TechBeacon was launched in the summer of 2015 and has since then been growing quickly. The team had a lot of quantitative data, e.g., analytics and heatmap, but never did a user research. This is the case study of how I created personas and translated them into key insights.
To comply with my non-disclosure agreement, I have omitted and obfuscated confidential information in this case study. The information in this case study is my own and does not necessarily reflect the views of HPE.
What is TechBeacon?
TechBeacon is a content platform that publishes articles written by industry practitioners.
TechBeacon is a daily destination for IT professionals looking to share their knowledge and stay up-to-date on everything related to software development.
- Establish personas and create reliable and realistic representations of TechBeacon key audience
- Instead of data points, we understand needs, behaviors, patterns and preferences
- Through personas, we can gain insight into what the priority should be for design, development, and content
As the only designer at TechBeacon at the time, I created the user research plan for TechBeacon. My responsibilities included:
Researched on users
I identified users, recruited interview participants, conducted interviews, analyzed findings and created personas. I also drew key insights from the personas in order for the stakeholders to easily understand.
One of the goals of creating personas is to build empathy and form consensus. I socialized personas with the internal teams as well as the external stakeholders.
- Identify users
- Recruit interview participants
- Conduct interview
- Analyze findings
- Create personas
There are three types of users on TechBeacon website:
- Frequent users
- Infrequent users
- Managing editors
The team decided to focus on readers for this project.
Recruit Interview Participants
Instead of sourcing the participants from user research websites, e.g., UserTesting.com and Optimal Workshop, I decided to do the harder route by recruiting participants from our mailing list.
There were many advantages in recruiting by from our mailing list:
- to ensure the participants are the actual users on TechBeacon
- I would have the full control of interviews
- it creates a healthy user pool for future research
- it saves money
I then found users in Pardot by Salesforce, our mailing list tool. I segmented users based on their engagement levels:
- Criteria for frequent users:
- Subscribed to newsletter
- Prospect score is 180 to 500
- Last activity is less than 60 days
- Criteria for infrequent users:
- Subscribed to newsletter
- Prospect score is 50 to 200
- Last activity is greater than 60 days
- Don’t use free email accounts, e.g., yahoo, hotmail, and gmail