Use cases
A guide to the problems that come up again and again. Each one with the detail of how it is solved, what goes in, what comes out, and what is discovered along the way.
Customer churn prediction
Who is leaving, with how much lead time and why. A model that calculates the probability of cancellation and the signals that carry the most weight, so the team acts on the customers that matter to retain.
See case →Purchase propensity
Who is close to buying, and what. A probability per customer, recalculated before each send, so the message reaches the person who was waiting for it.
See case →Demand forecasting
How much will be sold, and with what margin of error. By SKU and by period, with a range in addition to the central value, integrated in the planning cycle that already exists.
See case →Customer lifetime value
How much each customer will be worth, before they demonstrate it with their history. The difference between knowing how much to pay for a customer after a year and knowing it on day one.
See case →Customer segmentation
Groups built from observed behaviour, not declared attributes. With an actionable profile for each group, so the team can do something different with each one.
See case →Everything you know about a customer, in one place
What is scattered across systems, read and unified without moving it. Structured fields and text profile, with traceability of each data point to its source.
See case →A system of agents working for your team
Analysis, decision, writing and review, each step with its own specialist. The campaigns your base would generate, with the team you have.
See case →