Application owners struggle with not having enough visibility in search traffic trends to be able to improve their users’ search experience. They need to understand if their users are satisfied with the app and able to find the content and answers they need, such as specific organization policies or ‘how to’ articles or other knowledge-rich content. Application owners want to understand what the gaps are, where the gaps are happening, and how to fix them.
And, even more critical, applications owners want to know what users were not able to find. This is particularly important to find ways to reduce user friction and frustration in receiving irrelevant results or answers. This data can reveal when to retire unused or least used content to ensure irrelevant content is removed more efficiently, which can negatively impact on credibility and reliability.
With our Advanced AI Search Management Tools, application owners have the insight and visibility they need to improve the search experience for their users.
AI Search Analytics Dashboard
AI Search Analytics Dashboard helps application owners better understand the needs of users, and gain insights on how to improve search experience and knowledge coverage as well as build cases for business-critical actions. It allows application owners to view and monitor search usage and performance, and review search trends, all of which gives them the view they need for better performance and results.
Here’s a closer look:
Overview Section
In the Overview, there are high level widgets that provide the number of Search Users, the Total number of Queries, the Average Response Time, and the Searches over time within a selected Date Range to provide insight into user journey and user engagement – to plan and prioritize improvements.
Search Quality
Along with the Overview, Search Quality metrics are mission-critical. These can be measured in Genius Results of what percentage was triggered versus the percentage clicked, the Average Click Position and the Self-Solved Rate
Genius Results
Search quality can be seen when contrasting percentage of triggered versus percentage clicked. It reveals whether the Genius Results delivered the best possible response and the result the user was looking for, allowing operators to make adjustments based on this data.
Average Click Position
Average Click Position measures how efficiently search can provide the answer that the user is looking for; for example, average click position < 3 means that the search user can find what they are looking for from the top 3 search results on average. The lower the click position, the better the search relevancy.
Self-Solved Rate
Self-Solved Rate is used to quantify how search can help businesses see how efficiently the portal delivers self-service and helps to drive deflection. Gain insight into out how often users need to find something on the portal and how efficient their experience is in finding what they need, to truly self-serve their requests and receive back relevant answers.
Knowledge Gaps
Along with the Overview and Search Quality, the Dashboard also provides guidance on an organization’s potential Knowledge Gaps, through ‘Queries with no results’ and ‘Queries with no clicks’.
Queries with No Results and Queries with No Clicks
‘Queries with no results’ and ‘Queries with no clicks’ reveal when search failed to retrieve the most relevant information. These reveal knowledge gaps or unavailable information and enable businesses to build strategies and actions to address those gaps. ‘Queries with no results’ and ‘Queries with no clicks’ can reveal missing content in an organization’s knowledge library and help operators make the case for content creation. It can also mean that the search delivered poor results, requiring performance and relevance tuning so operators identify the need to build a synonym dictionary and manage new synonyms. With insights gained, operators can resolve unsuccessful search terms and have visibility in areas that were previously inaccessible to deliver improved experiences.
View All
Across from Queries, there is a “View All” option. Drilling down, it provides details of the Queries to view individual queries, allowing for a deeper dive into the analytics of a specific query.
Conclusion
Search has become a business-critical tool that users depend on to be more efficient in their work and organizational environment. Users expect relevant, even exacting results aligning to the criteria they input, and they expect it quickly. In this context, application owners want to deliver an efficient search experience for their users to find what they need; to understand what users are interested in; and discover whether or not they found what they were looking for.
To do this, ultimately, application owners need AI Search Analytics Dashboard to gain visibility in how they can improve the search experience of customers or employees and can take the feedback for performance tuning and relevance tuning. Analytics gives them insights how they can improve the experience in the portal, how to handle customer requests or employee requests – and most importantly, turn the data into actionable strategies and activities backed by strong business cases - all of which are business critical for delighting end users.
