Just Add Data: Make it easier to prioritize your documentation


Analyzing documentation metrics is a great way to prioritize documentation work and resources. For example, identifying well-read or under-viewed documentation topics can guide which ones to work on—whether by revising well-read but less-updated documentation, or by doing more work to get helpful documentation more visible to readers by modifying titles or improving links to the topic. In this talk, I’ll cover what kinds of data to collect, how to gather that data, and how to use it to inform your documentation priorities.

Learn what types of data to measure, such as page views, helpfulness ratings, time spent on page, and why to measure that data. In addition, I’ll discuss the value of measuring or gathering other types of data from sources—other websites within the organization, pull request issue tags, support cases, and sales/field requests—to help identify cross-functional needs that could shift your priorities.

You’ll learn about using data to approximate the number of readers and their engagement with your documentation, and how to partner cross-functionally to gather additional contextual data such as total user base. I’ll provide basic guidelines around analyzing data and set expectations around the time it takes to manually interpret and categorize the data and make it useful for analysis.

I’ll reinforce important points such as how and why to use data or measurements to make a decision, the purpose of measuring different types of data, and what types of conclusions you can draw from different sample sizes (e.g., small sample sizes are still valuable). Using data analysis, you’ll be able to identify topics with low engagement, or find popular topics that beg for a rewrite, and prioritize your documentation improvements accordingly.

  • Conference: Write the Docs PORTLAND
  • Year: 2019

About the speaker

Sarah Moir