A more quantifiable way to connect qualitative need states to category management

In retail, a customer decision tree (CDT) is the first step in understanding shopper behavior. But all consumer decision trees are not created equal. We’ve combined the best quantitative methods from market structures and the best qualitative methods from traditional customer decision tree to deliver the best possible consumer decision tree on the market.

Years of experience developing robust and actionable customer insights
Households analyzed globally every week
Average category growth through improved customer-centric retailing

Retail consumer decision trees just got a lot more powerful

A consumer decision tree has always been a useful qualitative assessment tool. And market structures are great quantitative analyses. But when you combine them – and make them available via an intuitive user interface – the possibilities become exponentially greater.

Qualitative AND Quantitative

SymphonyAI’s Customer Decision Tree solution for retailers is a new approach to customer-centric merchandising that analyzes millions of household transactions at the store with universal product code (UPC) level insights to understand the true interdependencies and relationships. More than just a qualitative assessment like traditional consumer decision trees and more customer-centric than a traditional Market Structure, our solution allows category managers to truly identify and quantify the degrees of substitutability and transferable demand.

Customers buy UPCs, not PPGs

Promoted product groups (PPGs), sometimes called price promotion groups, are a useful tools for retailers and manufacturers. But just as a customer doesn’t pay the “average price,” they also don’t go to the store with a list of PPGs to buy. So, shouldn’t your consumer decision tree be done at the item and store level too? Ours is.

While most providers can’t handle the volume of data to do customer decision trees at an item level, our scalable cloud solutions allow us to do just that. And when you can understand the UPC-level insight dependencies and interactivities, you can make more informed decisions about assortments, promotions, pricing, and more.

Scalable Integration and Democratization

For too long, customer decision tree in retail has been a one-time analytical exercise – expensive, static, and quickly stale. In an omnichannel environment, both retailers and CPGs need solutions that can evolve alongside the constantly changing consumer behavior.

We’ve made the consumer decision tree available directly to end-users via an intuitive user interface, complete with collaboration and workflow enablement. When combined with regularly updated purchase, loyalty, and other longitudinal data, customer decision trees become an integrated and ongoing part of the category management process.

We’ve been able to automate and optimize our processes in everything from assortment and shelf replenishment to preparing orders for our customers

Andrija Derezic CIO
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