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 Marketplace if you’d like to take the search experience to the next level. 

The articles contains the following sections:

• Understanding the relevance score in search results
• Understanding boosts in search results
• Which content is included and excluded in search results
• Improving the search experience for end-users

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.

The current field weights are as follows.

Field	Weight for KB articles	Weight for community posts
Title	3	3
Details	N/A	1
Body	1	N/A
Labels	2.8	N/A
Comment	1	1
Section title	1.5	N/A

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.
• Phrase boost - In multiple term queries, exact word order is preferred. For example, when searching for “car park”, results containing “car park” are ranked higher than results containing “park car.”
• Query length - For one and two word queries, the algorithm returns only documents that match all the search words. For longer queries, 40% of the query terms must be present in a document for it to become a search result.
• Overall quantity and quality of relevant results.

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

Understanding boosts in search results

In addition to text analysis we 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.
• Community post votes (Guide Professional and Enterprise) - End-users can rate community posts as “helpful” or “unhelpful,” just as they can for articles. The percentage of positive votes functions as a boost and makes a certain post rank higher than it otherwise would.
• Labels (Guide Professional and Enterprise) - Labels are elements 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 and excluded in search results

When you search Help Center you are searching all knowledge base articles (first 500 KB of each article) and all community posts, if you have community. The default snippet size for a search result is 200 characters.

These items might also be included in the search:

• Restricted content - Only users with permission to access restricted content will see in search results. 
• 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.

These items are not included in the search:

• Attachments - Content within article attachments is not included in Help Center search.
• My Activities - Search in My Activities in Help Center is limited to tickets and, specifically, tickets you have access to. It does not include articles.

Other relevance features

Fuzzy search

When using Instant Search in the help center, end-users can benefit from our fuzzy search implementation. Fuzzy search is a process where an article or post is deemed to be relevant to a search query even when there is not an exact match to the search terms in any of its fields. We use this technique to protect users from spelling mistakes.

Unlike stemming, which removes suffixes and prefixes to get to the root of a search term, fuzzy search uses edit distance to identify search results that contain terms close to the query terms. For example, if you search for “user segmemt” the search engine will also return results containing “user segment”.

The current rule for finding approximate matches is:

• Terms up to maximum two characters must match exactly
• Terms containing three to five characters are allowed one typo
• Terms longer than five characters are allowed two typos

Optimized language support

For content written in certain languages, we apply specific optimizations.

Stemming is language specific. In English, the search engine knows that if you search for the term “films” you also want results that contain the singular form “film.” Similar rules apply to all languages.

Stop words are another language-specific factor. Stop words are the most common words in a language that are usually excluded from the search query to avoid returning too many results. For example, in English, “the” is a stop word.

The Help Center search is aware of the stemming rules and the stop words for a number of languages that together make up up to 99% of all searches performed by end-users.

We are optimizing searches in the following languages:

Arabic, Bulgarian, Burmese, Chinese, Danish, Dutch, English, French, German, Greek, Hindi, Indonesian, Italian, Japanese, Khmer, Korean, Norwegian, Persian, Portuguese, Romanian, Russian, Spanish, Swedish, and Thai. 

All other languages benefit from basic search support.

Improving the experience for end-users

There are a number of ways that you can improve a user's search experience.

Consider changing the color of search results highlighting in your custom theme. Use CSS to change the appearance of your search results keyword highlighting.

On Guide 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.

Providing tips for your end-users to find content more easily

There are a number of operands you can recommend to help end-users locate content in search.

• Find an exact phrase: Use double quotes (") around a phrase to find every article or post that contains all the words in that phrase.
  For example, "article title" retrieves every article or post that contains the words article and title.  The first hits are those where the phrase article title is a standalone phrase.  You'll also get hits where the word title appears before article, or if there is a stemmed version of the word (e.g. articles).  You won't get hits where an article or post contains only the word title, for example.
  Note: If you use single quotes (') around a phrase, the single quotes are ignored.  If you search for 'article title', you'll see hits for every article that contains either the word title or article (exactly as if you had searched without the single quotes).
• Exclude results containing certain words: Use the minus operator (-) in front of the search term to find every article or post that does not include that word or phrase.
  For example, reporting bugs -support returns articles and posts containing reporting and bugs, but excludes those that contain support from the result set.
• Combine operands for advanced search: you can combine the operands above to find a very specific set of results.
  For example, "reporting bugs" -support returns hits for articles and posts that contain both the words reporting and bugs, but do not contain the word support.