Demand Forecasting
Churn Prediction
Price Prediction
Data Pipeline & Model Training
Agentic Coding Coaching
Large Language Models
Focus on the leads that will actually convert
Sales teams treat every lead the same, or rely on simple rules — company size, job title — that miss the real buying signals. Marketing spends equally across audiences that convert at wildly different rates.
We build conversion prediction models from your website traffic, CRM data, and sales history. You get a scoring model that tells your sales and marketing teams which leads are most likely to buy, so they spend time on the right ones.
Sales reps spend just 30% of their week actually selling. The rest goes to admin, data entry, and chasing leads that won't close. Salesforce, State of Sales.
A model that scores every visitor or lead by their likelihood to buy
Three places this changes your business
A scored lead list changes how sales teams spend their day. High-probability leads get called first. Low-probability leads get a nurture sequence instead of a phone call. The result is more conversions from the same headcount.
A B2B software company increases its close rate by 31% after ranking leads by conversion likelihood instead of recency.
Audiences that look similar can convert at very different rates. A conversion model identifies the signals that actually predict purchase, so you can concentrate spend on the segments and channels most likely to buy.
An e-commerce brand reallocates 40% of its retargeting budget toward high-score visitor segments, improving return on ad spend without increasing total spend.
Knowing that a visitor is likely to buy lets you treat them differently in real time: a more direct offer, fewer friction points, a faster path to checkout. The score is the input. The intervention is yours.
A subscription box company shows a time-limited offer only to high-score visitors, increasing checkout completion without discounting across the board.