When you hear “data segmentation”, your instinct might be to bury your head in the sand or fall asleep. Why? Well, segmentation can seem daunting (or boring) to those unfamiliar with it.
It’s an unfortunate truth because segmentation is perhaps one of the most effective tools at our disposal. The ability to slice and dice your Google Analytics data is the difference between mediocre, surface-level insights and meaningful, useful analysis.
As Avinash Kaushik famously wrote, “All data in aggregate is crap.” [Tweet It!]
Setting Up Your Google Analytics
Before you can segment your data to find useful insights, you’ll need to ensure you’ve setup your Google Analytics properly. There are four core steps to getting started: account setup, property setup, view setup, and goals setup. (You can read a more in-depth guide here.)
Even if you’ve been using Google Analytics for a while now, run through these four steps to ensure everything is working properly.
1. Account Setup
First, let’s get Google Analytics accurately reporting pageviews. To do that, you have two options:
- Google Analytics Tracking Code – This is the traditional method. Copy and paste the tracking code on your site.
- Google Tag Manager Script – Install the Google Tag Manager script and setup the Pageview tag. Click here for detailed instructions on how to do this.
Note that Google Tag Manager is a powerful tool that gives you full control over the Google Analytics setup. With it, you won’t have to rely on a developer or someone more tech-savvy.
Once the code or script has been added / setup, use your “Real-Time” Google Analytics reports to verify that pageviews are being tracked properly.
Chris Mercer of SeriouslySimpleMarketing.com has some additional advice to offer…
2. Property Setup
This step is pretty straightforward as well. There’s only two steps:
- Enable “Demographics and Interest Reports” under “Property Settings”.
- Link other Google products to your Google Analytics account to capture as much useful data as possible. Do this under “All Products”. You can add Google AdWords, Search Console, AdSense, etc.
3. View Setup
Every View in Google Analytics has its own Goals and Filters, which are what make customization possible.
Before you setup Goals and Filters, Chris advises creating a backup View (aka a “Virgin View”)…
“All Website Data” is your default, automatically created View. If you haven’t setup Goals or Filters, you can simply rename it and use it as your backup View.
When you’re ready to setup your “working” View, start with the basics under “View Settings” (i.e. URL, country, time zone and currency). Also…
- Turn on bot filtering. Check the box beside “Exclude all hits from known bots and spiders” under the “Basic Settings” section of “View Settings”.
- If you have an on-site search bar, enable “Site search Tracking” under the “Site Search Settings” section of “View Settings”. This will tell you what your visitors are actively looking for.
- If you’re an eCommerce site, switch “Enable Ecommerce” to “ON” under “Ecommerce Settings”. After you’ve done that, you can return to the same settings and switch “Enable Enhanced Ecommerce Reporting” to “ON” as well.
- Setup any Filters you’re interested in. Remember, these are permanent and not every View will have Filters. You might consider filtering out internal IP addresses, for example.
4. Goals Setup
Next, you’ll want to setup goals to track your success.
Select “Goals” and then “New Goal”. You can then select a type of Goal…
- Destination Goals – When a visitor lands on a specific page, the Goal is triggered. These are perfect for building funnels.
- Duration Goals – When a visitor spends X amount of time on your site, the Goal is triggered. These are perfect for measuring engagement.
- Pages/Screens Per Session Goals – When a visitor lands on X amount of pages in a single session, the Goal is triggered. Again, these are perfect for measuring engagement.
- Event Goals – Whenever a certain condition (or set of conditions) is met, the Goal is triggered. These are the most flexible.
What Is Segmentation?
Now that you have a basic understanding, you can begin having some real fun using segmentation. (If you’re especially interested in segmentation and Goals, you’ll enjoy this article as well.)
Segmentation is essentially dividing a large amount of data (i.e. everything in Google Analytics) into smaller units that are easier to digest and analyze.
Before you can dive into them fully, it’s important to understand the difference between hit-level metrics and session-level metrics. Avinash wrote an excellent post on this very topic, Excellent Analytics Tip #23: Align Hits, Sessions, Metrics, Dimensions!
