressions.
For the top queries there is not a strong correlation between position and CTR.
Targeting the page of “web analytics certification” instead of “web analytics education” would probably yield better results.

A long story short, these insights definitely serve as great input for fine-tuning my search strategy.

I hope you have learned something new. What are your strategies for optimizing your search performance in 2016?

The post How to Fine-Tune Your Search Strategy with Google Search Console appeared first on Online Metrics.

10 Easy Tactics to Improve Your Next Data Analysis Project

Paul Koks — Tue, 18 Aug 2015 07:00:33 +0000

Data analysis is hard. Make your life a bit easier by following a structured approach.

Two weeks ago an email triggered me to write this article. Market Motive reminded me of their courses which I took a few years ago (highly recommended!).

You might have heard it many times before, but the market for web analysts and data scientists is booming!

In the last 10 years I have consulted on over 100 websites.

Projects ranging from one hour consults for start ups to large projects and websites that generate over 10 million pageviews each month.

Every project has its own, unique challenges.

The single most important thing that I have learned is that you need a plan to succeed.

You can easily waste hours of time if you don’t know what you are doing.

In the next 10 steps I try to outline a process that is easy to follow and at the same time incredibly powerful.

It helps you to get better results from your next data analysis and in a much quicker way.

The process will fit in any web analytics tool, although I assume most of you are familiar with Google Analytics.

1. Start With a Business Question

I strongly recommend to start every data analysis with a business question. Don’t end up in just puking data out.

What are you trying to solve or improve? The more concrete the better and just write it down on paper first.

Try to go in more detail than simple stating you want to increase the conversion rate.

You might want to evaluate the market (competitors) situation as well.

Answer this single most important question before you dive into any web analytics tool.

2. Know Your Stakeholders

Are you hired to perform an internal analytics data audit? Or did your boss ask for recommendations to optimize cross-channel customer journeys?

It makes much difference if you report to a Web Analyst or ecommerce Director? And whether it’s an internal or external assignment.

Figuring out who the stakeholders are is a crucial step in your data analysis project.

3. Exceed Expectations

Great, by now you know the main business question and you have compiled a list of involved stakeholders.

Maybe there are other expectations like:

What other questions need to be solved?
When is the outcome of your analysis expected?
Do you need to report in a certain format? (Excel, Powerpoint, video presentation etc.)
Do you need to minimize the report length?
Is additional training on-the-job part of the assignment?

These and many other expectations might come up after interviewing your stakeholders.

Asking the right questions is an art.

Himanshu Sharma – one of the top bloggers in the web analytics industry – has written a thorough post on asking questions.

Take this seriously and try not only to meet, but exceed expectations.

4. Experience the Website

Don’t dive into web analytics data before you have visited the website or other environment connected to your project.

This is a very important step in your data analysis project.

What tasks can visitors fulfil? How would you define the macro and micro goals?

You might already get stuck on a few usability issues or find other areas of improvement.

Don’t get prejudiced here, but simply get an initial idea on how the website performs.

It’s great to incorporate Peter Morville’s User Experience Honeycomb in your journey.

Useful: Your content should be original and fulfill a visitors’ need
Usable: Site must be easy to use
Desirable: Image, identity, brand, and other design elements are used in the correct way
Valuable: Users must derive some value by visiting the website
Findable: Content needs to be navigable and it should be easy to find
Accessible: Content needs to be accessible to people with disabilities
Credible: Users must trust and believe your stories

Always, but especially if you are working for an external company, you will benefit from this analysis during your project.

5. Configuration Check

Ask for Google Analytics account access and check whether the implementation and configuration are done in the correct way.

I am experienced in working with several web analytics packages.

In the last few years most of my clients had Google Analytics or Adobe Analytics installed on their website(s).

Both tools can be a pain to set up correctly. I can easily state that over 80% of the accounts that I saw were incorrectly set up.

When performing a configuration check you will find out what goals are measured and other things that might be important for your data analysis.

6. General Data Quality Check

Let’s assume the website’s data you have to analyze is captured in Google Analytics.

First of all you need a good understanding of the different reports, metrics and dimensions that are available.

I would suggest to take the following steps to assess the data quality:

Take a look at diagnostics messages and spot anything that might be wrong
Evaluate traffic sources; is there a logical campaign tracking structure?
Evaluate goals (and ecommerce); do you see the right numbers showing up in Google Analytics?
Evaluate content reports: do you spot many duplicate URLs due to query parameters?
Are there any more spots that need improvement?

