Space-aware assortments based on customer behavior increase sales, profit and loyalty.
For years, retailers have been carrying out assortment planning processes based primarily on historical sales data and not on current and evolving customer buying behaviors. This can lead to many problems including inflated SKU counts, which result in inaccurate forecasts, ordering issues, out-of-stocks and reduced customer satisfaction.
By feeding the assortment process with behavioral-based store clustering, retailers can optimize store groupings to drive more relevant item assortments by format, store, department and category. Symphony RetailAI’s intelligent clustering solution integrates demographic, loyalty and demand data to build more granular and relevant store groups by category – creating store groupings that more closely align with customer preferences as well as historical sales data.
Our assortment optimization solution leverages the intelligent store clusters to generate truly localized assortments that meet customer needs and are space and inventory aware. These customer-relevant assortments are built using price sensitivity data, product correlations, sales, profitability, assortment priorities and more, ultimately delivering assortments that fit the available space and ensure inventory is sufficient to avoid out-of-stock issues.
- Creates customer-relevant clusters for developing strategic space-aware assortments
- Consolidates multiple data sources and applies predictive analytics to create assortments that reflect local customer preferences and respect store space constraints
- Identifies and transforms category trends and market insights into informed category planning decisions
- Enables localized assortments that meet the needs of your most valuable customer segments
- Accelerates category growth by 2.8% on average through customer-centric assortments
- Dramatically improves employee productivity by cutting the category review processes in half
- Works seamlessly with shelf space planning to deliver assortments that are space aware