Score these accounts and return the top 10 ranked, with reasoning per pick.
Inputs:
- Account list (with attributes): {{paste CSV or list}}
- Scoring criteria + weights: {{paste — e.g. industry fit 30%, employee count 20%, recent funding 15%, tech-stack match 20%, intent signals 15%}}
- ICP definition (if you have one): {{paste}}
Output:
## Ranked top 10
| Rank | Account | Score | Why it scored high |
|---|---|---|---|
The "Why" column is 1–2 sentences referencing the specific data, not generic.
## Outliers worth a look
Accounts that didn't make top 10 but have one extreme signal — a recent funding round, a hire in a key role, a tech-stack change. List 3–5.
## What I'd disqualify and why
Accounts at the bottom of the list — for each, the specific reason they're not a fit so the SDR doesn't waste a cycle.
## Scoring sanity check
- Are top accounts clustered in one segment? If so, is that real signal or scoring-method bias?
- Is anyone scoring high on adoption-killer criteria (e.g. wrong region, wrong stage) that the weights are masking?
Hard rule: don't pad the top 10 if only 6 accounts genuinely fit. Honest "6 strong fits + 4 stretches" > "10 mediocre fits."account-scoringpipelineICP