This step is so important. You cannot perform a good data analysis if the data quality is poor.

Larry Maguire wrote a terrific article on this topic.

Make sure to read and share it!

7. Outline Document

You need to take a different approach, if you find too many barriers in the first six steps.

In general it would mean you have to get someone (or yourself) to help get the measurement part right.

For now, let’s assume everything is set up correctly.

I have learned from experience that outlining a document can really save a huge amount of time. It actually is a must do if you want to speed up your process.

Before you start your data analysis you should think about:

What elements to include in your data analysis report
How to structure the information
From where to retrieve the information

You will know whether you needs to set up segments, custom reports or other stuff to enhance your data analysis.

Here is an example of an AB-test report outline that might come in handy as well.

8. Get Your Data

Your success lies in your preparation.

By now you have a thorough understanding of the website/business, stakeholders, business question, where the data is stored any more things that are relevant to a good data analysis.

So that you will know which reports and data you need to answer the most important business question for your project.

Read these 10 data analysis ideas to feed your ideas.

You might prefer to work with an API to easily extract the desired data. Automating your Google Analytics data export is a huge timesaver.

Make sure to keep working on your analytics skills if you want to deliver a great project.

If available, qualitative data will make your analysis even more powerful.

9. Analyze Your Data

Many people prefer to use Excel for data analysis and building charts.

I recommend not to copy simple charts from Google Analytics or other web analytics tools.

You want to visualize your data and make it the most easy to get your points and advice across.

My Online Training Hub offers a great set of Excel courses from which anyone can benefit.

I prefer to work with at least three different tab types in Excel.

This makes it easier to work with your data and transform it with magical formulas into actionable insights.

Always keep your Excel files as you might want to update your analysis in the future.

Greg Reda shares a few more data analysis methodoly thoughts:

Be skeptical about the data
Think like a trial lawyer
Clarify your assumptions
Check your work
Communicate

10. Prepare Your Report

Now it’s time to fill in your actual report (or online video) with the most important findings.

You always want to include:

Introductory section
Overview of report
Date range of your analysis
Most important findings
Conclusions
Recommendations / actionable advice

It depends on your stakeholder wishes how your final report should look like and what elements to include.

In the next video, Piyanka Jain shares how to derive decisions from data in a smart way:

It’s great to hear her talk if you have some extra time.

Bonus: Share Your Data Analysis

You have done a great job, but don’t know how to communicate your results.

Here are some general tips on how to get your message across (and make your boss or client happy):

Never just send an email without follow-up (your report might get no attention at all)
If possible, set up a real life meeting and guide your audience thoughout your presentation
Secondary option is to set up an online meeting and go through your presentation

Your job is almost done once you have communicated your findings in a proper way.

You need to make sure to check later on whether your recommendations are already implemented or not. Yes, it’s part of the job!

If you see the fruits of your labor it will be motivating and it enhances your chances of getting another assignment or a raise.

This is it from my side, hope you have learned something new!

Do you have additional tips on data analysis where others can benefit from? I am happy to hear your thoughts.

The post 10 Easy Tactics to Improve Your Next Data Analysis Project appeared first on Online Metrics.

Six Challenges of Qualitative Data Analysis

Paul Koks — Tue, 14 Jul 2015 07:00:51 +0000

In an ideal world there is both valuable quantitative as well as qualitative data available to you.

You can’t say that one data source is better than the other. They complement each other and provide you with a more accurate picture of what’s going on and why.

Both data sources are very helpful in the field of conversion optimization.

Well thought out hypothesis – based on quantitative and qualitative data – are important to define the best A/B test experiments.

However, it is very important to understand the limitations of qualitative data analysis.

In this article I share six common problems with qualitative data that you should know.

Sampling-Related Problems

The first three limitations are sampling-related issues.

1. Limited Sample Size

Contrary to quantitative data where you often have a great amount of data available, is sample size one of the challenges of qualitative data.

If you browse on the internet, you find out there is no general agreement on the ideal sample size for qualitative research.

It is very costly to perform extensive qualitative research with hundreds of participants.

And is it really needed to question so many people to get valuable insights?

Watch this video to get a better understanding of this topic:

Keep in mind that qualitative feedback from 10 or 20 participants can still help you a lot with optimizing your website.

