Data-driven consumer goods innovation

Vypr helps to optimise products before they reach our supermarket shelves. Vypr gathers opinions from consumers to help retailers and manufacturers validate and develop fast moving consumer goods (FMCG). The platform provides a (disruptively) cost-effective way to get insights that save waste from launching new products destined for failure and tune innovation to improve profits.

Vypr gathers data from mobile apps that are designed to emulate real-world shopping decisions as closely as possible. This is made possible by the lessons learned from behavioural economics research.

I’ve been working with Vypr since 2016, providing a data science Strategy to support Vypr’s Roadmap and then implementing analytical methods (like multinominal logistical regression modelling and conjoint-analysis) within the platform.

These techniques will help to inspire confidence with statistical rigour to produce new insights:

• focusing reporting such that only the most scientifically robust results are presented
• providing relevant context to help users take better informed decisions
• exploring the role of psychological, social, and economic factors in consumer behaviour
• predicting the most profitable pricing strategy and product design
• filtering to the most consistent and reliable respondents and
• ensuring representativeness and supporting retention of the panel
• demonstrating impact to clients with impact evaluation