Lead Scoring API With Typed Confidence for Small B2B Teams
Score inbound leads in real time with a calibrated probability instead of a made-up points system, and push hot leads straight to Slack.
$9,000MRR potential
85/100Opportunity score
EasyBuild difficulty
MediumCompetition
The problem
Points-based lead scoring is guesswork, and real predictive scoring tools are priced for enterprise.
The solution
A HubSpot/Pipedrive integration that sends signup data plus enrichment to a decision model and returns fit and intent probabilities, then alerts reps on hot leads.
Why now
Decision models return calibrated probabilities natively, so you can set a real threshold like 'alert when P(fit) > 0.8'.
Who pays
B2B SaaS teams with 200-5,000 inbound signups a month and no data team
Market size
$2.6B (estimated addressable market)
Build plan
PROTech stack & AI models
- Jev for fit and intent scores
- Claude Haiku 4.5 for a one-line lead brief
- HubSpot and Pipedrive APIs
- Clearbit-style enrichment
MVP scope (ship in 2-4 weeks)
- Connect CRM in 2 clicks
- Define ICP in plain English
- Slack alert with the lead brief
- Closed-won feedback loop
Pricing model
$79/mo up to 1k leads, $249/mo up to 10k.
First customers & go-to-market
- HubSpot App Marketplace
- Write 'lead scoring for startups' guides
- Launch on Product Hunt with a free tier
Copy-paste prompt to start building
Write a function that takes a signup payload and an ICP description and builds the Jev request with two score questions (fit 0-1, intent 0-1) and one choice question (segment).