Writing Docs Worth Reading
summary
No single “magic number” defines docs success; Datadog combines Google Analytics, Hotjar, Postman, Zendesk, Algolia and Datadog logs to measure outcomes. A page showing 30 minutes average time on page reveals a broken step; heatmaps show heavy clicks on the Run with Postman button and library links; Postman and Datadog automated API tests catch regressions; support tags plus Zendesk drive a goal to decrease ticket response time; search gaps surface via AnswerThePublic.
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chapters (17)
- 0:00Introduction to docs importance
- 1:32Using data to improve docs
- 2:55Defining documentation goals
- 4:18Content categories for docs
- 5:40Tools for measuring docs success
- 7:03Google Analytics time on page
- 8:47Tracking user clicks from docs
- 10:11Measuring end-to-end success
- 10:52Page views and user behavior
- 12:17Heat maps and user interaction
- 13:40Hotjar user feedback questions
- 15:46Testing API documentation
- 16:49API usage and library focus
- 17:10Support team collaboration
- 18:56Tracking signups from docs
- 20:00Optimizing search for docs
- 21:43Q&A session
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