Value Assessment Note Generator

After discovery calls, AEs and SCs struggle to quickly produce a crisp, executive-ready value assessment that ties the prospect's stated pain directly to measurable business outcomes. Raw call notes are scattered and difficult to synthesize into a structured business case.

Parse discovery notes to extract pain points, business context, company size, and industry. Rank pain points by business impact. For each top pain point, generate a quantified cost of inaction using industry benchmarks. Query G2 MCP for reviews from similar companies referencing the same pain themes. Match G2 review quotes to each pain point as third-party validation. Produce a structured Value Assessment Note with Executive Summary, Pain Point Analysis with cost of inaction, Proposed Solution Outcomes, and Social Proof from peer companies. Flag any open questions to confirm before sharing externally.

Converts raw call notes into a boardroom-ready value story in under 5 minutes. Reps no longer lose momentum between discovery and proposal because the business case writes itself while the call is still fresh.

Ground all cost estimates in prospect-specific data mentioned during the call rather than generic industry benchmarks. For example, if the prospect mentions that 3 people spend 10 hours per week on a manual process, calculate the cost of inaction from that concrete figure. Generic benchmark statements like "companies in this space lose $X per year" lack credibility with executives. Tying every cost estimate back to something the prospect actually said in the call makes the value assessment far more compelling and actionable.

G2 peer review matching significantly amplifies credibility. When you surface a review quote from a peer company in the same industry expressing essentially the same pain point the prospect just described, it resonates far more powerfully than analyst reports or external benchmarks. Executives trust their peers more than third-party data sources.

Relies on industry benchmarks when specific prospect data is unknown, which may not perfectly match individual company situations.