Knowledge discovery is an essential component of a knowledge base platform. To facilitate finding right content in the knowledge base, a powerful search engine is required. More importantly the search engine should be quick to index any newly published articles and make them available for search.
Importance of search
Search engine provides a better customer experience to knowledge base readers. Instead of readers trying to find an article using pre-defined category they can use search functionality to get right content. Readers can search using keywords and search engine brings relevant article in no time!
In addition to better experience, search functionality enhances engagement with the knowledge base content. Readers might not be aware of complex taxonomies that an organisation deploys to organise content and readers do not have time for “look and find”. Even if a reader finds a content by navigating complex structure, they might bounce quickly as soon as the content is not relevant! This solely defeats a purpose of having a self-service knowledge base. If a reader can find a relevant content quickly, engagement with the knowledge base increases. This leads to decrease in customer support tickets and improves customer retention.
At Document360, we understood the importance of search in knowledge discovery and content engagement. We deploy a powerful artificial intelligence based search engine to index all knowledge base articles in real-time. We use a third-party provider that powers our search.
This search engine can be tailored to a particular project and search keywords can be highlighted in the search result pages. In addition to this nifty elements, search highlights top five search results by defaults for quick navigation.
The search highlight can be customised by navigating to Settings -> Knowledge Base Site -> Article settings & SEO -> Search highlight
At Document360, the search results also provide a breadcrumb of the content such that it helps readers to understand how knowledge base content is organised.
How to optimize knowledge base search
There are few best practices that you can follow to optimize the knowledge base search feature for indexing content and bringing relevant knowledge base articles.
- The title of the article plays on important role in creating search index. Ensuring relevant title for the article helps search engine fetch right article when the reader types a keyword in the search bar.
- Add relevant tags to the article as search engine uses tags to prioritise relevant article.
- Write relevant content pertaining to the title and tags. Ensuring that content has many occurrences of search terms emphasise that this content is relevant to the search keyword.
- Also ensuring the article slug is relevant to the article content boosts the search engine performance.
In addition to powerful search engine, we also provide rich search analytics. Search analytics helps the knowledge base owners to understand volume of search queries, number of users and search engine performance. Document360 also provides a functionality to compare these metrics over time.
Top search keywords are listed in “Popular Searches” section of search analytics page. This provides a valuable information on what is trending among your documentation readers and what relevant articles are most accessed. These articles need to be of high quality to enable self-service.
We also show “No search result” keyword to help content writers
- Write a new article if there is no article available for that keyword
- Tag a current knowledge base articles to help with knowledge discovery such that those articles appear on search results
Analysing longitudinal trends of these keywords and its frequency provide insights to tailor right content to your readers and add appropriate article tags.
Knowledge base search feature helps with knowledge discovery, and it is fundamental component of knowledge base platforms. Search engine helps your customers to find content quickly and increases engagement with your documentation.