Retail & Media

Tier-one merchandising platform - planogram optimization

Category arrangement optimizer ran in 6–10 minutes per scenario, blocking interactive planning sessions

Industry

Retail & Media

Status

In production

Tier-one merchandising platform - planogram optimization

The challenge

A provider of image recognition tech and market data services for tier-one manufacturers needed to dramatically reduce optimization run time from 6–10 minutes to near real-time so merchandisers could test scenarios during live planning sessions. They also needed to improve sales uplift from prior baselines through better alignment between store characteristics and target outcomes.

What we built

The team upgraded a genetic algorithm based optimizer that recommends category arrangements by size and adjacency. By strengthening selection, mutation, and randomization operators, and by reframing the fitness function to better match store features with sales targets, run time dropped from minutes to near real-time and uplift improved materially. The optimizer now recommends commercially useful layouts rather than purely academic optima.

The impact

What changed

10x faster

Optimization speed

from 6–10 minutes to 30–60 seconds

7–8%

Sales uplift

improved from ~3% baseline

Real-time

Interactive what-if scenario testing in planning sessions

Built with

Genetic AlgorithmsConstrained OptimizationImage RecognitionReal-time ProcessingProduction MLFitness Function Design

See what we can build for you