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How the best do it

How do the best companies replace ICP opinion with a scoring model built on their own data?

They stop arguing about who the ideal customer should be and go and measure who it turned out to be. Pull your last fifty to a hundred closed won and closed lost accounts, define what good actually means for you (fast cycle, high retention, expansion, low support load) and look for the attributes that correlate with it, including the ones nobody expected. Then turn that into a score that lives as a field on every account in the CRM and actually routes work: who gets a rep, who gets a sequence, who gets nothing. The two things that separate a good model from a spreadsheet nobody opens are negative signals that subtract points, and a quarterly re-run, because your ICP is a regression on live data, not a slide from the seed round.

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4 resources, 4 link-checked.

✍️ Essay
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Kellogg's framing, that the ICP begins as a founder hypothesis and should end as a regression on renewal, expansion and win rate, is the whole argument for data over opinion in one sentence. He also makes you define what best means before you model anything.

Your ICP Starts as an Aspiration and Becomes a Regression

From Kellblog by Dave Kellogg 9 min read

  • An ICP should name firmographics, role and problem together, for example VPs of sales at technology companies with 500 million to 2 billion in revenue.
  • Use a bullseye: ring 0 is the ideal customer, outer rings are progressively worse fits, rather than one flat list.
  • By 50 to 100 million ARR your ICP should come from regression on your own data, not founder intuition.
  • Regression often moves the line: the real break may be at 250 employees when you had drawn the segment at 0 to 500.
Open kellblog.com
📄 Article
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The build guide: weighted dimensions, negative signals that subtract points, and score bands that decide routing. It is the operational half that most ICP writing leaves out.

ICP Scoring Rubric Examples for B2B SaaS Teams

From Understory by Naufal Nugroho 15 min read

  • A worked scoring rubric: firmographic 25, technographic 20, intent 15, engagement 15, triggers 10, economic outcome 10, negative signals 5.
  • Decay behavioural signals by 10 to 20 percent for every 30 days of inactivity so old intent does not inflate a score.
  • Point examples: demo request +30, pricing page visit +10, case study download +8, unsubscribe minus 15.
  • Set the MQL cutoff to catch the top 20 percent, for example 70 when the average lead scores 35.
Open understoryagency.com
📄 Article
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A concrete menu of the events that put an account into a buying window, from job changes to fiscal cycles, which is exactly what you need when your fit list is large and your timing sense is zero.

18 buying triggers for identifying B2B buying cycles

From UserGems 10 min read

  • Catalogues 18 buying triggers, including fiscal cycles, champion promotions, job changes, M&A, and funding rounds.
  • New budgets at the start of a quarter or fiscal year are the moment buyers are ready to fund new tools.
Open usergems.com

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The same ground, at another level

How who you sell to reads from a different seat.

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Also in Starting Up

The same ground, over in Understand your customers, our Starting Up track.

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