- Capabilities for Salesforce Communities
- Coveo for Sitecore
- Optimal Model Data Period
- Model Training Frequency Change
- Model Restrainment
- Tests Before Activation
- Supported Languages
- Secured Salesforce Communities
- Relevance Improvement Time
- Impact Measurement
- ART and Service Cloud
- Automatic Relevance Tuning Function
- First Returned Results and False Promotion
- Coveo UA Enabled Simultuneously
- Coveo On-Premises
How Do You Measure the Coveo ML Features Impact?
You can use the following 2 traditional marketing metrics to evaluate how successfully your community search connects users with the information they need to solve their specific issue:
Click-Through Rate (CTR) – The percentage of users clicking on any link on the search results page. Higher values are better, meaning that users are more often opening search result items following their queries.
Average Click Rank (ACR) – Similar in concept to page rank, this metric measures the average position of opened items in a given set of search results. Lower values are better, as a value of
1represents the first result in a list.
Coveo ML optimizes search results and query suggestions, and will therefore improve CTR and ACR metrics and contribute to increase self-service. You can test the addition of Coveo ML features like any other query pipeline change (see Testing Query Pipeline Changes).