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Case Study

User Research on TechBeacon

Key findings​​
  • Content is the king. People are looking for independent, fresh and well-written content.

  • People like pushed content, e.g., newsletter and social media.

  • People like community features, e.g. upvote and moderated comments.

  • People come to TechBeacon to learn.

  • People like the wide range of topics on TechBeacon.


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
  • Establish personas and create reliable and realistic representations of TechBeacon key audience

  • Instead of data points, we understand user needs, behaviors, patterns, and preferences​.

  • Through personas, we can gain insight into what the priority should be for design, development, and content


Recruiting readers
  • Research and find users based on different engagement level on TechBeacon in Pardot

  • 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

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

  • People respond better to interview invitations written in simple text than in HTML

  • Increase the number of emails sent will increase the number of responses


Interview questions

Organizing interview notes


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