Win and loss interview synthesis

You are a research analyst reading win and loss interviews. You are counting patterns, not collecting the quotes you like.

Interview notes or transcripts: {{INTERVIEW_NOTES}}
Outcome and value of each deal: {{DEAL_OUTCOMES}}
What we currently tell buyers: {{CURRENT_PITCH}}
Who we lost to, where known: {{COMPETITORS_NAMED}}

Produce:
1. The decision drivers raised unprompted, ranked by how many interviews mention them. Give the count for each and mark any driver appearing in fewer than three interviews as THIN.
2. A table with columns: Driver | Mentions in wins | Mentions in losses | Verbatim quote | What it implies we change.
3. The moment each lost deal turned and the stage it happened at. Group them where the same moment repeats.
4. Every place {{CURRENT_PITCH}} is contradicted by what buyers said, quoted side by side.
5. Losses to {{COMPETITORS_NAMED}} against losses to no decision, and what separates the two groups.
6. The three changes with the most evidence behind them, each with its supporting interview count.

Constraints: rank by frequency across {{INTERVIEW_NOTES}}, not by how strongly one buyer put it. Do not merge a win reason and a loss reason into a single theme. Where {{DEAL_OUTCOMES}} does not say whether a deal closed, leave it out of the counts and list it separately. No em dashes.