Geo-temporal demand prediction for high-ticket home services.
Roofing, HVAC, solar, remodeling, and pool/spa operators use predictive intelligence to anticipate demand at the geo-temporal level — and to concentrate spend on prospects within the active decision window.
What makes Home different.
Geo-temporal demand
ZIP and DMA-level demand prediction tied to seasonality, weather events, and macro signals.
Decision-window scoring
Probability of decision within 30/60/90-day windows.
Decay, velocity, and cost — measured.
Per-vertical curves derived from the platform's calibrated model output. Industry averages overlaid for reference.
Hours since first intent signal
Days from first contact
Traditional vs. predictive within the vertical
Inside a deployment
Mid-market lender lifts ROAS 3.1x with behavioral risk + intent overlay
Behavioral risk scoring integrated with intent signals produced cleaner top-of-funnel for a consumer lender. The combined model reduced underwriting waste 38% and lifted return on ad spend 3.1x within two quarters.
Supporting research & guides
roofing storm restoration data
hvac replacement intent
solar installation leads
pool spa prospect targeting
Common questions
Do you support weather-driven demand spikes (e.g., post-storm roofing)?+
Yes. Weather-trigger signals are part of the home-services model family.
Predictive intelligence · enterprise onboarding
Move from list-buying to probability-buying.
Engage your account team for a calibrated intelligence estimate, methodology walkthrough, and a sandbox environment scored against your own audience.