Don’t let aggregated metrics get in the way of insights –Using Google Analytics segments for meaningful insights.

by Annie Clare May 01, 2020
Image of orange segments

While the top-line aggregated data served up in Google Analytics (GA) is quick and easy to access, and is handy for high level management reporting, it doesn’t give us an understanding of trends, problems and opportunities for our website or marketing strategies.

Fortunately, it doesn’t take much knowledge or effort to dig a little deeper and turn up truly useful insights that suggest changes we can make to improve our future results. One of the best places to start is using segments, to better understand the behaviours and value of different sub-sets of your site users.

In this article I will cover:

  • An example of the improved insights gained by using segmented versus aggregated data
  • Some suggested segments you can use
  • How to create and use Google Analytics segments

Aggregated versus segmented data

Aggregated data in Google Analytics is the rolled-up total of a metric that we find in all of the standard reports. For example in management dashboards we may start off with aggregated data of metrics such as:

  • Total site visits
  • Average bounce rate
  • Total transactions
  • Total goal conversions
  • Total revenue
  • Average order value

This gives us a very high level picture of what the site has delivered overall.

Hopefully it would also be presented with some context, for example, versus target or versus previous period. Otherwise how can the report readers accurately and consistently assess success?

This aggregated data doesn’t however give us information we can use for optimisation, such as why the result was achieved? Or what we can do differently in future to achieve better results? Applying Google Analytics segments can assist in deriving these type of insights.

Applying context

In the example below (using data extracted from GA) we see how by viewing only the aggregated data, without any context, we could miss key information that could help us develop strategies to drive future growth.

The top line aggregated metrics might look like this:

There are some nice big numbers there, but what do we learn from this? Have we achieved what we hoped to? Has our marketing and website development program worked as we wanted? Have we been successful?

At a minimum, we should add some context. Ideally a pre-defined target for each metric, or if that is not available, a comparison to a relevant previous period or industry benchmark.

Adding comparative context of the previous period

This gets a little more interesting. We can see from this that our revenue has increased. Fortunately, a higher average order value and slightly higher visits have countered a decline in transactions and conversion rate. We could start to think that our acquisition strategies have been more successful this year, however our conversion rate once on the site is not performing as well as last year.

If we leave our analysis here and decide to take actions based on this, we may decide to focus our attention on improving our conversion rate. Maybe we’ll look at refining our checkout funnel, user journeys, content or other site design elements to achieve this. Using this data our average order value result looks strong compared to last year, so we may not prioritise improving this.

Insights driven by segments

But wait, let’s look a little deeper at the details behind these metrics, by applying segments. One of my favourite starting segments when looking for insights is device type, as shown below.

When we apply this simple overlay our insights change.

What this new data tells us can be summarised as:

  • 57% of all visits are on mobile devices, and this figure is trending up.
  • That 57% of mobile visits contributed just 28% of all transactions. Desktop devices are still king here, delivering 61% of all transactions.
  • Just 18% of all revenue is on mobile devices, compared to 69% on desktop.
  • The average mobile transaction is worth $94 less than a desktop transaction.

Inferring insights onto future strategies

This data reports the past, and the trends going back over previous years (not shown here) tell us that this pattern is a consistent trend. While this is interesting, it’s irrelevant if we don’t act on it.

What does this mean to our business outcomes if we don’t make changes?

We can expect to see our high value desktop visits declining, and our low value mobile visits increasing. Ultimately, as mobile becomes the dominant traffic source, even meeting last year’s revenue will be at risk. Even worse, revenue could start to decline year on year.

These segmented insights now point to a need to prioritise strategies that improve the mobile average order value and conversion rate. As a secondary strategy, we may also choose not to ignore the value of desktop, but rather look at marketing campaign tactics that target high propensity desktop environments when we are looking for a sale.

This is a big shift in insight and strategy from our initial insight, using aggregated data, that did not prioritise working on the average order value metric and demonstrates the value that can be gained in applying very simple segmentation to drive insights that improve business results.

Fortunately , segments are very flexible and easy to use in Google Analytics.

Top Google Analytics segments to use

Device type is not the only segment that gives useful insights. Depending on your business and objectives there are any number of segments you can create and use in GA to get better insights. Some segments types I frequently use for high level analytics are:

  1. Device type
  2. Marketing channel (or campaign,)
  3. User type – new versus returning (using standard GA user definition)
  4. User type – subscriber or logged in versus guest user (using custom configuration)
  5. Geography
  6. Visit frequency
  7. Content based – e.g. started at Blog content
  8. Shopping stage – e.g. those that didn’t start shopping, versus those who did
  9. Conversion – converters versus non-converters
  10. Demographics

Google Analytics also offers advanced segmentation rules that enable users to create segments based on more complex set of conditions, sequences of actions etc. That is a topic for another day.

How to create & use Google Analytics segments:

Creating and using GA segments is very easy.

Go to almost any Google Analytics report and click on the Add Segment button at the top of the report (note a small number do not offer this option).

This opens an administration page for Segments. You can either choose an existing segment – there are a number of commonly used segments pre-populated in GA or you may have previously created and saved a custom segment – or you can create your own.

If using an existing segment, tick the segment you wish to use and click Apply.

Or, if you want to create a new segment, click on the red New Segment button.

From here:

  • Name your segment
  • Select the segment topic from the left-hand navigation
  • Create your segment rules
  • Once complete, click Save, and the segment will be immediately applied to your report.

You can apply up to four segments in one report.

I recommend that you always validate newly created segments. If the data doesn’t make sense or add up as you would expect, then you may want to review your rules. Peer review is also an excellent way to double check your segment, after all, a small mistake in a segment could result in inaccurate data, incorrect insights and bad decisions.

Below is an example of a segment I have made to report on all Users who have visited my site more than twice.

To remove a segment from your report click on the down arrow icon and select Remove.

Segments you create are only accessible to your google account. If you want another user to access it, then you can share either from the down arrow in the report, or from the segments administration interface (select the segment and click on Actions).

Bonus: Use segments for Audiences

As well as using segments for reporting and insights, a useful bonus is that they can be translated into audiences with remarketing programs using either Google Search, Google Display Network or Optimize. This way you can automatically populate your remarketing audiences, based on a predefined set of behaviours on your website.

Give it a go!

Segments are easy to create and use in Google Analytics, and are an excellent starting point for delving deeper into your data to drive insights that will improve your business outcomes. Jump in and try it out – you can’t break anything!

And if you’ve got any questions or want further assistance with driving insights from your Google Analytics data, please don’t hesitate to get in contact with me.

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Annie Clare Consulting helps brands take the guess-work out of decisions, through data-driven insights, strategies and optimisation.

Get started with free Google Analytics audit and plan, to help step up your data-driven decision making and meet your customers’ needs.

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