Here’s a graphical summary…
When segmenting, you can choose between user-, session- and hit-level segmentation. Understanding the difference is absolutely critical if you’re in the eCommerce space. Take a look at how Avinash explains the three…
- User-Level – The person’s entire journey on your site. For example, Mr. Green’s total user revenue is $100 + $62 + $25 = $187.
- Session-Level – Using the example above, if you created a session-level segment for visitors who have spent $70, Mr. Grey’s last session, Mr. Blue’s first session and Mr. Green’s first session would all be displayed.
- Hit-Level – Using the example above, if you created a hit-level segment for visitors who have spent $100, only Mr. Green’s third hit would be displayed.
If you’re just getting started with segmentation, head to the Google Analytics Gallery (“Import from gallery”). There, you’ll find segments created by Google and other users, which you can use on your own site.
For example, here’s a look at the segments that come with the “Occam’s Razor Awesomeness” bundle by Avinash…
If you choose to go ahead and create your own segments, you’ll have the option to choose between: simple segments (i.e. Demographics, Technology, Behavior, Date of First Session, Traffic Sources), conditional segments, and sequence segments.
Simple segments are fairly straightforward. Here’s a look at the creation of a “Demographic” segment…
As you add specifications, they will populate in the “Summary” pane to the right. That way, you can be sure you’re creating the segment you intended to.
You can mix and match between simple segments. For example, you can segment English-speaking women between the ages of 25-34 (“Demographics”) who come from Twitter (“Traffic Sources”).
You can also adjust which Views the segment is available in by clicking “Change” in the top, right-hand corner.
Conditional segments are considered “Advanced”. They allow you to “segment your users and their sessions according to single or multi-session conditions”. Here’s a look at the creation of a “Conditional” segment…
Justin Cutroni, Analytics Evangelist at Google, walks you through an example in his article, Google Analytics Segmentation: Updated for Better Analysis…
You could also use conditional segments to identify potential customers. For example…
- Include: Page contains ProductDetails.
- Include: Event exactly matches AddToCart.
- Exclude: Page exactly matches ThankYou.
In this example, the visitor added one or more products to her cart, but did not end up converting. Knowing this, you can identify points of friction throughout your funnel or even launch a remarketing campaign.
If you use Google Analytics Remarketing, sequence segments will be familiar to you. Essentially, you can “segment your users and/or their sessions according to sequential conditions”. A sequence segment can be between multiple visits or within a single visit.
These are used to segment visitors who visited two consecutive pages in a row.
Take a look…
This is perfect for eCommerce sites. For example, if the first step in your sequence is visiting the cart and the second step is that no transaction took place, your segment will show you visitors who began the checkout process, but did not convert.
If you need to see how sequential actions are connected and how they change your visitors’ behavior, use sequence segments.
4 Ways to Use Segmentation to Increase Conversions
The best way to understand the power of segments and how useful they are is to jump right in and run through some real-world scenarios.
1. Page Load Speed
If you read ConversionXL regularly, you know that page load speed can have a big impact on your conversions. Slow pages simply don’t convert as well. So, you might head to “Page Timings” under “Site Speed” to find out if there are any pages loading slowly that you should analyze.
Try using the “Comparison” visualization (an option to the right of the search function) for more clarity.
Google Analytics might not give you a world-class site speed analysis, but it’ll give you a list of problem pages (and potential solutions) to bring to your developer.
Speed is impacted by device, browser, geographic location and more. So, just identifying the problem pages isn’t enough. You need to understand the context for the slow page load speed. You can do this using segments. For example, apply a filter to find out if the page loading slowly in all countries or just Russia and Turkey.
Tip: Use Motion Charts to find additional context. They’ll tell you how page load speed has changed over time. Are your alterations speeding up the problem pages? You’ll also be able to easily spot anomalies.
2. Time of Day / Day of Week
The time of day and day of the week you push ads, send emails, tweet, etc. do matter. However, you can’t simply go off of an infographic created with someone else’s data. You’ll have to find that data yourself.
- Step 1: Create a custom report and choose “Flat Table”. Dimensions will be “Day of Week Name” and “Hour”.
- Step 2: Add relevant metrics. What might be impacted by time of day / day of week? Sessions, conversion rate, etc. are a good starting point.
- Step 3: While in your custom report, ensure all of the rows are showing (select “Show rows:” in the bottom, right-hand corner). Then, export the data to Excel.