Two tips about your sample size:

Rule of thumb: you need more participants if new participants keep on providing you with relevant, new insights.
Be flexible; don’t rigidly set the number of participants at the start.

2. Sampling Bias

Sampling bias definition by Wikipedia:

“In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population are less likely to be included than others.”

In other words, your qualitative sample will never include a representative overview of all the different people that come to your website.

It’s important to keep that in mind when interpreting test results.

3. Self-Selection Bias

Do you like to participate in surveys? A few of you might say “Yes” and others think “Arghhhh”.

This is the exact problem here. It’s a free choice to participate in a research study or not.

On the other side, quantitative data is gathered from most people whether they like it or not.

Just sign up for Hotjar, set up a heatmap and the data will be collected for you.

Ok, I don’t talk about the tech-savvy people here. ;-)

Sampling and self-selection biases are closely related and limit the usefulness of qualitative data.

Observation Biases

The second group of problems with qualitative data include observational biases.

4. Hawthorne Effect

The Hawthorne Effect can best be described as:

“Participants in behavioral studies change their behavior or performance in response to being observed.”

For example, your opinion about a particular website might be different when you know you are being observed if compared to when you (don’t know) you are being observed.

I recommend to watch this video (it clearly explains the Hawthorne Effect and its background):

5. Observer-Expectancy Effect

Let’s say you are running a survey and function as an observer in the research room. You are walking around and observe the participants.

Do you think you won’t influence the results?

It is known that researcher’s beliefs or expectations causes him or her to unconsciously influence the participants of an experiment. This is called the observer-expectancy effect.

6. Artificial Scenario

Most experiments include pre-set goals in a specific environment. And you can’t get feedback on things you don’t ask.

For example, you run an experiment for an ecommerce website.

Your goal is to find out whether the form (where people leave their personal information) functions well or if anything needs to be improved.

In this case it is such a focused goal so that you won’t learn about other valuable things through this study.

The participant might have a lot of other things to say, but without asking them you won’t know it.

Conclusions

As you can see, there are a many challenges with qualitative data.

However, marketers can perform extremely well if they use this data in combination with quantitative data to form strong A/B test hypothesis.

Refrain from changing your website on just a small set of qualitative responses.

Instead, enrich your conversion optimization framework with all data sources that are available to you and get more out of your testing efforts.

What’s your experience with qualitative data? Do you use it in combination with quantitative data?

The post Six Challenges of Qualitative Data Analysis appeared first on Online Metrics.

5 Common Web Analytics Metrics Demystified

Paul Koks — Tue, 14 Apr 2015 07:00:56 +0000

There are dozens of web analytics metrics available today. Most of them are useful to a certain extent. They should guide you on making important decisions for your business.

What if you interpret your metrics in the wrong way or wrong context? A number can tell a story, but 10 people who see the same number might all tell a different story.

In this article you will learn about five basic web analytics metrics and how to interpret them in a better way.

1. Bounce Rate

Bounce rate is one of the famous metrics in Google Analytics. Many companies tend to base crucial decisions on just this one metric.

The definition that Google Analytics uses:

“Bounce Rate is the percentage of single-page sessions (i.e. sessions in which the person left your site from the entrance page without interacting with the page).”

Let’s break it up a bit so there is no misunderstanding here:

Single-page sessions: your landing page is the same as your exit page
No interaction: no interactive event is triggered during your session

Context Delivers Value

From now one refrain from only looking at your web analytics metrics from an aggregated viewpoint.

The context helps you to interpret them in the right way.

Segment your bounce rate
1. Landing page
2. Page intent
3. Traffic source
4. Device category
5. Type of visitor
Bounce rate and type of website
1. Blog
2. Services website
3. Corporate website
4. Leadgen website
5. Ecommerce website
Bounce rate and other metrics
1. Conversion rate
2. Time on page
3. Non-pageview interactions

All these factors help you to interpret the bounce rate in a better way.

By itself and on an aggregated level, the bounce rate isn’t actionable at all!

2. Exit Rate

Two years ago I wrote a guide on bounce rates and I directly compared this web analytics metric to exit rates.

“The bounce rate is measured against the number of entrances, the exit rate is measured against a particular page.”

Something to keep in mind:

“A bounce is always an exit, but an exit doesn’t have to be a bounce.”

