CPG companies and retailers need to carry the right product assortment to meet customer demand and expectations. Effective localization of assortment and space planning can be a very challenging task. Most retailers often fall short of harnessing the true potential of technologies and techniques in Machine Learning (ML) and Operations Research (OR), often called Data Science.

In this report, Coresight Research analyzes key industry trends and discusses how CPG companies and retailers can achieve the goal of customer-centricity through the hyper-localization of assortment. We consider data and assortment planning challenges and the skills required to succeed in retail category management.

The research report explores how HIVERY has uniquely combined these technologies into a "single learning engine," which harnesses store-specific SKU data that delivers locally relevant and effectively merchandised shelves. The age of precision category management.

These technologies are now allowing teams in category management, shopper insight, marketing, and sales the ability, for the first time, to conduct rapid retail strategy simulation & optimization.

By increasing accuracy and removing the manual process, these new methods and approaches offer a competitive advantage to both CPG companies and retailers, transforming Joint Business Planning (JBP) sessions between the retailer and CPG, and arming them with win-win category strategies rapidly.