Search Analytics

Know exactly what your visitors are searching for, what they need help with, and what content they’re not finding.

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Search Analytics

No more guessing what articles to write, your visitors will tell you! PHPKB helps you to optimize your knowledge base by studying the search patterns of your users.

An effective knowledge base results from a constant process of creation and revision. To optimize this process, you must understand the data behind the people using your knowledge base. You need to learn what users are looking for in your knowledge base and where they are failing to find answers. This will help you to improve your knowledge base content and customer support experience.

Knowledge Base Search Statistics

Search statistics record every search term users enter in the search form and let you review these search terms. Then, it goes one step further and tracks whether that search term returned a result and categorise the reports as either successful and unsuccessful. The main benefit of storing searches is to get an idea what keywords are bringing successful search results and which of the search keywords are not bringing any results in your knowledge base.

Search Analytics

Through failed searches, you can find out the search keywords that customers are seeking and that you weren't expecting, or maybe you have misspelled the actual terms used in your article data. These statistics let you recognise the problem areas and can quickly capitalize on this new data by making minor adjustments to your current documents.

Why search statistics are helpful?

Search analytics can help you find missing articles. If a high number of your customers are searching for an article that doesn’t exist, you might think of writing that article. You can look for highly searched keywords that aren't yielding any search results. For example, if end-users are searching for "How to use LDAP feature in PHPKB?" and no content exists in the knowledge base, add that article to your knowledge base.

Search analytics aren’t just about missing articles. Learning about search patterns also helps in ensuring that the article content is up to date. You can improve your knowledge base content by identifying content gaps and updating existing content to be more complete. If most people search for help articles using a specific set of terms, consider incorporating those terms into your actual document to improve its usability. For example, if end-users are searching for "How to harvest email addresses from knowledge base?", and you have an article "Exporting email addresses", consider adding that information to the article. Correcting misspelled terms, or adding similar phrases to the tags and metadata of an article, will bring the correct documents for your visitors.

With the search analytics offered by PHPKB knowledge base software, you can improve end-user search results by updating your knowledge base content in the following ways:

  • Add labels to content: You can add tags to content so that the correct content appears in search results. For example, if you see that end-users are searching for "re-phrase" but you use "rephrase" without a dash in your content, add a label with the similar term to the content.
  • Modify article titles: Rewrite titles to more closely match end-user searches. For example, if your article is titled "Deleting an end-user account" and users are searching for "Removing a member account", consider updating the title.
  • Bifurgate larger articles into smaller: Divide large articles into smaller articles to help customers find what they are looking for. For example, instead of "Managing Articles" consider smaller articles about "Adding an article," and "Deleting an article".
  • Rephrasing content: Add common end-user search terms to the body of appropriate articles so that the article appears higher in search results.
  • Remove misleading content: Remove old content so it does not confuse your customers. Example: If you have updated a feature and have added a new article about that, delete the old article with obsolete information.

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