Actionable Exit Rate

Let’s assume your website counts thousands of pages. What could you do to transform the exit rate into an actionable metric?

Again, context is key. At what pages are you looking? Is there a difference in exit rate on the channel level? What do you want your visitors to achieve?

You need to ask yourself questions to make a metric actionable.

An example:

“You are employed at an E-commerce company and work on a framework for A/B testing purposes. Your manager asks you about the pages to start testing on first.”

In this case you should consider looking at:

High traffic (funnel) pages
Pages that are relevant to the shopping process

Try to identify “leaking buckets”: pages with a relatively high exit rate that you need to optimize for higher conversions.

And if you identify one, look at it on a segmented level as well. Is there enough room for improvement in one or more areas?

3. Conversion Rate

As a start I like to ask you a question:

“You measure in Google Analytics 1000 sessions, 500 users and 10 conversions. What is the conversion rate?”

You probably think it should be 1% or 2%:

Based on sessions: 10 / 1000 = 1%.
Based on users: 10 / 500 = 2%.

Google Analytics measures the conversion rate based on the number of sessions.

In this case, you will see 1% in Google Analytics. And do you agree with that?

An example:

“You are running a blog like me. One of your main conversions is a newsletter subscription. What you notice is a relatively high amount of returning visitors that convert. It indicates that people come back a few times before they decide to subscribe to your newsletter.”

My journey on your website (I assume you recognize me as one person with four sessions):

The screenshot above make things a bit more clear to you. I am the same person every day and my conversion rate could be 100% percent or 25% percent. The latter is the value that Google Analytics calculates.

In my opinion, it is more accurate to calculate the conversion rate based on number of users instead of sessions. Or do you think I would subscribe four times to your newsletter? :-)

The Challenge

On default it is pretty hard to get accurate user metrics in your account. Because there are too many devices and browsers in scope that might devalue this web analytics metric.

First of all you need to work with Universal Analytics and implement a UserID. That goes beyond the scope of this article.

Recommend reading:

The Magic of Universal Analytics: Strategy, Tactics, Implementation Tips by Avinash

4. Average Time on Page

First of all, I don’t like averages. Averages are very misleading. You need to know what makes up this average number.

In the example above you see 22 grades and an average score of 6,5. There are 7 students with a 5 or lower which isn’t a good grade at all!

In general, it’s better to look at distributions instead of averages.

Google Analytics calculates the time on page as follows:

The time duration between arriving on page one and arriving on page two

If you arrive at my homepage at 11.00am and the next page you see is my blog at 11.02am, you have spent 2 minutes on the homepage.

Take a look at this graph to get a better understanding of how Google Analytics calculates average time on page:

When calculating average time on page, Google Analytics doesn’t take into account visitors that bounce. The time that you have spent on the last page isn’t measured.

5. Average Time on Site

You need to ask yourself a lot of question to make this metric actionable:

How does Google Analytics actually calculates average time on site?
Do I want my visitors to stay longer on my website or is that a sign they can’t find the information quick enough?
Is there a correlation or possible causation between the average time on site and conversion rate?

And many more things should pop up in your mind when you are working with this metric.

Average time on site = average session duration.

“Google Analytics calculated average session duration as the total duration of all sessions (in seconds) / number of sessions.”

There is one thing you need to understand here. Google Analytics doesn’t measure the time you spend on the last page before you leave. And this has a huge impact on this metric.

Here is an example:

11.01am: you arrive on page-a (known)
11.05am: you arrive on page-b (known)
11.09am: you have finished your reading on page-b and leave the website (unknown)

Your session duration is measured as 4 minutes, but in reality you have spent 8 minutes on this website. Quite a difference!

Maybe you are a technical guy who can come up with a Google Analytics hack, but keep in mind you always need to be careful with that. It might impact other web analytics metrics as well.

Turn Session Duration into Insights

Every metric is useful in its own way.

If you want to look closer at session duration, you could set up a few “session duration” goals in Google Analytics:

You could compare these goals to more important – macro goals – on your website. And find out whether there is a correlation between both.

What is your opinion on web analytics metrics? How do you get the most out of your metrics?

The post 5 Common Web Analytics Metrics Demystified appeared first on Online Metrics.

The Best Web Analytics Report to Start Your Optimization Journey

Paul Koks — Tue, 03 Mar 2015 08:00:56 +0000

A lot of times people ask me about my favorite web analytics report to start an optimization journey.