- Step 4: In Excel, create a pivot table and apply conditional formatting to generate a heatmap of your time of day / day of week Google Analytics data.
Following these steps, you’ll be able to answer a lot of relevant questions. Are your visitors more active during business hours? If the answer is no and you’re a B2B SaaS company, that might be a problem.
Yehoshua has some parting advice on this topic…
3. Conversion Funnels
Next, focus on where visitors are dropping out of your funnel. That’s where you’re leaking money and where you should start optimizing. For some companies, conversion funnels are as simple as a submitting a lead gen form. For others, it’s viewing a product, adding it to a cart, proceeding to checkout, etc.
Using horizontal funnels, you can analyze based on channel, A/B test variation, browser type, new vs. returning users, etc. Pretty much anything you can think of.
This is where those conditional (potential customers) and sequence (cart abandoners) segments mentioned above come into play. You can use them to discover points of friction and plug the leak.
Which traffic sources are these people arriving from? What landing pages are they arriving on? Further segmentation will help you answer those questions.
Tip: You can add any of these segments directly to your AdWords Remarketing List to give your display advertising and remarketing campaigns a boost. You’ll save money and increase conversions by targeting more qualified traffic.
Once you identify points of friction, you can visit the pages to spot obvious issues. Beyond that, to discover why visitors leave your funnel, you’ll need:
- Error Message Data – Set up an Event Goal to track error messages.
- Qualitative Research – Conduct customer interviews, watch session replays, create an on-page survey, etc.
4. Converters vs. Non-Converters
There are two types of visitors: visitors who converts and visitors who don’t convert. Segmentation can help explain why conversions happen (and why they don’t).
Google has shared a great example. First, here’s the “Audience Overview” with the segments applied…
Not surprisingly, there are fewer converters than non-converters, but converters contribute more in terms of activity. Also, you can see that over a third of all converters are turning visitors, meaning they don’t make the decision the first time they visit.
Now let’s look at “Age” under “Demographics” with these segments still applied…
So, the older your visitors are, the less likely they are to convert.
The 25-34 demographic accounts for the most sessions and is fairly evenly divided between converters and non-converters. This tells you that, so far, the youngest demographic appears to be especially valuable to you. Of course, further insight requires more segmentation.
What’s interesting is that while the 65+ demographic accounts for fewer conversions, they have a higher conversion rate. Perhaps you just discovered a big opportunity that would have otherwise been missed.
Next, let’s look at “Gender” under “Demographics” with the same segments…
Men account for more sessions than women, but women have a marginally higher conversion rate.
Using these segments, you’ll start to find patterns in your data. In this case, young visitors account for more conversions, but older users have a higher conversion rate and men account for more conversions, but women have a higher conversion rate.
Note that this is just a starting point. Now that you’ve identified the patterns, you’ll need to create age and gender (etc.) segments to see what the rest of your data says. That’s the process here…
- Identify meaningful data patterns (converters vs. non-converters).
- Create corresponding segments and apply them to your reports.
- Analyze your data to determine what changes you need to make to improve conversions.
Segments to Get You Started
There’s no shortage of segment suggestions online today.
Two of our favorite segments at ConversionXL are: the big spender segment and visitors who used the internal site search. You can read about (and download) these two segments and a custom Google Analytics report for social media here.
If that’s not enough for you, here are a couple other segment lists / roundups…
- 16 Secret Google Analytics Advanced Segments Worth Their Weight in Gold
- Top 15 Most Useful Advanced Segments in Google Analytics
Segmentation is all about finding meaningful answers to valuable questions. If you don’t go into it with a question to answer or a problem to solve, you’re likely to end up lost in a sea of data.
Smart optimizers don’t waste time with crappy aggregate data. They use segmentation to find insights they can act on. [Tweet It!]
Make sure Google Analytics is setup properly and accurately tracking / reporting.
Understand the difference between hit-, session- and user-level segments.
Explore the Segmentation Gallery and play around with pre-made segments.
Start by creating your own simple segments based on demographics, technology, behavior, etc.
Graduate to conditional and sequence segments, which are more advanced.
Use segments to find patterns, drill down further by creating more segments based on those patterns, and analyze your segmented data to make meaningful changes that will improve conversions.