How this CEO turned 25,000 hours of sales calls into a self-learning go-to-market engine | Matt Britton (Suzy)

What It Covers

Matt Britton, CEO of Suzy, demonstrates how he transformed 25,000 hours of recorded sales calls into an automated go-to-market system using Zapier, AI, and no-code tools to extract maximum value from customer conversations.

Key Questions Answered

• •Call transcript automation architecture: Use BrowseAI to scrape Gong call IDs and transcripts when APIs lack direct integration, then trigger Zapier workflows that process each recording through multiple LLM analysis steps, data enrichment lookups, and output generation automatically after every customer call completes.
• •Sentiment scoring for churn prediction: Implement AI-generated sentiment scores from 1-10 on every customer call transcript, then aggregate scores over time to predict churn risk. Scores below 7 trigger automatic alerts to a dedicated Slack channel, enabling proactive intervention before customers leave.
• •Customer language for keyword targeting: Extract exact phrases and terminology customers use during calls to describe their problems and interests, then automatically add these keywords to Google Ads campaigns. This ensures paid search targets language that resonates with prospects similar to successful existing customers.
• •Redacted content generation from calls: Create blog posts automatically from customer call transcripts by using AI to remove all identifying information about specific companies and strategies, then publish SEO-optimized content 21 days later. This generates thousands of use-case articles for organic and paid traffic without manual writing.