The situation
A software company for the events industry sold a range of products and add-ons. Once a customer had bought one product, there was often a natural next one.
The problem
The business wanted a systematic way to say which products went well together, so that upsell conversations were based on evidence, not instinct.
What we did
The team looked at the history of what customers had bought and searched for patterns: which products tended to appear together, and how strongly. It's the same idea supermarkets use when they work out which items are bought in the same basket.
From these patterns the team wrote simple, targeted rules, along the lines of "customers who have bought X are good candidates for Y", and handed them to the people who talk to customers.
The outcome
In a single month, the targeted upsell approach brought in an extra $20,000 in revenue.
What it meant for the business
Conversations with customers became more relevant, because they were based on what similar customers had actually found useful. Rules like these are easy to explain, easy to adjust and easy to extend as new products arrive.
Could this work for you?
Any business with an order history can look for natural pairings. You may be surprised by how much opportunity is hiding in plain sight.
Related services: Data analysis and insights, Customer 360
This project was led by our founder, Achyutanand Jha, in an earlier role. The client is not named, and figures are those reported at the time.