Skip to main content

The AI-powered sales coach


The Pega Sales Coach uses self-learning adaptive models. The sales coach gathers sales data and uses the information to calculate performance scores for the sales representatives. The performance scores provide insights into how the sales representatives are performing. The sales coach continuously evaluates sales representatives and suggests action to improve performance.

Information  Insight  Action

Coaching life cycle

The sales coach bot that runs regularly creates the recommended coaching. The sales coach bot posts a message to the manager's pulse feed.

New pulse message for coaching recommendations for manager

Suggested coaching plans are displayed on the manager's home screen. The manager can then decide to leverage or dismiss the coaching plan.

Manager home screen Coaching plans

To create a plan for a sales representative, the manager needs to complete the Plan details and Next follow up date.

Create coaching plan

A message is posted to the sales representative's Pulse feed.

New pulse message for coaching plan for sales representative

The coaching plan is displayed on the sales representative's home screen.

Sales representative home screen coaching plans

The manager and sales representative converse in the Pulse feed.

Sales representative and manager converse over pulse

When the follow-up date arrives, the sales coach bot reviews the sales representative's performance and posts an update to the coaching plan Pulse feed.

If the manager is satisfied with progress of the sales representative, the manager can close the plan. Alternatively, the manager can change the follow-up date to give the sales representative more time to improve.


If you are having problems with your training, please review the Pega Academy Support FAQs.

Did you find this content helpful?

Want to help us improve this content?

We'd prefer it if you saw us at our best.

Pega Academy has detected you are using a browser which may prevent you from experiencing the site as intended. To improve your experience, please update your browser.

Close Deprecation Notice