For me it feels like an easy to answer question. The success of any online business (website) mainly depends on two factors:

How many qualified visitors does the website attract and from which channels?
How many of these qualified visitors perform a desired action?

It’s terrific if 10% of your website visitors order a product. However, if you just receive a few visitors a day it doesn’t mean much.

On the other hand, getting thousands of visitors but a conversion rate of 0,1%, is in general not good either.

You need to have a good balance.

Do you agree with me that traffic + conversion (and retention) are the most important metrics to start looking at?

A simplified view is given below:

Let’s forget about retention for now.

It’s too complicated to look at retention as your first metric. Optimizing on retention metrics requires in most cases both web analytics as well as back-end data.

Qualified Visitors

What’s a qualified visitor you might think.

There are quite a few definitions out there. I like to explain it in a different way.

I make it as simple as possible by defining four categories of website visitors:

Group 1: never buys
Group 2: small chance of buying
Group 3: big chance of buying
Group 4: always buys

Based on the definitions above, you like to see many visitors to fall in group 3 and 4.

As an ecommerce shop owner you prefer the number of people that fall in group 1 as low as possible.

In reality it is not so easy to influence the distribution of your website visitors.

However, you can do a lot to improve the chances of buying for people that belong to group 2 and 3.

Especially group 3 is worth investing in!

From experience I can say that making group 1 as small as possible has a lot to do with your targeting.

Who is visiting your website and through which channels?

An example of a channel where many people fall in group 1 or 2, is untargeted email / affiliate marketing campaigns.

I know companies pay lots of money to get people click through to their website to find out no one buys.

It is not unlikely that you see these campaign numbers:

20.000 visits
98% bounce rate
CR of 0.001%

Invest enough time in targeting the right visitors and you are halfway in getting great results!

Desired Action

A desired action is always connected to a micro or macro goal on your website.

Most often a micro goal is connected to (one of your) main goal(s).

Your main goal is also defined as your macro goal. It is directly tied to your online business goals.

In the example (last chapter) I talked about “buying”. A desired action is not always connected to a transaction.

It completely depends on your business what a desired action is and what not.

A few examples:

Subscribing to newsletter (blog)
Submitting a form (leadgen website)
Positive support experience (services website)
Buying a product (ecommerce website)
Watching a product movie (corporate brand website)

As you can see, there are literally thousands of desired actions you could come up with.

What does this all have to do with the best web analytics report?

By now you will better understand why I choose the All Traffic Sources by Conversion Rate as the best analytics report to start with.

No goals on your website? This can’t be true. No goals means no business.

Best Web Analytics Report

No matter which web analytics tool you use, the all traffic sources report will be available.

Maybe it is named a bit different, but it refers to all channels that drive traffic to your website.

Since most people are used to Google Analytics terminology, I call it All Traffic Sources for now.

It is very easy to open this report in your Google Analytics account.

Open Google Analytics
Click on Reporting tab
Head over to Acquisition
Click on All Traffic
Click on Channel or Source / Medium

For an overall picture – and when a lot of sources are involved – I recommend to start on the Channel or Medium level.

In this case I select channel:

This is real data from my website.

What do we see here?

Default channel grouping as primary dimension
Acquisition, Behavior and Conversions (ABC) statistics for every channel
Selected goal 1: Newsletter subscription
CR and number of conversions overall
CR and number of conversions per channel

On this particular day my CR was well above 4%. My social channel did beat the other traffic sources. There are quite a few direct and organic conversions as well.

This is a simplified example. Can you image the insights you can derive from just this report and a larger data set?

Note: it is very important that you set up your campaign tracking in the correct way. It really ruins your data if you get this wrong.

This report provides you with a first and overall understanding about how your business performs. Of course you need to dig deeper, but it’s a great start!

Concluding Thoughts

The reports that I have shared show you the sources of traffic and outcome (conversions). Two important things you should really care about.

A few last remarks:

Set up goals and goal values to get this to work.
Start on the highest level (medium or channel) and drill down to segments.
Present this Web Analytics report to your boss or client right away and they will love you for the insights they get.
Offer a few possible solutions on how to optimize each channel and they will love you even more. :-)
Think about Conversion Optimization (from a holistic viewpoint) as well. Make an optimization plan to improve the outcome for the main online business goal(s).

What’s your favorite web analytics report? How do you start your optimization journey?

