Search Report

This report guides about all the search queries made by the end users on the installed search clients. The report is segregated into four classifications and each section covers four metrics.

Search Classification Metrics
All Searches Query, Users, Sessions, Searches
Successful Searches (Clicks) Query, Users, Sessions, Searches
Searches with no Click Query, Users, Sessions, Searches
Searches with no Result Query, Users, Sessions, Searches

All Searches

All Searches is the first Search Classification. It displays a list of all the queries looked up on a search client. With pagination, users can dig deeper into analytics.

The table on the right has a searchable and three sortable columns:

  1. Query. The keyword or phrased looked up. It is possible to find a query in this column through the search function.
  2. Users. The number of browsers on which the query was searched. The column is sortable.
  3. Session. The number of search sessions in which the query was looked up. The column is sortable.
  4. Searches. The number of times the query was looked up. The column is sortable. Clicking any number in Searches opens a dialog detailing the number of times a facet was applied. The dialog has three columns:
    • Facet Type is a category with several values. "Tag" can be a Facet Type and individual tags, such as "python", "search", and "salesforce", are Facet Values.
    • Count. The number of times a certain Facet Value was applied.

Successful Searches (Clicks)

List of searched queries which returned at least one result and at least one of the results is clicked

The table on the right has a searchable and three sortable columns:

  1. Query. The keyword or phrased looked up. It is possible to find a query in this column through the search function.
  2. Users. The number of browsers on which the query was searched. The column is sortable.
  3. Session. The number of search sessions in which the query was looked up. The column is sortable.
  4. Searches. The number of times the query was looked up. The column is sortable. Clicking any number in Searches opens a dialog detailing the number of times a facet was applied. The dialog has three columns:
    • Facet Type is a category with several values. "Tag" can be a Facet Type and individual tags, such as "python", "search", and "salesforce", are Facet Values.
    • Count. The number of times a certain Facet Value was applied.

Searches with No Click

Search queries where results were shown up on the search client, but users haven’t probably found the results relevant. Hence no result was clicked for these queries.

This data assists content manager prioritize content generation and thus significantly improve the search experience of the users.

The table on the right has a searchable and three sortable columns:

  1. Query. The keyword or phrased looked up. It is possible to find a query in this column through the search function.
  2. Users. The number of browsers on which the query was searched. The column is sortable.
  3. Session. The number of search sessions in which the query was looked up. The column is sortable.
  4. Searches. The number of times the query was looked up. The column is sortable. Clicking any number in Searches opens a dialog detailing the number of times a facet was applied. The dialog has three columns:
    • Facet Type is a category with several values. "Tag" can be a Facet Type and individual tags, such as "python", "search", and "salesforce", are Facet Values.
    • Count. The number of times a certain Facet Value was applied.

Searches with No Result

 Search queries for which no result is produced. A search can be no-result for multiple reasons.

  • Documents with the search keywords do not exist in your data repositories.
  • The user does not have the permission to see documents.
  • Your search client is not connected with the content source where the documents are stored.

It doesn’t end there. For every query where no result was found, a detailed user journey is provided when you click session ID. This helps you to deep dive into the filters that were passed, the advanced criteria that was used, or the keywords that finally end up producing no result on the search page.

The user journey captures: the activity type and details (like text searches, page views, search queries etc.), time of the activity performed, facets and values selected, and what kind of advanced queries are used (like Exact phrase, without words etc.). Using these details, you can explore more about the reasons why such searches are not generating results.

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Last updatedFriday, February 26, 2021

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