Inside the product
Actionable insight, in real time.
In for-profit education, buyers couldn't tell good leads from bad. We built a machine-learning platform that predicts which inquiries convert into enrolled, paying students — and beat a $4 billion incumbent 5-to-1.
Nobody could tell good leads from bad.
In for-profit education, marketers bought inquiries by the hundreds of thousands — but couldn't reliably tell which would convert into enrolled, paying students. Lead scoring was demographic and static: run in spreadsheets, remodeled every year or two, one price for every lead. The result was an efficiency death spiral — lower-quality leads, lower campaign performance, lower margins, and ever-lower prices.
Predict conversion, in real time.
Build a SaaS platform that predicts inquiry conversion — from form to paying student — so buyers can score, filter, and price every lead in real time.
Big data + machine learning.
We built LegitLead: a predictive-analytics platform trained on consumer big data from first- and third-party sources, with breakthrough data-science technology and proprietary algorithms.
5× the leader; a profitable exit.
LegitLead delivered a 5× improvement in lead-conversion efficiency versus Targus — the leading provider and a $4 billion public company — and commanded a 14× price premium over standard lead-validation tools. A pilot with DeVry University cut customer-acquisition cost 40–60%; Carrington College became the second customer within the first year. The company reached profitability at $500K in first-year revenue at 85% gross margin, then exited to a strategic buyer in the for-profit education industry.