Personas with Segment Analytics (Part 2)

The following is a post from the APG Team’s summer 2020 intern, Jaad Mohammed.
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Note: For a complete overview of Google Analytics persona creation methods, see Persona Creation Using Google Analytics: Summary of Methods

To continue with our discussion from Personas with Segment Analytics (Part 1), to perform a persona inspired segmentation using your web analytics tool (here we are using Google Analytics for our platform as an example), these are some details about your customers you would need to gather which will be later used to create personas:

1. Age and Gender: You can see the breakdown of your audience by their ages if you navigate to Audience>Demographics>Overview

We will use the age group with largest demographics to make our 1^st persona. For more information about this group. We shall find affinities of this user group.

2. Affinity: For this we will expand Age >  Secondary Dimension, Within Secondary dimension, type “Affinity”.

Now you can see the categories associated to your 1^st personas age group and gender. Google Analytics uses different types of factors such as browsing history, time on page, and then associates this with a ready-made user profile (i.e. ‘shoppers’, ‘technophiles’, ‘foodies’, ‘music lovers’). Note down a few of the top affinities.

3. In-Market: This helps us to know what kind of products your audience actively compares and researches. For this, within Secondary dimension, type “In-Market Segment”.

Note Down a few of the top products.

Location: If you navigate to Audience>Geo>Location. You can find out the countries your 1^st person likely belongs to.

 Device Used: By clicking Audience>Mobile>Devices, you can see exactly which brand of mobile they’re using and even what service provider or operating system they prefer.

Now that we have collected the information to make our persona. We can put it all together in a neat template to finally create a persona profile. The template you use to represent your persona can be designed by yourself if you have the right resources.

If not, no worries, there are a wide variety of free and paid templates online you can use you to represent your persona data. For example, How to Create a Buyer Persona with the HubSpot Persona Tool walks you through using the free HubSpot persona template and looks something like this:

 APG, automatic persona generation, can also create rich personas from Google Analytics data, based first on behaviors and then adding the demographics. 

Repeat the above steps for different age groups and gender to create a few more personas.Now you can conduct a segmentation analysis for any web data metric based of personas by filtering in details specific to your persona type.

For example, for a metric like bounce rate. Navigate to Audience>Overview, click the drop-down menu and select bounce rate.

Now you see the bounce rate of all users visiting your website. Let’s compare “All users” to a user like our 1^st persona “Samuel”. To do this we need to add a segment Audience>Overview>Add Segment>New Segment

Now input details of your 1^st person which we previously collected like age, gender, affinity etc.

Now you can compare and that in a given day how many of your total bounce rate relate to users like Samuel. Since Samuel is our 1^st persona and represent the user that uses our website the most, we need to understand why our most valuable customer bounced.

Additional filters like first time visitor or re-visitor could help us come to some conclusion for their bounce rates.

You may add additional segments if you wish to compare different types of personas.

There you have it; this is one way you can conduct a persona using segment analytics in Google Analytics using web analytics data.

More about APG?

Jung, S., An, J., Kwak, H., Ahmad, M., Nielsen, L., and Jansen, B. J.  (2017) Persona Generation from Aggregated Social Media Data. ACM Conference Extended Abstracts on Human Factors in Computing Systems 2017 (CHI2017). Denver, Colorado. p. 1748-1755. 6-11 May.