About Help Center end-user search

Help Center provides simple full-text search of your content. Help Center search indexes your knowledge base articles and community posts.

When a user enters a search query in Help Center, the search algorithms get to work, looking for indicators of the most relevant results and ranking them. The relevant snippet from the content of your knowledge base article or community post is created.

The search results are then displayed to the end user with snippet and keyword highlighting.

Tip: Check out Algolia in the Apps Marketplace if you’d like to take the search experience to the next level. Algolia offers as-you-type results, to quickly narrow the search, and the ability to enable similar results if there are no exact matches.

Understanding the relevance score in search results

The ranked search results are based on relevance scores, and are displayed to the user in descending order of their scores.

Relevance scores are indicated by a weighted average per field score. A field is a part of a record, representing an item of data. Some examples are:

• Matches in an article or post title field score higher than matches in other fields.

• Matches in article labels score higher than matches in the body field.

Relevance scores are also impacted by a text analysis process that considers the following factors:

• Exact match - Results that exactly match a word in the search string. This scores higher than a stemmed match.

• Stemmed match - Results where a word matches after stemming. For example, the plural form of a word generally matches the singular form.

• Term frequency - Number of matches returned in a single field. Higher term frequency increases the score.

• Field length - Matches in shorter fields score higher than results in longer fields. For example, if you have a single word search, that matches a one-word title, that will score higher than a hit in a long article title with many words.

• Proximity boost - The score is boosted when all the search terms are close together in the same field. For example if all the search terms are included in an article title this puts them in close proximity and gives the result higher relevance.

• Query length - For one and two word queries, the algorithm returns only documents that match all the search words, but for longer queries a percentage of the search words can be missing. For a 3 or 4 word query, one word can be missing. And so on.

• Overall quantity and quality of relevant results.

Note: Suggested articles are what users see when they type the subject of their request into the “submit a request” form on Help Center. Suggested posts are what users see when they create the title of a community post in Community v2. The search relevance used for “suggested articles and posts” is exactly the same as the rest of the Help Center.

Understanding boosts in search results

In addition to text analysis we also give extra weight to certain features of articles and posts. These include:

• Article votes - End-users can rate articles as “helpful” or “unhelpful” so that over time an article may develop a score like “10 of 50 users found this article helpful.” We give articles with a higher percentage of positive votes a boost so that they show up a higher in results than they otherwise would. The more overall votes an article has weighs in too; for example, an article with a rating of 10 out of 50 gets more weight than one with 10 out of 100.

• Labels (Guide Professional) - Labels are elements which you can use to influence the relevance score of your articles in search results. Consider using labels carefully to balance your Knowledge base search results.

Which content is included in search results

When you search Help Center you are searching all knowledge base articles, and also community posts if you have your community enabled.

Other items may or may not be included in the search, as follows:

• Restricted content - Only users with permission to access restricted content will see in search results. Learn more about restricting Community and Knowledge base content.

• New content - When you add or update content it usually takes only a few minutes before the content is indexed and can be searched.

• Comments - Article and post comments are included in Help Center search results. Comments will show up in the search results as long as the search result snippet is matched in the comment. If there are multiple comment matches within one community post, the algorithm will pick the most relevant comment snippet

• Attachments - Content within article attachments are not included in Help Center search.

Note: When you search in My Activities in Help Center, it is limited to tickets, and, specifically, tickets you have access to. It does not include articles.

Improving the search experience for end-users

If you are on Professional or Enterprise, you can use the search analytics dashboard to review Help Center search terms from the last 30 days. For each search term you can see the number of searches for that term, number and type of search results returned (if any), click-through, and the next action taken.

Search analytics gives you insight into what your customers are looking for and where they are failing to find answers. To make end-users more successful you can analyze search data, then take actions to improve search results and your knowledge base content.

To open the Search Analytics dashboard to review end-user search terms

• Click the Reporting icon () in the sidebar, then click the Search tab.
  Learn more about the options in the dashboard.

To make end-users more successful searching in Help Center

• Advise end-users that they can search for an exact phrase in Help Center by using quotes. For example, “find this for me.”

To change the color of search results highlighting in your custom theme

• Add some CSS styling.