Score a rep’s account list data quality before a QBR

<context>
I want to score the data quality of a rep's entire account list before a QBR or 1:1 — so I walk into the conversation with a clear picture of where their CRM data is clean, where it's at risk, and what it means for their pipeline.

Rep and territory:
- Rep name: [REP NAME]
- Account list with primary contacts: [PASTE COMPANY, CONTACT NAME, TITLE, LAST TOUCH DATE — one per line]
- Active pipeline: [PASTE DEAL NAME, COMPANY, STAGE, ACV — one per line]
</context>

<task>
1. For each account's primary contact, use Lusha to validate:
   - Still at the company in the same role?
   - Title current?
   - Reachable (verified email or phone)?

2. Score each account's contact health:
   - GREEN: contact confirmed, verified, reachable
   - AMBER: contact still there but title changed, or last touch 30+ days ago
   - RED: contact departed, unverified, or unreachable

3. Map contact health to pipeline:
   - For any RED or AMBER account with an active deal: flag as pipeline risk
   - Return: deal name, stage, ACV, contact status, risk reason

4. Return a rep data quality scorecard:
   - Overall score: % GREEN / AMBER / RED across all accounts
   - Pipeline at risk: RED and AMBER deals sorted by ACV
   - Total ACV exposure from RED accounts
   - Accounts with longest gap since last verified touch
   - 3 coaching observations based on the data patterns

5. A one-paragraph QBR talking point: what does this data tell us about how the rep is managing their territory?
</task>

<constraints>
- The QBR talking point must be based on actual data patterns — not generic commentary.
- 3 coaching observations must be specific: "6 of your top 10 accounts by ACV have a contact last touched 45+ days ago" not "some accounts need attention."
- Total ACV at risk is the headline number — surface it first.
</constraints>

The situation: A VP of Sales runs this before a QBR with rep S.K. Territory: 9 accounts, $419K active pipeline. Contact data last updated across the board 6–10 months ago.

Output from live Lusha run, May 25, 2026:

Data quality score: 44% GREEN — 4 GREEN, 3 AMBER, 2 RED

Total ACV at risk: $302K (72% of active pipeline tied to AMBER or RED contacts)

Pipeline at risk sorted by ACV:

1. Zendesk renewal — $180K — Proposal — 2 AMBER contacts, both promoted to SVP
2. Highspot new biz — $72K — Negotiation — 1 AMBER contact, title changed
3. Salesloft reactivation — $50K — Discovery — RED, contact departed, no replacement found

3 coaching observations:

1. 72% of active pipeline has a contact data problem — this isn’t random, it’s a territory-wide pattern suggesting contacts aren’t being updated after interactions.
2. The $180K Zendesk renewal is at Proposal stage with both primary contacts showing incorrect titles. S.K. is about to send a proposal addressing SVPs as VPs.
3. The Salesloft deal has no verified contact — $50K in Discovery with no one to call. Either the deal should be removed from pipeline or a replacement contact found before Q3 starts.

QBR talking point: “72% of your active pipeline has a data quality issue — not a small number of edge cases but the majority. The Zendesk renewal is the most urgent: you’re at Proposal with two contacts whose titles are wrong in the CRM. The Salesloft deal has no verified contact at all. Before we talk about close plans, let’s agree on a data refresh as a pre-condition for any of these deals moving forward.”

Contacts verified live via Lusha connector, May 25, 2026. Names masked to initials.