When leads land from several places at once, most teams work them in the order they arrived. That's the one ordering guaranteed to be wrong. Arrival time has nothing to do with who's ready to buy.
Scoring ranks them against what's actually closed for you before. Source, service requested, budget signals, timing language, how they described the problem. You get an ordered list, so the first call of the day is the one most likely to turn into work.
The model's built on your history, not an industry average. A scoring system trained on somebody else's business is a horoscope with decimals.
It also gets retrained. What predicted a close last year drifts as your offer and your market move, so the model is something we revisit rather than something we hand over and forget.
02
Scoring works on existing clients too
That same approach on your current book tells you where the risk and the upside are. Which accounts are healthy, which are drifting, which are quietly ready for more work but have never been asked.
For most businesses that second list is worth more than the lead list, and almost nobody keeps it.
Same scoring, different question. Instead of who's likely to buy, it's who's likely to leave and who's ready to be asked for more. Both are cheaper to act on than a cold lead.
03
A name and a number isn't a lead
Most inbound that arrives is thin. A name, an email, maybe a phone number and one line of description. Your team then burns the first ten minutes of every call working out who they're even talking to.
Enrichment fills that in before the call. B2B: company size, industry, role, tenure, tools in use, recent signals worth mentioning. B2C: property and household context relevant to what you sell, from legitimate public and licensed sources.
It lands in the CRM record, not a separate report. If your team has to open a second tab to see it, they won't, and you've bought data that nobody reads.
04
Context is what makes the call land
The point isn't a fuller database. It's that whoever picks up the phone knows enough to have a real conversation instead of an interrogation.
Knowing the caller runs a nine-person operation, has been in the role three years, and asked about the same service twice last quarter changes the opening line. That's the difference between a call that converts and one that goes back in the queue.
We're careful about sourcing. Enrichment data comes from legitimate providers and public records, and we'll tell you where every field came from.
05
How the model actually gets built
We start with your closed deals, not a template. Every win and every loss you can give us, with whatever context came attached.
From there we look for what the winners had in common that the losers didn't. Sometimes it's obvious, like service type or property status. Often it isn't. On one engagement the strongest single signal was how the lead described their own timeline in the form.
The output is a score and the reason behind it. Your team sees why a lead ranked where it did, which matters because a black box gets ignored the first time it's wrong.
06
Where the data comes from
Enrichment is only useful if it holds up. We use legitimate providers and public records, and every field traces back to where it came from.
We'll tell you what's licensed, what's public, and what we can't get. If a data point would put you on the wrong side of how your industry is regulated, we leave it out and say why. Legal and real estate both have rules here, and getting it wrong costs more than the enrichment is worth.
07
What the first few weeks look like
Week one is your history. We pull the closed-won and closed-lost records and look for the pattern. You get that read back before anything gets built.
Then we score the current list and hand it to the team in the order they should work it. That's the test. If the top of the list doesn't convert better than the middle, the model's wrong and we fix it rather than defend it.
Enrichment comes after scoring, not before. There's no point buying context on leads you shouldn't be calling.
08
How this gets scoped and priced
Scoped on the first call, quoted before anything starts. Price moves on list size and how clean your history is, since a model needs outcomes to learn from.
Enrichment carries a per-record cost from the providers. We pass that through at cost instead of marking it up, and you see the provider rate before we run anything.
09
When this isn't the right call
If you don't have enough closed history, there's nothing to train on. Under a hundred or so outcomes you're better off fixing capture and follow-up first, then coming back in six months with data worth scoring.
And if your team already calls every lead within minutes and closes most of them, ranking won't help. That's a capacity problem, not a prioritization one.
They built the pipeline with us: capture, enrichment, tagging, routing, enforcement. Every lead now has context, a next step, and someone accountable.