I'm running a quarterly win/loss analysis. Below is data from [number] deals closed in [quarter/time period] — both won and lost. For each deal I've included: prospect company profile, deal size, stakeholders involved, sales cycle length, key objections, competitive situation, and outcome.

**WON DEALS:**

Deal 1: [Company profile: industry, size, stage. Deal value: $X. Key stakeholders: [roles involved]. Sales cycle: X weeks. Main objections: "...". Competitor in play: [yes/no, who]. Outcome: won, signed in week X.]
Deal 2: [Same format]
... (continue for all wins)

**LOST DEALS:**

Deal N: [Same format. Outcome: lost — reason: went with competitor / no decision / budget cut / champion left / other.]
... (continue for all losses)

Run a deep structural analysis:

1. **Stakeholder patterns:** Which roles appeared in won deals vs. lost deals? Is there a stakeholder configuration that predicts success?
2. **Timing patterns:** At what point in the sales cycle do won deals accelerate and lost deals stall? Is there a "danger zone" week where deals go cold?
3. **Objection trajectories:** In won deals, how did objections evolve from first to last? In lost deals, did objections escalate, repeat, or go silent?
4. **Competitive dynamics:** When a competitor was in play, what differentiated the wins from the losses? Was it positioning, pricing, timing, or relationship?
5. **The hidden pattern:** What's ONE insight from this data that we probably haven't noticed — a correlation between two factors that isn't obvious from reviewing deals individually?
6. **Actionable recommendations:** Based on these patterns, give me 3 specific changes to our sales process that would shift the win rate. Not generic advice — changes grounded in THIS data.

Be direct. If the data suggests we're doing something wrong, say so.