Search Term Analysis & Clustering

The Search Log gets you under the hood of the Search algorithm so you can understand the results returned for recent searches. View the query, searcher's location, timestamp, total clicks and more. To follow the searcher's experience, click into individual searches to see the results and why they were shown based on your custom search configuration, the Search machine learning algorithms and your Knowledge Graph so you can debug searches and optimise your experience.

Yext's built-in Search Terms screen normalises query strings (for things like capitalisation, leading and trailing whitespace, and punctuation) into a list of truly unique search terms sorted by popularity to see what users are really searching for. You can score the relevance of entities returned for each search term, assign statuses and labels, and leave notes to quickly provide feedback on search results.

Search Term Clusters uses AI to automatically detect patterns in user intents so you can get a high-level view of what users are searching for. This machine learning tool identifies different search terms that share a common intent and groups them into one cluster. For example, a restaurant's relatively few searches for terms like "check my balance" and "gift card balance" could individually be overlooked, but when grouped, it's clear that users want to know more about gift card balances.

To help you prioritise optimisations to your experience, Search Term Clusters are categorised by size — Small Cluster vs. Large Cluster — and performance — Performing Well vs. Needs Attention. If searches on a topic have low engagement, its cluster would be highlighted as "Needs Attention" so you can add content that addresses the trending topic. Starting with Large Clusters helps you focus your efforts on the answers your users want most.