The following is a post from the APG Team’s summer 2020 intern, Jaad Mohammed.
Behavioral personas take the basic personas one step further.
Personas are imaginary people representing the user, audience, or customers of a market segment based on real market research data. With personas, you get answers to questions such as: “Who is the customer?” “What do they want?” and “How can you give them what they want?”
Behavioral personas tell you what you know about an already well-defined target audience. Behavioral personas can give you insights into why the system is or isn’t working for this particular group of people.
Behavioral personas are cost-effective: as you already have the user data from user research.
For example, a usual persona would be “Mark, Male age 35-45 years old, Father of two, married, college graduate, own a house, is interested in: sports, cars, racing, … etc.”
Whereas a behavioral persona would look something like “Mark, a game tester who spends 60% of his time at the office on our – ‘your systems name here’ – to debug the issues regarding game performance, he mostly uses “features a, b and c” on the system … Mark has the influence to suggest new software’s for his company.”
How do you make Behavioral Personas?
Use your data! Behavioral personas can be formed almost entirely by analyzing data that’s probably already on your server (e.g., site search data, weblogs) and/or the information provided by Google Analytics. This data can be used to identify patterns of customer behaviors.
Enrich your data! Also, if possible, interview some of your current users. It helps to speak to some of your existing customers to understand what motivates them to uses your system and why they prefer your system compared to others. With interviews, you can gain some invaluable insights your weblog or Google Analytics might not give you. After all, behavioral or not, personas are human!
Retention is critical – find what brings your current users back, and promoting other users to engage in this behavior will do wonders in converting a non-sticky user to sticky-user.
Behavioral personas work best when you’re working to figure out factors such as user retention of a well-defined user segment for an existing system. This insight can tell you how well the current system is working for your users and what improvements can be made to make the user experience better.
Spenser Skates suggests a way of analyzing user retention by creating pivot tables with Google Analytics.
Salminen, J., Jung, S.G., Chowdhury, S. Şengün, S., and Jansen, B. J.
(2020) Personas and Analytics: A Comparative User Study of Efficiency and Effectiveness for a User Identification Task. ACM CHI Conference on Human Factors in Computing Systems (CHI’20), Honolulu, HI, USA. 25–30 April, 1-13.