For companies that span across a wide range of geographies, the question of where, what and how much to sell of any given product is difficult to answer, and requires a significant amount of manual effort. But does this have to be the case?
Our client, a multinational consumer packaged goods (CPG) company was struggling to answer these questions effectively, and was failing to realize the true potential of its stores.
Download our latest case study and discover how Fractal leveraged AI algorithms to increase store coverage and net revenue, while reducing the cost to serve.
Monitoring the evolution of consumer’s retail demands means making sense of a mountain of data
The Challenge - Our client needed to see the full picture
Siloed and disparate data for customer segmentation, route planning and stock lists was preventing the business from reaching its potential.
• We introduced AI algorithms to work through the calculation of customer segmentation, coverage and route optimization.
• Our solution was divided into three key areas: advance discovery, packaged AI and actionable insights, all with the aim of creating an intelligent enterprise.
• Store potential was optimized with MSL rankings and AI-enabled recommendations.
Results - Our route-to-market solution provided a wealth of benefits
Store visits increased by 20%
Store coverage improved by 30%
Cost to serve was reduced by 12%
Net revenue improved by 4%
Download our case study and learn how CPG companies can reach their full potential with revitalized route-to-market strategies, all enabled by AI algorithms.
Download the full case study
Download our case study and learn how CPG companies can reach their full potential with revitalized route-to-market strategies, all enabled by AI algorithms.
