Analyze · ICP-Fit & Lead-Quality Analysis

Score Recent Closed-Won Deals for ICP Fit

Grade your last 90 days of closed-won agency deals against ICP to see whether you're winning the right clients or just any client with a budget.

foundermanagerIntermediate⏱ 2-3 hours per quarter
When to use
Run at the end of each quarter, or before re-pitching your ICP to the team. It distinguishes 'we hit revenue' from 'we hit revenue with ideal clients we can serve well.' Critical input for retention forecasting.
The prompt
You are an analytics-driven head of marketing for a digital marketing agency, doing a brutally honest review of who you've actually been signing.
Agency: [AGENCY_NAME] — [SERVICES]
ICP: [ICP_DEFINITION]
Closed-won deals (last 90 days):
[DEAL_LIST] — each row: client, MRR/contract value, industry, size, revenue, services_sold, sales_cycle_days, source
Score every closed-won deal against the ICP and tell me what % of new revenue is actually from ideal-fit clients vs revenue-of-convenience.

- Score each deal on every ICP criterion — show the matrix.
- Calculate weighted ICP-fit revenue % (sum of A/B contract value / total contract value).
- Flag any C/D-tier wins and call out the risk (likely churn, low margin, scope creep).
- Do not moralize — classify and quantify only.
- Suggest ICP refinement only if 3+ A-tier wins share an attribute not in the current ICP.

1) Scored matrix per deal. 2) % of new revenue by bucket. 3) Risk flags on C/D wins. 4) ICP refinement proposal if pattern exists.
Variables
  • [AGENCY_NAME] — Your agency's name
  • [SERVICES] — Services your agency sells
  • [ICP_DEFINITION] — Current ICP
  • [DEAL_LIST] — Closed-won deals from CRM, last 90 days
Example input
Agency: Northbeam Digital — SEO + paid social for DTC brands
ICP: US DTC ecommerce, $3–25M, 10–80 staff, Shopify
Closed-won (last 90d):
1. GreenLeaf Tea — $8k/mo — DTC tea — 22 staff — $6M — SEO+Paid — 38d cycle — Referral
2. NovaSkin — $12k/mo — DTC skincare — 35 staff — $11M — Paid — 21d — Referral
3. SaaSCo — $4k/mo — B2B SaaS — 60 staff — $8M — SEO — 67d — Newsletter
4. PetPaws — $6k/mo — DTC pet — 12 staff — $2.4M — Paid — 29d — Google Ads
5. Mike's Marina — $3k/mo — local services — 6 staff — $900k — SEO — 55d — Inbound
Example output
Scored Matrix:
| Client | Ind | Size | Rev | Total | Bucket | MRR |
| GreenLeaf | 3 | 3 | 3 | 9 | B | $8k |
| NovaSkin | 3 | 3 | 3 | 9 | B | $12k |
| SaaSCo | 0 | 2 | 3 | 5 | C | $4k |
| PetPaws | 3 | 3 | 1 | 7 | B | $6k |
| Mike's Marina | 0 | 0 | 0 | 0 | D | $3k |

New revenue mix: A/B = $26k (79%), C = $4k (12%), D = $3k (9%).

Risk flags:
- SaaSCo (C): wrong industry, expect channel-fit problems, watch month 3.
- Mike's Marina (D): off-ICP everywhere — high churn risk, low margin, will pull time from A clients.

No ICP refinement needed — 2 B-tier wins both DTC, consistent with current definition.
Pro tips
  • Track the A/B revenue % quarter over quarter — that's your real strategic win rate.
  • Pair this with margin data if you have it — D-tier deals are usually margin-negative.
  • Share the scored matrix with sales leadership before changing commission plans.
Works with
ClaudeChatGPTGemini
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