The post The Best Web Analytics Report to Start Your Optimization Journey appeared first on Online Metrics.

8 Tips to Evolve From Reporting Squirrel to Analytics Ninja

Paul Koks — Tue, 17 Feb 2015 08:00:18 +0000

Minimize your reporting time and maximize your optimization efforts. And you are on the right path to become an analytics ninja!

For a lot of people this is easier said than done.

You might be stuck in corporate politics. Or you might have a lot of clients with these awful reporting needs.

You send a lot of reports and they are saved in the Inbox. And never looked at. Unfortunately this is true in a lot of cases.

I don’t say reporting is bad; it’s often overused and misabused.

Change is a must if you are stuck at 80% reporting and 20% optimization time!

It’s the same as investing 99% of your budget in traffic and 1% in CRO. It simply doesn’t work that way.

You want highly qualified visitors that are ready to convert on an astonishing platform!

Make a change before it is too late. The possible impact of automation is huge…

Believe me, it can be different! There is enough time left to save your career.

In this article I describe eight tips to change from a reporting squirrel to an analytics ninja.

Do you join me for an exciting ride? Good!

Reporting ≠ Optimization

Realize that reporting and optimization are not the same. It might sound like a no-brainer, but why are so many of us still devoting too much time to reporting?

Im my opinion:

“Reporting can aid your optimization efforts but doesn’t bring a direct ROI for you or the company you are employed.”

“Optimization efforts are directly related to improving the experience and ROI of your website visitors; this in contrast to reporting.”

External resources:

The Ultimate Definition of Analytics by Stephane Hamel.

1. Become an Expert in Your Field

There are literally hundreds of ways to expand your skillset further. When doing so you will find your influence to grow.

If you say a lot of smart things, people are more eager to listen to you.

So you could more easily persuade your colleagues and clients to take the road that leads to the best outcome for all.

Five things to embrace:

Improve 10 Vital Web Analytics Skills

One of my most popular posts is about the top 10 web analytics skills. Read it and I am sure your knowledge rollercoaster is going faster than ever before.

Read, Watch, Learn and Adapt

There are a lot of interesting blogs, books, videos, podcasts etc. out there. Make a selection and derive great ideas you could apply in your unique situation.

Last year I published a post about the top 20 Analytics blogs (recently updated).

A few other interesting reads:

Learn Statistics

A/B testing might sound easy. You have your control page and put your ideas in an ideal version – all based on a simple hypothesis – and the $$$ come in.

Sorry to disappoint you, but A/B testing and Conversion Optimization isn’t that easy.

Ideally you should know about:

The company that is involved and the competitive field
Important characteristics of “the customer”
Quantitative data (website behaviour)
Qualitative data
Persuasion elements that drive conversions

And most importantly, if you interpret the data in the wrong way, you are wasting time and money.

So make sure to learn a bit about statistics as well.

Suggested resources and tools:

Start an Online Business

The best way to learn more about reporting and optimization is by putting things in practice.

Is there a better opportunity than starting an online business (or simple website) by yourself? I don’t think so.

I recently wrote an article about why every web analyst should start an online business.

Just read it and let me know what you think!

Keep on Learning

Everything changes.

Especially in the Analytics field – a rapidly changing environment – you can’t lose your attention for a long time without being “punished”.

Keep on the edge of things and you will do great!

2. Learn How to Deal With HiPPOs

You boss, well he or she might behave as a HiPPO blocking your road to Analytics nirvana!

Read these six tips to deal with your HiPPO to avoid another obstacle.

They actually made the fun out of it a few years ago :-)

3. Automate Your Reporting Efforts

Do you like to become an analytics ninja like Yehoshua Coren?

Simply stop wasting your time with reporting every week.

Do you build dashboards in Analytics? Automate them and use the basic design and elements for future dashboards.
Do you build dashboards in Excel? Automate them with plugins and macros.

It will save you hours of your valuable time, each and every week.

Do you use Google Analytics? You will enjoy reading this post about reporting automation.

4. Report on Results

Forget pageviews, forget visits. These metrics are not the drivers of commercial success.

Develop your talent to explain and persuade your boss or client to take another direction.

Of course, no traffic means no sales. We all know that.

Put those numbers in perspective. I have seen websites with ten thousands visitors each month and hardly any sales.

