Predictive Analytics

You can see which customers bought. You can't see which ones are drifting away before they leave. You can see your revenue total. You can't see which customer segments are responsible for most of it — or what they have in common. Every business that has transaction history is sitting on a predictive dataset they have never analysed.

Fortune 500 data science teams built customer churn models and demand forecasting infrastructure over years, at a cost that was never accessible to a $5M business. The platforms that run these models at scale are now priced in the hundreds of dollars per month, not millions. What has been missing is not the platform — it is the person who can configure it correctly for a specific business problem and interpret what it tells you.

We build predictive models on your transaction history. We identify which customers are showing early signs of leaving — declining order frequency, smaller basket size, longer gaps between purchases — before they actually go. We map what your top 20% of customers have in common, so you know who to find more of and where.

We forecast demand by product, location, or season. We identify what the next likely purchase is for each customer segment. The output is specific and expressed in business terms — not statistical output. Available as a standalone engagement for businesses with sufficient transaction history, or integrated into Strategy & Design work.