Segmentation with Google Analytics

Business Problem Statements and Solutions that Segmentation can solve in GA.

Neal A. Akyildirim
5 min readMar 15, 2020

With Segmentation, we are able to view a subset of data based on certain criteria that we define in Google Analytics. We are essentially aggregating the data based on different dimensions that we choose to identify certain clusters within the data. The idea behind segmentation is that, we can see certain key insights that drives the business outcomes such as increase or decrease in revenue.

Below are some business problem statements that we can use Segmentation to solve;

- Who are our core user personas?

- Can we apply target messaging and digital ads?

- Can we analyze the users who purchase product X?

- Can we identify specific trends in our business?

- Are there any reasons why the sales declined in a certain region and age group?

- Can we offer certain discounts or rewards programs to a region?

- What factors are related to whether website visitors make a purchase?

- What traffic sources and channels drive the most engagement?

- How do the new users vs returning users compare?

- How does page X impact revenue per visitor?

- Who are the users that abandon their cart?

- How is our retention? What separates the one time buyer from multi time buyer?

Before we start answering these questions, we should outline some of the important aspects of segmentation and review simple and advanced segments within Google Analytics.

- We can apply maximum of 4 segments to a report at a time.

- Adwords cost data is not compatible with segments.

- There are 3 levels in segmentation.

o User Level: Users that are visiting our site.

o Session Level: Site interactions by single person grouped into sessions.

o Hit Level: Site Interactions during a session.

For example; we want to look at the users that spent more than 1000$ on our site. A user might have spent $100 in first visit, and $900 in second visit with total of $1000 spent. In a session segment this user would not be included. Hit level is even more lower level such as segmenting users that visited a page with video for example.

- User level segments can be only applicable to a maximum date range of 90 days.

Simple Segments: Demographics, Technology, Behavior, Date of First Session, Traffic Sources and Enhanced Ecommerce.

Advanced Segments: Conditions (segment users or sessions according to single or multi session conditions), Sequences (Segment users or sessions according to sequential conditions).

For example, to answer the business problem on how does page X impact revenue per visitor, we can use conditions.

Another business problem on finding out who abandon their cart without fully checking out can be viewed by setting up a sequence segmentation.

Let’s review on how we can answer some of the business problem statements we formulated above.

Purchasers vs non-purchasers

By comparing these two segments, we can analyze the users who purchase our products. We can see how purchasers engage with the site by looking at their page/sessions, new vs returning users, bounce rate and highest engaged pages and make necessary optimizations within the site.

For example, if we see purchaser’s consumer certain page content, we can further increase our marketing efforts directing new users to that page and further optimize that particular page to convert more frequently.

Organic vs Paid vs Referral

By comparing these acquisition channels, we can review the traffic channels that gives us the most engagement and conversation.

One time buyers vs multi buyers

This is an interesting comparison. We are essentially looking at retention and finding out what separates the one time buyer from multi time buyer? Below is how we can set up these segments.

You can do the same with only 1 transaction, which will give us the segmentation for one time buyers.

High Value Customers

With this segmentation, we are comparing our average value customers vs the high value customers. For example; we might consider users that have average order value of $500 and some users with order value of $1500. We can see how the users that spend $1500 engage and convert within our site and apply marketing efforts accordingly.

Keyword Length

With this segmentation, we can set up a certain threshold on the keyword length users performed in order to come to our side and compare them. For example, one user might have used keyword “fashion” to come to our site, and another one used “blue pants”. We can create advanced segmentation, using conditions as below.

In this case “3” in Regular Expression establishes the number of keywords. We can create 4 segments from 1 to 4 keyword lengths and compare the acquisition via organic search.

We can answer complex questions with segmentation. Google Analytics, out of the box, gives us the information on aggregated data. If we want insights to be valuable and actionable to specific business problems, we need to customize the data transformation based on our problem statements. Configuring segmentation based on requirements is one important aspect of data transformation in Google Analytics.

--

--

Neal A. Akyildirim
Neal A. Akyildirim

Written by Neal A. Akyildirim

Data Scientist | Product Lead | E-Commerce | Online Retail

No responses yet