The signals that predict a close are behavioral, and behavior is observable on your own property with consent. No purchased personal data, no identity graph, no cross site tracking. AllState converted 47.73% of worked leads on this basis.
| Signal type | Used |
|---|---|
| First party behavior on your site | Yes |
| Engagement with your follow up | Yes |
| Firmographics the buyer gave you | Yes |
| Purchased personal data | No |
| Third party identity graphs | No |
| Cross site tracking | No |
Stated before an engagement rather than after a complaint.
Most scoring models weight who someone is. The ones that work weight what they just did, and how recently.
Which pages, in what order, and how long.
Three things this week beats ten things in March.
How they engage once you reach out.
What the buyer chose to tell you, and nothing more.
A score nobody acts on is a dashboard. The point is a call list that is right often enough that the sales team stops second guessing it.
SeedLeads centralizes capture so scoring reads a single record per person rather than three partial ones across three tools. Most scoring projects fail here, before any model exists.
Weighted on intent depth, recency, velocity and response, with decay so the queue reflects this week rather than last quarter.
LeadChaser acts on the score, timed to the buying window rather than a campaign calendar. AllState converted 47.73% of worked leads this way.
Closed and lost both return to the model, so the weighting reflects what actually converted for you rather than what converts on average for someone else.
This is not run by a black box of tools. It is a team of Growth Architects who plan, build and optimize it, using AI where it accelerates the work and human judgment where it actually matters. Different specialists, one accountable team.
Meet the team →
Michael · Engineering Lead
Amal · Automation Architect
Bryn · Solutions Engineer
If we can't increase your revenue by the 6 month mark, our team works for free until we do.
“BusySeed created and managed our social media and wrote blogs that raised our SEO to a new level. We are getting new clients from organic search, and their lead generation campaigns made it easy to justify the investment by focusing on ROI.”
“BusySeed demonstrated tremendous ability in understanding our needs and taking us by the hand in the process of designing a digital strategy from scratch.”
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Yes, and for most businesses it works better. A useful score comes from what someone did, not from who they are: which pages they read, how deep they went, whether they returned, which questions they asked, how quickly they responded. None of that requires a data broker, a third party identity graph or a profile assembled behind the visitor back. The signals that actually predict a close are behavioral, and behavior is observable on your own property with consent.
First party behavioral and intent signals: pages viewed and in what order, time on high intent pages such as pricing and comparisons, return visits, content depth, form and reply latency, engagement with follow up, and the firmographic context the person voluntarily gave you. Recency and velocity matter more than any single action, because a buyer who did three things this week outranks one who did ten things in March.
Purchased personal data, third party identity graphs that deanonymize visitors, cross site tracking that follows people off your property, and anything inferring sensitive characteristics such as health, finances, religion or politics. Those carry real regulatory exposure and they rarely improve a model that already has behavior. We would rather tell you what is off the table before an engagement than after a complaint.
No, and attribution data is getting less reliable anyway: measured across the industry, attribution accuracy has deteriorated 40-60% over the past eighteen months as third party signals disappeared. A model built on first party behavior is more durable precisely because it does not depend on signals that keep being switched off. AllState converted 47.73% of worked leads using LeadChaser on this basis.
Yes, though the score starts coarse and sharpens fast. With a name and email you still have domain, which gives firmographic context, plus every behavioral signal from that point forward: whether they open, what they click, which pages they read next, how quickly they reply. The first score is a guess. The third is usually well calibrated, which is why the follow up sequence matters as much as the model.
Our own stack. SeedLeads captures and centralizes records so scoring has one clean source; LeadChaser works the scored records on a cadence tied to the buying window rather than to a campaign calendar. Because we built both, the logic is tuned per client rather than configured from a template. See revenue growth for how scoring fits the wider system, or B2B lead generation for what feeds it.
Book a free 15 minute session. We will look at how your leads are currently prioritized and show you what a behavior based model would have ranked differently.
