Shaping Assortment Strategies with AI-Driven, Store-Level Analytics
In the contemporary retail sector, the abundance of data is a double-edged sword. While it offers many insights, navigating this vast information to extract actionable intelligence can be daunting. That’s where advanced analytics transforms raw data into a powerful tool for assortment planning and decision-making.
One of the core aspects of retail management is assortment planning—deciding which products to stock to meet consumer demand and optimize shelf space. This is a delicate balance, as overstocking and understocking can lead to lost sales and increased costs. With traditional methods, achieving this balance is often based on intuition or outdated models, which may not reflect current market dynamics.
Enter the era of in-depth analytics. Modern analytics tools like HIVERY Curate can provide hyper-local, retail-specific store-level insights by harnessing machine learning and AI. These tools go beyond just crunching numbers; they simulate, qualify, and optimize dynamic strategies within real-world constraints.
They empower retailers and Consumer Packaged Goods (CPG) manufacturers to ask critical questions and receive qualified predictions on the potential impact of specific strategies. For instance:
- How to maximize the productivity of existing space?
- How to rationalize each store's Stock Keeping Units (SKUs) while limiting churn to 5%?
- What is the impact of demand transfer across the portfolio?
- What opportunities exist to re-optimize cluster strategy and planogram numbers?
These questions highlighted the value of data in optimizing supply chains, especially in Distribution Centre (DC) optimizations. From a DC and in-store standpoint, proper channeling can significantly improve supply chain efficiency.
One of the key takeaways from working with over 100 different categories of CPG brands and their retailers is the potential of analytics in solving the Days of Supply (DOS) conundrum and vendor-specific DC optimizations. By using data analytics, it's possible to build vendor-specific DC optimizations, which can significantly value-add to the supply chain process. This enhances the store-side operations and paves the way for backtracking the days forward coverage in the DCs by item by DC, leading to a more streamlined supply chain.
With the right data at the store level, HIVERY Curate can significantly simplify the work of category managers. This is especially valuable for retailers such as Walmart, Target, or Dollar General who are facing challenges like overstocking and drops in stock prices. By using HIVERY Curate, these retailers can optimize their operations and make better decisions.
The significance of establishing appropriate partnerships and achieving a high level of engagement between retailers, manufacturers, and analytics providers cannot be overstated. With effective collaboration and investment, utilizing comprehensive analytics for optimizing assortment and supply chain is a futuristic vision and a present-day reality.
As the retail landscape evolves, the ability to smartly navigate it with in-depth analytics will be the linchpin for successful assortment strategies. The journey from data to decision is now more streamlined, insightful, and actionable, thanks to the advent of sophisticated analytics tools like HIVERY Curate. See how HIVERY Curate can help you unlock the full potential of AI-driven retail assortment space optimization.
Related resources you might be interested in:
- Podcast - How does AI help with assortment deletions and additions?
- Over-assorted sub-categories? HIVERY Curate Offers Solutions
- Omnichannel Assortment Optimization - Understanding Retail through Online and Offline Synergies
- Navigating Common Pitfalls in Product Line Reviews (PLR): A Guide to Success with HIVERY Curate