What is driving online success? What keeps your business healthy in the long run? Focus on online metrics that matter and report on them!

How to discover great metrics? Read on, you won’t reget it!

5. Formulate Great Questions

Every web analyst should learn how to ask questions.

If you ask the right questions, you can quickly solve customer problems. And find out what are the exact reporting needs that actually make sense.

Have you heard about the five whys? It’s an effective method to find the root causes behind a problem. And distill an opportunity to make things better.

Here are 11 questioning tips from a fantastic post written by Himanshu Sharma.

Overcome your fear of asking questions.
No question is a stupid question.
Ask questions whose answers seem pretty obvious.
Don’t try to figure out everything on your own.
Acknowledge the expertise of your client by asking questions.
Ask questions every day.
Give answers that sound like questions.
Your client already know the answer, he is just unaware of it.
Raise objections by asking questions.
Ask follow up questions.
Make asking questions your daily habit.

And I do agree that asking questions will skyrocket your Analytics career!

6. Determine One Key Metric

In relation to this point, I like to refer to two books you should have on your bookshelves:

Lean Analytics by Alistair Croll and Benjamin Yoskovitz
The Lean Startup by Eric Ries

A lot of people talk about these books and principles behind in relation to startups. I feel the lean and agile approach should apply to any business in one way or the other.

As a web analyst you are equipped with a lot of tasks. During the optimization process you don’t want to focus on the wrong metrics.

Like discussed before, it is very important to ask questions.

In addition, finding One Metric That Matters (OMTM) is crucial. Both for you as well as the business your work for.

In Lean Analytics the three core principles are:

What business are you in?
What stage are you at?
Who is your audience?

Take the time to answer these questions for you specific situation and you will move closer to your metric that matters.

Watch this video by Alistair Croll if you have some free time (96 min to be exact) :-):

Or give yourself FREE access to this Udemy course (click on screenshot to go to website):

Vanity Metrics vs. Actionable Metrics

Here is how I see the difference between both type of metrics.

Vanity metrics:

“A vanity metric equals a number that might indicate an improvement (e.g. more visitors on your website), but the improvement is disconnected from your organizational online business goal(s).”

Actionable metrics:

“An actionable metric equals a number that might indicate an improvement (e.g. average order value) and the improvement is directly connected to your organizational online business goal(s).”

In the Lean Startup good metrics are described as: actionable, accessible and auditable.

In Need of More than One Metric?

It’s better to select one great metric instead of a few useless, vanity metrics.

Keep in mind that any additional metrics (KPIs) should be in line with your business goals. If they are not, ditch them!

You are one step closer to becoming an analytics ninja.

7. Answer the What, Why and How

Great, by now you have learned about:

How to become an analytics expert
How to effectively deal with your “boss”
How to move from reporting to optimization
Why and how to ask questions
How to select a great set of metrics

I am sure this wealth of knowledge will greatly benefit your career.

You all know Avinash Kaushik I assume. If not, feel ashamed. ;-)

He has introduced the web analytics concepts behind What, Why and How.

The picture above shows how I feel about this.

What: is the lowest level of insights (quantitative insights) // what happened?
Why: is the next step (qualitative insights) // what happened and why?
How: is analytics nirvana (data + psychology + business + consumer understanding) // how can we influence the why based on the what?

In other words:

“It is good to know what happens on our website (our conversion rate is well below 2%)”

—>

“Our customers experiment technical issues when placing an order and don’t feel secure in the process, what about our prices?… great to know this”

—>

“Let’s combine these data insights with all the information we have about our business, market and consumers. How do they react on persuasion elements? We need to formulate effective A/B tests based on a smart hypothesis. This might improve the experience of our website visitors. Now we are getting there!”

Don’t get stuck in the What!

Interesting read: Trilogy of Analytics Tools.

8. Create a Data-Driven Culture

If you really aim to become a kick-ass analytics ninja, there is one more thing. And it’s very important!

“Transform your organization into a data-driven culture”

You will move from analytics to action. It isn’t easy, but the fruits of your labor are awesome.

How to Move Into a Data-Drive Paradise

There are seven steps that I – and my good friend Avinash – recommend to follow:

You must be tired, but… you are on your way to becoming an analytics ninja!

Do you have any tips to move from reporting to optimization that you would like to share?

The post 8 Tips to Evolve From Reporting Squirrel to Analytics Ninja appeared first on Online Metrics.