Click-through rates and search query data play a significant role in measuring the performance of a DITA index. These metrics provide insights into how effectively the index assists users in finding information:

Click-Through Rates (CTR): CTR measures the percentage of users who click on index entries after performing a search. High CTR indicates that users find the index entries relevant to their queries.

Search Query Data: Analyzing search queries made by users can reveal which terms and concepts are frequently searched. This data helps in understanding what users are looking for and whether the index provides relevant results.

Iterative Improvement: Use CTR and search query data to continuously improve the index. If certain terms have low CTR or are frequently searched but not well-represented in the index, consider adding or refining those entries.

Example:

In your technical documentation project, you track the CTR and analyze search query data. You notice that the term “troubleshooting” has a high CTR, indicating its relevance to users. However, “user preferences” is frequently searched but has a low CTR. You add more detailed and relevant entries for “user preferences” in the index to improve its performance.

<!– Example of measuring index performance with CTR and search query data –>

<index>
  <title>Technical Documentation Index</title>
  <indexterm>
    <primary>Troubleshooting</primary>
  </indexterm>
  <indexterm>
    <primary>User Preferences</primary>
  </indexterm>
  <indexterm>
    <primary>Installation Guide</primary>
  </indexterm>
</index>

In this example, the performance of the DITA index is improved by analyzing CTR and search query data, ensuring that users can easily find information.