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In order to meet customer demand and expectations, it is essential for CPG companies and retailers to carry the right product assortment. Effective localization of assortment and space planning can be a very challenging task, and most retailers often fall short of harnessing the true potential of technologies such as artificial intelligence (AI) and modern approaches in machine learning (ML) and data science (DS). In this report, Coresight Research analyze key industry trends and discuss how CPG companies and retailers can achieve the goal of customer-centricity through the hyper-localization of assortment. We consider challenges in using data and assortment planning, as well as the skills required to succeed in retail category management. They also explore how HIVERY has combined ML and DS into “single learning engine”, which harnesses store-level data for category management optimization, enabling precision in category management and localized assortment. 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 arming them both with win-win category strategies rapidly. |
