Without further ado, here are nine things that people often get wrong about personas (based on our experience):
We often get questions from prospective clients about how to use personas. Like, “okay, after I have these personas, then what? How can I use them?“.
I have two standard responses for this:
- Persona analytics is just like any analytics. If you want to understand your customers, there must be some reason for that. What is that reason?
- What are your marketing/business/design goals? What do you want to improve? After knowing these, we can then tell how we think personas could be useful.
The point is that we are not some magicians that can tell you what to do. Instead, we should figure it out together. It’s called co-creation — you, as the client know more about your organization, your problems and goals than us. We need that information to figure out if personas make sense and if so, how.
In this article, the main focus is on:
- highlighting the importance of the use of personas in helping craft good customer journey maps (CJM).
- how the Automatic Persona Generation (APG) system can help make CJM’s in a quick and effective way!
Disclaimer: This article does not cover the topic of CJM in-depth but rather focuses on the marriage between CJM’s and personas! For a detailed breakdown on the what, why and how of CJM’s, refer to this customer journey mapping guide by the folks at UXPressia.
Let’s get to the exciting stuff now!
In this article, I share insights into what are pain points and how can personas — and more specifically the Automatic Persona Generation (APG) system that was built by our team help identify customer pain points.
Expressing customers with pain points as customer personas can contribute to developing better products and services, ultimately leading to a delightful UX for the end-user.
What is a pain point?
If you are a marketer who has grown tired of routinely targeted marketing messages or if you are simply looking for a way to boost your brand awareness and try something new for your marketing strategy, then read on! Influencers may be for you!
If you are an influencer or want to be one, then this article is also for you!
A tech-savvy social media influencer at work Source: Unsplash
In a previous post, we analyzed the demographic Bias in Artificially Generated Facial Pictures that raised a concern that the generated images might not fairly represent all demographic groups.
In this post, we discuss if these artificially generated pictures are good enough for use in personas profiles for real-world systems and applications, which are highly dependent on images for the personas. One of the key aspects of generating personas using a data-driven approach is to be able to represent the persona profile with a matching picture.
The following is a post from the APG Team’s summer 2020 intern, Jaad Mohammed.
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:
- 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 1st persona. For more information about this group. We shall find affinities of this user group.
- Affinity: For this we will expand Age > Secondary Dimension, Within Secondary dimension, type “Affinity”.
Now you can see the categories associated to your 1st 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.
- 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 1st 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.