NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.

Sometimes the best innovations come from reimagining how we help people grow. Timothy Davison, an AI Native Product Manager at Abnormal, set out to solve a common challenge for Customer Success Managers (CSMs): how to get meaningful, consistent coaching when they spend most of their day in back-to-back calls.

CSMs play a crucial role in driving growth, retention, and renewals. But despite their importance, scalable coaching has always been a challenge:

• Managers don’t have time to review every Gong call and leave comments.

• Existing tools provide surface-level stats (like talk time) but lack personalized, actionable insights.

• CSMs spend up to 10 hours a day on calls, leaving little room for reflection or self-improvement.
  

Without structured feedback, opportunities for professional development and stronger customer outcomes get lost.

Tim’s answer was the Customer Success AI Coach, an AI-powered system that delivers targeted coaching at scale.

Here’s how it works:

1. Within 30 minutes of a customer call, the tool pulls the Gong transcript.

2. The transcript is scrubbed, removing all personally identifiable information before processing.

3. An LLM compares the conversation against a matrix of customer success competencies.

4. The system generates a personalized coaching email that includes:
   
   

   • Strengths: Two areas the CSM did well, tied to actual quotes from the call.

   • Growth opportunity: One or more areas to improve, with context and recommendations.

   • Interaction stats: Quantitative data like talk time, number of questions asked, and pauses, benchmarked against team and 30-day averages.
     

Each coaching email is practical, fast, and private, giving CSMs a safe space to learn and improve. Over time, the tool builds persistent skill profiles for each CSM, tracking their progress and tailoring coaching to their individual journey.

Early feedback from CSMs highlights the value:

• Time savings: “After 10 hours of calls, it’s impossible to remember everything. This gives me something concrete to reflect on.”

• Actionable coaching: Rather than broad advice, feedback is tied directly to moments in real calls.

• Scalability: Managers no longer need to watch call recordings to deliver feedback; coaching happens automatically.

• Quantitative insight: By surfacing call stats (like ideal talk time vs. actual), reps can benchmark themselves against peers and adjust behaviors.
  

The result is coaching that’s consistent, scalable, and deeply personalized, helping CSMs improve faster while keeping managers focused on higher-level strategy.

The roadmap is ambitious. Tim and the team are working on:

• Merging quantitative stats with qualitative coaching, so insights like “you talked 10% more than the ideal,” come paired with suggestions on how to adjust in future calls.

• Expanding beyond Gong to include additional data sources.

• Strengthening skill profiles into a robust growth framework that supports career development and customer retention alike.

What stands out about Tim’s project is how quickly he went from idea to impact. Just three weeks into his role, he identified a gap, built a prototype, and demonstrated how AI could scale coaching in a way humans simply can’t.

That’s the kind of innovation that defines Abnormal’s culture: giving employees the freedom to experiment, apply AI in new ways, and transform everyday challenges into opportunities for growth.