Automatically analyze your team's performance on customer calls with an AI coach. This workflow uses Zapier and ChatGPT to provide personalized feedback directly to employees and log performance data for managers.
with Claire Vo
Start with a clean call transcript obtained via a Gong trigger and a Browse AI scraper. You will also need to have enriched this data using a Google Sheets lookup to get the name and Slack user ID of the employee who was on the call.
Add a new ChatGPT action to your Zap. The prompt for this step should be different from the sentiment analysis. Instruct the AI to act as a performance coach and analyze the transcript specifically from the perspective of the employee's actions.
Act as a sales coach. Analyze the attached call transcript, focusing on the performance of our team member. Create a constructive feedback note for them. Identify 1-2 specific things they did well (like asking great questions) and 1-2 specific things they could have done better (like interrupting the customer). Frame the feedback to help them improve on their next call.Use the output from the AI coach prompt to send a private message in Slack. Configure the Zapier 'Send Direct Message' action to send the feedback directly to the employee's Slack ID you looked up in the first step. This provides immediate and private coaching.
Add a final step to create a record of the feedback. Use a 'Create Spreadsheet Row' action in Google Sheets to log the employee's name, call date, the positive feedback, and the areas for improvement. This creates a valuable dataset for tracking performance trends over time.
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