AI-Powered Meeting Preparation

Create an AI meeting prep prompt template in Claude or ChatGPT: "Research [Company] for sales call. Find: company overview, recent news, funding, tech stack, competitors, key decision-makers, potential pain points related to [your solution]."

Before 5 upcoming sales calls, spend 10 minutes using AI to generate call briefs; paste company name and context into AI, review output, refine with additional searches if needed.

Set pass threshold: AI research reduces prep time by >=50% (from 20 min to <=10 min per call) and yields >=3 actionable insights per call within 1 week.

Structure AI-generated brief with sections: Company Overview (what they do, size, stage), Recent News (funding, launches, hires), Tech Stack (tools they use, integration opportunities), Pain Points (likely challenges based on industry/size), Key Stakeholders (names, titles, LinkedIn profiles), Suggested Talk Track (opening, discovery questions, value prop).

During calls, reference AI-discovered insights to build rapport: "Saw you just raised Series B—congrats! As you scale, [pain point] becomes critical..." validates research and establishes relevance.

After each call, rate AI brief quality (1-5) on accuracy, relevance, and actionability; note which AI-provided insights were most useful during conversation.

Log meeting prep metrics in a spreadsheet: prep_time, insights_used_in_call, call_outcome, ai_brief_quality_score; track whether AI prep correlates with better call outcomes.

In PostHog, create events for ai_prep_completed and call_conducted with properties for prep time, insights used, and call outcome.

After 1 week, measure: Did AI reduce prep time by >=50%? Did AI-prepped calls yield better outcomes (more discovery, stronger rapport, faster progression)?

If AI prep saves >=50% time and yields >=3 actionable insights per call, document AI prompts and proceed to Baseline; otherwise refine prompts or add additional data sources.