Case Study
User Research on TechBeacon
Key findings
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Content is the king. People are looking for independent, fresh and well-written content.
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People like pushed content, e.g., newsletter and social media.
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People like community features, e.g. upvote and moderated comments.
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People come to TechBeacon to learn.
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People like the wide range of topics on TechBeacon.
Context
TechBeacon was launched in the summer of 2015 and had since then been growing quickly. The team had a lot of quantitative data, e.g., analytics and heatmap, but never did user research. This is the case study of how I created personas and translated them into key insights.
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.
Research goals
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Establish personas and create reliable and realistic representations of TechBeacon key audience
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Instead of data points, we understand user needs, behaviors, patterns, and preferences.
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Through personas, we can gain insight into what the priority should be for design, development, and content
Recruiting readers
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Research and find users based on different engagement level on TechBeacon in Pardot
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Criteria for frequent users
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Subscribed to newsletter
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Prospect score is 180 to 500
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Last activity is less than 60 days
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Criteria for infrequent users
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Subscribed to newsletter
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Prospect score is 50 to 200
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Last activity is greater than 60 days
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Don’t use free email accounts, e.g., yahoo, hotmail, and gmail
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1st recruiting attempt (A/B test subject)
A - Subject: TechBeacon Needs Your Help
B - Subject: Looking for Your Perspective
Learning from the 1st attempt
From this round of A/B test, I learned the email subject "TechBeacon Needs Your Help" had more open rate than "Looking for your perspective". With this learning, I continued to the next round of A/B test.
2nd recruiting attempt (A/B test subject)
A - simple text
Response rate 0.51%
B - Polished HTML
Response rate 0.21%
Learnings from the 2nd attempt
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People respond better to interview invitations written in simple text than in HTML
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Increase the number of emails sent will increase the number of responses
Approach
Interview questions
Organizing interview notes
Personas