Account Scoring that skips dead accounts fast.
Point us at an account list from Apollo, ZoomInfo, or Clay. Every account gets a score from 1 to 10 against your ICP. Anything under 7 is dropped. Anything over 7 moves into research. No SDR spends a morning on the wrong accounts.
What is account scoring? Account scoring ranks your target accounts by how well each fits your ideal customer profile (ICP), usually on a 1-10 scale, so your team works the best-fit accounts first instead of guessing. A strong account scoring model weighs firmographics, technographics, funding, and signals from the company's own website, and filters out existing customers before any work begins.
How it works
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Known customers get filtered before the AI runs.
Your verified customer list lives in your ICP config. A deterministic pre-filter catches exact-name and domain-stem matches and forces them to score 1. No paid LLM call, no wasted token. This exists because, on an early run, the model scored three already-known customers above 7. The deterministic filter makes sure that never reaches your list.
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Pass one, provider data only.
Firmographics, technographics, funding stage, headcount, industry. The model scores on what your data provider (Apollo, ZoomInfo, or Clay) knows. Accounts scoring 1 to 4 are rejected without further work. Fast path, no web traffic.
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Pass two, website crawl for borderline accounts.
If pass one scores 5 or higher and a website exists, we crawl the homepage plus four interior pages (about, product, pricing, customers, integrations). BeautifulSoup strips nav and footer, truncates to 2,000 chars per page. The model re-scores with the full picture. Website content outranks provider data on what the company actually does.
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Multi-segment evaluation, with your rules.
If your ICP has multiple segments, the model evaluates each one separately. Your buying signals, disqualifiers, and tool-stack criteria are pulled straight from your ICP config. No hardcoded assumptions about your market.
Account scoring FAQ
What is account scoring?
Account scoring ranks your target accounts by how well each fits your ideal customer profile (ICP), usually on a 1-10 scale, so your team works the accounts most likely to buy first. It is the first filter in outbound: score every account, then research and message only the ones worth the effort.
What is an account scoring model?
An account scoring model is the logic that turns account data into a fit score. A strong one weighs firmographics (size, industry, geography), technographics, and funding stage, adds signals from the company's own website, and applies your disqualifiers and existing-customer exclusions. The output is a ranked list, not a yes-or-no flag.
How do you score accounts against an ICP?
Run a fast first pass on firmographic and technographic data and reject the clear non-fits. Crawl the website only for borderline accounts to confirm what the company actually does. Filter known customers before any AI runs. Anything above your threshold (we use 7 of 10) moves into research.
Account scoring vs. lead scoring: what is the difference?
Account scoring ranks companies by ICP fit. Lead scoring ranks individual people by engagement and buying intent. Account scoring decides which companies to pursue; lead scoring decides which contacts at those companies are ready to talk. Outbound starts with account scoring.
See it working on your ICP.
Book a demo and we'll run a sample batch against your target market. No obligation, no pretty slides, just scored accounts.