AI Lead Scoring, Built From Your Own Deal History
Not every lead deserves the same amount of attention. AI ranks your leads by how likely they are to buy, so your team calls the right ones first instead of working the list in order.
Start Scoring Your LeadsWhat This Solves
Sales teams often treat every lead the same, calling them in the order they arrived rather than the order they're likely to convert. That means real revenue-ready prospects sometimes wait behind leads that were never going anywhere, simply because of timing. Over a busy month, that misallocation of attention adds up to real missed revenue.
Who This Is For
This is for sales teams with enough lead volume that manually judging quality has become a bottleneck, but not enough headcount to hire a dedicated analyst to do it by hand.
How It Works
We connect to your CRM and existing lead data.
We build a scoring model based on what your best customers actually looked like before they bought.
We test the model against your historical deals to check accuracy.
Your team gets a ranked list, updated automatically as new leads come in.
Benefits
Less time wasted on leads that were never going to convert
Faster response to the leads most likely to close
A scoring model that improves as more data comes in
Clear visibility into why a lead is scored the way it is
Works inside the CRM your team already uses
How We Measure Success
We agree on what success looks like before starting, whether that's time saved, faster response, or fewer errors, and check back against that number rather than declaring victory just because something is technically live.
A US software reseller's team was calling leads strictly in the order they arrived, regardless of fit. After scoring went live, reps started their day with the top ten leads by likelihood to close, and close rates on first-week calls improved measurably within the first full quarter of use.
What Good Looks Like After 90 Days
Ninety days into a ai lead scoring, built from your own deal history engagement, the system should be running with little day-to-day attention from your team, refined based on real usage rather than the assumptions we started with. Your team should be able to point to a specific number that changed, fewer manual hours, faster response times, or fewer errors, rather than just a vague sense that things feel better. If it still needs constant hand-holding at that point, something in the setup needs adjusting, and fixing that is on us, not something you should have to work around on your own.
Common Questions
It depends on your historical data, but we test the model against past deals before rolling it out, so you can see its accuracy before trusting it.
It can start with fewer signals and improve as more data comes in. We're upfront if your current data is too thin to start with.
Yes. The scoring is built to be explainable, not a black box, so your team can see which factors drove a given score.
Periodically, as new deal outcomes come in, so the model keeps reflecting what's actually converting rather than staying static.
Yes. Most engagements start with a narrow, well-defined scope and expand once the first phase has proven itself, rather than committing to everything at once.
We test against your actual data and workflows before calling anything finished, specifically so an unusual setup gets caught and addressed during testing, not after launch. **CTA BUTTON** Start Scoring Your Leads
Start Scoring Your Leads
Not every lead deserves the same amount of attention. AI ranks your leads by how likely they are to buy, so your team calls the right ones first instead of working the list in order.