AI predictive lead scoring for HubSpot Pro
- No config. Three steps, about three minutes.
- No black box. Plain-English reasons on every score.
- Updated daily. Every lead re-ranked overnight.
- No upkeep. No rules to write, no thresholds to tune.
- In HubSpot. Scores write back to your contact properties.
It's like hiring a tireless data scientist to live inside your HubSpot account: learning your ideal buyer, continuously watching prospect behaviour, and handing your reps a ranked list of every lead each morning.
Why this score
- Visited pricing 3× this week
- Opened the last 5 emails
- Series B · 120 employees
Illustrative example
What changes on Monday morning
- Effort goes where it converts. Reps start at the top of a ranked list, not the top of the alphabet.
- No more time on cold leads. The triage is done before anyone opens the CRM.
- Reps get to the call sooner. No morning spent deciding who's worth a dial.
- Fewer arguments about lead quality. Sales and marketing work one ranking instead of trading opinions.
- Nothing to maintain. No rules, no thresholds, no quarterly scoring workshop.
- Marketing spend goes further. Less budget consumed working leads that were never going to close.
Built for HubSpot Pro sales teams drowning in inbound
Every lead, ranked
Ranked by likelihood to convert and rescored daily. Sort by score, or by what moved most recently.
Live from day one
Connect HubSpot and scores arrive in about fifteen minutes. No field mapping, no data scientists, no closed-deal minimum.
Native to HubSpot
Scores write back to your contact properties. Your reps never leave the tool they already use.
Reasons, not just a score
Every score comes with the handful of signals behind it, in language a rep reads in three seconds.
The model only changes when it's better
A new model has to beat the one you're on, measured on your own closed deals. If it doesn't, you keep the one that works.
Your reps tell us when we're wrong
Thumbs up or down on any score. It doesn't quietly retune your ranking behind your back. Closed deals are what change the model.
Predictive wins
| Dimension | Manual scoring, on HubSpot Pro | Predictive scoring, on HubSpot Enterprise |
|---|---|---|
| Bias | You guess which signals matter. | The model finds what actually preceded closed-won deals. |
| Keeping current | Rules go stale until someone updates them. | Retrained as new outcome data arrives. |
| Complexity | A handful of rules a person can hold in their head. | Many signals weighed at once, including how recent each one is. |
| Ops workload | Days spent building and tweaking if/then logic. | Runs in the background. |
| Lead decay | Ready buyers wait their turn in a rigid tier. | High-probability buyers surface at the top. |
| Sales and marketing | Sales blames marketing; marketing blames sales. | One objective model both teams can point at. |
LeadCondor brings predictive lead scoring to HubSpot Pro.
Connect, confirm, done.
One OAuth click to connect. No field mapping, no data scientists, no setup project. Then day-one scores start landing in your Action Feed.
Stop guessing who to call.
Put rep time where the revenue is. If LeadCondor surfaces even one deal your team would otherwise have missed, it likely pays for itself. Start a free trial and see your leads ranked in minutes.
Start free trial, no credit card