Use case

Your Reps Only Touch the Accounts Most Likely to Buy.

Not every lead deserves the same effort. We score every account for fit and intent, so your team works the top of the list instead of guessing at it.

Book a 30-Minute GTM Audit How we work

The problem

Reps treat every lead the same, chase low-fit accounts, and let high-intent ones go cold while they work a list in no real order. Effort gets spread evenly across leads that were never worth the same.

What we build

A fit model built from your best customers: industry, size, tech stack, and the traits that actually correlate with closing.

An intent layer that scores live signals like funding, hiring, tech changes, and site visits.

A combined score that ranks every account and refreshes as new data and signals arrive.

Scores written back to your CRM and surfaced as a ranked queue in the tools your reps already use.

How it works

Define what good looks like

We study your closed-won accounts to find the fit criteria that predict revenue, not vanity traits.

Build the scoring model

Clay enriches every account and applies the fit and intent logic, so scoring runs on complete data.

Rank and route

Accounts sort into tiers and route to the right rep, with the reasons behind each score attached.

Refine on outcomes

We feed closed and lost deals back into the model, so the score gets sharper over time.

What you can expect

Reps spend their hours on the accounts most likely to convert, and pipeline stops leaking through leads no one prioritized.

Built on

Clay

Trigify

RB2B

Apollo

HubSpot

Salesforce

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Frequently asked questions

Lead scoring ranks every account by two things: fit, meaning how closely it matches the customers you actually close, and intent, meaning whether it is showing buying signals right now. We build both layers in Clay, combine them into one score, and sort your accounts into tiers so reps work the highest-probability list first instead of a list in no particular order.

Fit comes from firmographics and tech stack: industry, headcount, revenue band, the tools they run, and the traits your closed-won accounts share. Intent comes from live signals: funding, hiring in relevant roles, tech-stack changes, and website visits, captured through tools like Trigify and RB2B. Clay enriches every account through waterfall providers first, so the score runs on complete data rather than the gaps a single source leaves.

Native CRM scoring usually runs on the thin data already in the record and a few manual rules, so it degrades as data goes stale. We enrich every account before scoring, blend fit with live intent signals, and refresh the score as new data arrives. The model also learns from your actual closed and lost deals, so it reflects who you really win, not a static point system someone set up once.

A first working model typically lands in weeks. The early work is analyzing your closed-won accounts, defining the fit and intent criteria, and wiring the enrichment and CRM writeback. Once the first scores are live and routing, we tune the weighting against real outcomes over the following weeks. Timelines shift with how clean your CRM data is and how many signals you want to track.

You do. The Clay workbooks, the scoring logic, the enrichment setup, and the CRM fields all live in accounts you control from day one. We document how fit and intent combine into the score so your team can run or change it without us. If we part ways, you keep the whole system and get a full handoff, not a scoring black box that stops updating when the retainer ends.