Find out which sales objections are actually costing you the most revenue

Run topic clustering across all meeting transcripts in the last 90 days where meeting type is Discovery, Demo, or Proposal. Output: top 30 topic clusters by mention frequency, with cluster label, representative phrases, and meeting-count per cluster. Filter to objection-adjacent clusters (price, timing, competition, feature gaps, security, authority, trust, integration concerns).

For each top objection cluster identified, search meeting transcripts for the 5 most representative verbatim quotes. Pull: quote text, meeting ID, meeting date, rep, account name, account ARR (if customer) or expected deal value (if prospect). The verbatim quotes are what makes the analysis usable — managers and enablement teams need to hear the actual language buyers use.

Compose an insights report ranking objections by frequency × deal value at stake (so a $500K deal mentioning 'too expensive' weighs more than ten $5K deals). Per objection: cluster label, frequency in last 90 days, total deal value mentioned in those meetings, 3 example quotes, win-rate of deals where this objection was raised vs. comparable deals where it wasn't. Tag each as: address-with-content (build a battlecard), address-with-product (real gap, hand to PM), or address-with-process (sales motion fix).

Compose a live objection-tracking dashboard: top 10 objections this month (vs. last month — trend signal), top 5 fastest-growing objections (early warning for new competitor or market shift), objection-by-rep heatmap (which reps face which objections most — signals coaching needs), and recent verbatim quotes feed (refreshes weekly). This is the enablement team's daily-driver view.