Archetypes vary from product to product. For example: A photo sharing product will have different archetypes than an analytics application. So lets dive in with the example of an analytics application to get a good sense of the process and elements involved (Note: Just like a SCRUM process, or any process, this can always be improved and tailored to your organization).
Lets define the Analytics Application
A high level purpose of using an analytics application (such as Google Analytics) is to see how well you are performing on your digital property, where you can improve, and to gather insights and trends on your current campaigns.
What’s the process for defining an Archetype?
Because many archetypes overlap with behavioral models and personalities — the first step is to create explicit archetypes for your UX process. Think of archetypes as prototypes of how you expect a user to behave vs. actual data you collect (data that give insights into behavioral usage). Behavior usage may include scroll depth on a long list, or heavy usage of filters within your product. The next step is to bucket users (to the best of your ability) based on both behavior and customer feedback. In the example for an analytics application a few behavioral archetypes could be:
- Reporting/Task Centric — These users try to quickly gather information and report on their findings.
- Activity Centric — An emphasis on filters/sorting which shifts focus to activities a user tends to perform.
- Data Centric — The primary focus is typically centered around a specific data set that a user would have a relationship with. Think Social Media Editors with Twitter/Facebook traffic data.
What elements go into an Archetype?
- What’s the primary focus & behavior of someone using your product?
- Is there an end-goal for a particular screen/feature? (Drive discovery, encourage interaction, etc.)
- When in the application view how will the feature be used? (Drilldown to micro data, Rewind and fast forward videos, etc.)
- In what environment do these actions take place? (In office, during meetings, time of day, etc.)
- Is there any psychological connection? (Focus around communication, updates, alerts, etc.)
Difference between a Persona vs. an Archetype
I’ll give an example of a persona first: Let’s name him Mike.
- Mike’s work environment is flexible. He works 50% of the time from home and 50% of the time from the office.
- He’s an upper management employee who needs macro level reporting on how well his digital property is performing; in order to report to a C-Level employee.
- Mike logs into the platform twice a week to learn how well his company is performing — The second time is to make projections for his weekly meeting.
- He travels 25% of the time and his platform usage is ~ 75% desktop and 25% mobile.
- Mike cares about impressions because the company relies on display advertising for revenue.
A good archetype would be a ‘Reporting/Task Centric’ archetype.
- The reporting view enables a specific task. This is the centerpiece of this archetype: The primary task is to gather data and a secondary trigger to report findings to a C-Level employee.
- A good UX pattern to employ would be a nested doll pattern. Where these users could see the high level reporting they need on the first screen. If other users need more detailed information they can drill down to specific funneling and micro KPIs.
- A reporting centric archetype uses both real-time data and historical data for offline analysis.
- The information a reporting centric archetype consumes is on the desktop and mobile environment.
- Users in this archetype need aggregated data and findings. There’s less of a case for having these user manipulate data.
- This archetype tends to visit the platform parent pages and not report specific child pages.
One can argue that both personas and archetypes are useful for the UX process; and they both are. I personally like using archetypes because it gives a better indication to behavioral patterns while personas give more insight into the characteristics of the person. Behavioral patterns show how people are using your application, while personas give insights into the people who are using your application.
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