- Step 1 - Installing Coveo for ServiceNow
- Step 2 - Creating a ServiceNow Source
- Step 3 - Replacing the Service Portal Search Page
- Step 4 - Replacing the Service Portal Search Boxes
- Step 5 - Configuring the Case Deflection Panel
- Step 6 - Configuring the Insight Panel
- Step 7 - Configuring a Recommendations Panel
- Step 8 - Configuring Query Filters
- Step 9 - Configuring Machine Learning Models
Configuring Coveo Machine Learning Models
All Coveo™ for ServiceNow components automatically log Coveo Usage Analytics (Coveo UA) events. Once sufficient usage analytics data has been gathered, this data can be leveraged by Coveo Machine Learning (Coveo ML) models to provide highly relevant AI-powered recommendations.
This article explains how a ServiceNow instance administrator or developer who has access to the Coveo Cloud organization linked to their instance can configure their Coveo ML models.
To configure your Coveo ML models
In your Coveo Cloud organization:
- Create a new query pipeline without a condition (see Adding and Managing Query Pipelines - Create a Query Pipeline).
All Coveo ML models must be associated with a query pipeline. While nothing prevents you from associating your Coveo ML models to your default query pipeline, it is a good practice to rather associate them to a distinct query pipeline so that you can measure the impact of Coveo ML through A/B testing before allowing all queries to be processed by your Coveo ML models.
Configure an Automatic Relevance Tuning (ART) model in the query pipeline your created at Step 1 (see Adding and Editing Coveo Machine Learning Automatic Relevance Tuning Models in a Query Pipeline).
An ART model uses Intelligent Term Detection (ITD) to automatically refine queries with additional contextual information (e.g., important keywords from a large textual case description). It also ensures that items deemed highly relevant are included in the query result set and have a fairly high ranking score value, even if those items do not actually match the original query.
A Query Suggestions model provides a list of relevant query completion suggestions as the end-user is typing in a search box. It can also make the search-as-you-type feature more powerful and reliable.
- Optionally, if you want to evaluate how well your Coveo ML models are performing before routing a larger portion of queries to the query pipeline in which they are defined, setup an A/B test between the default empty query pipeline and your new query pipeline, which now contains your Coveo ML models (see Adding and Managing A/B Tests).
- You may want to learn how to generate usage analytics reports to help you identify possible content gaps, discover how your Coveo for ServiceNow components are being used by your customers and support agents, etc. (see Usage Analytics Reports)