Category management is a highly competitive exercise in today’s face-paced retail environment, with each company seeking to increase their brands’ category market share and leadership presence through innovation and superior category strategy. 

Rarely are brands distributed according to their fair share of space at any given retailer, especially when assortment is optimized using a top-down approach that leverages averages of averages to push assortment into space available at each store. Even a small percentage of growth or loss can equate to millions of dollars. Therefore, it is equally important for all brands and Consumer Packaged Good Companies (CPGs) to protect & grow shelf space, regardless of whether they are below or beyond their fair share.  

Artificial Intelligence (AI) is the ideal tool to optimize assortment from the bottom up, looking at each store individually and using this analysis to determine the right assortment for each store or cluster. This approach allows CPGs to protect and grow revenue by maximizing retail space investment, all while uncovering growth opportunities for the category and improving the retailer / CPG strategic relationship.

Sound too good to be true? Here’s how.

Two-Prong Strategy: Protect & Grow category assortment 

Category management and retail sectors have always been dynamic, and every (Points of Distribution) POD is fought for in every relay. Direct to consumer brands and new innovations are fighting for the same space you are, with less on the line. To cope with the evolving competition amongst brands, AI helps CPGs identify the right strategy based on a predictive analysis of the most granular of data points through the two-prong “protect and grow” strategy:

Protect - Defending your category share & strategic value to your retailer

At HIVERY, we are often asked what happens if the AI recommends reducing a CPG’s space - and usually, this question comes from CPGs whose brands are well distributed and at (or above) a fair share of space. The answer is simple. With store-level assortment analysis taking into account store specific cannibalization, category advisors and non-advisors alike can protect their relationship and space by:

• Uncovering growth for their brand, optimizing existing space, and recommending SKU rationalization of products whose demand will transfer within the brand portfolio. This newly created space allows for increasing holding power to reduce out of stocks or swapping lower-performing products for those ‘sleeper products’ that will drive brand growth.
• Quantifying the value of each business and brand strategy through rapid SKU stimulation and seeing the impact before executing. AI can, in fact, provide data-driven, revenue-quantified recommendations to execute the strategies. This levels up the conversation with the retailer in ways not possible today and ensures the strategies are executable in-store and predicted to drive category growth.
• Identifying growth for their retailer, even within existing clusters protects the strategic relationship and everything that comes with it.  

Once existing space is protected, brands beyond their fair share can fight for additional space through new innovation, and HIVERY Curate can predict the success of the launch while pinpointing the best stores to launch in.

Grow – Capturing more category sales and space

AI-powered algorithms are able to optimize assortment at the store level by determining the unique ‘data fingerprint’ of each store and leveraging this to identify the assortment needs of each specific store. Even when executed at a cluster level, using this bottom-up analysis to identify what to add, remove or retain uncovers new opportunities for both brands and retailers. 

Where brands are below their fair share of space and expanded distribution would grow not only your brand but also the category, HIVERY Curate’s AI optimization provides specific recommendations on where to expand points of distribution (PODs), it identifies which SKUs to expand, and quantifies the revenue impact to the retailer. And, because HIVERY Curate’s optimization is aware of the actual space on the shelf, the AI often identifies room for additional facings or SKUs just by knowing how many inches are available.

Case Study: the two-pronged approach in action

Working with a large multinational company across two categories at a single retailer, our AI solution, HIVERY Curate, was used to identify and implement this two-pronged strategy. In one category where our CPG client had significant distribution, Curate identified growth for the category and the risk of reduced PODs to the CPG. With this information, our customer’s brand and sales teams have an opportunity to identify protective portfolio strategies, simulate their impact on the category and their revenue, and use this data-driven story to propose their programs to the retailer.

In another category where private label products have significant distribution, HIVERY Curate identified an opportunity for our CPG client to grow the category by also growing their distribution - a true win/win for all parties! 

Backed by the power of machine learning and proprietary algorithms developed over 5 years, together with an in-depth operations research method (often called applied mathematics) within HIVERY Curate, the CPG client was able to effectively plan and distribute optimal product assortments for each retail store.

As expected, the financial benefit was significant. Across both categories, we identified a $16M revenue growth opportunity for the CPG Client.

The next generation of category management solution

With the constant battle between category leaders and non-category leaders, the brands that are able to protect and grow their market share are the ones that survive and thrive. AI offers businesses an efficient way to do this.

As an intuitive AI-powered and user-friendly tool, it equips businesses with effective and compliant planograms that deliver the best results from physical retail space investment. 

In the end, it’s not just about earning more slices of the pie, but rather about growing the pie itself. HIVERY Curate delivers accurate, effective, and executable store-specific recommendations to improve and ensure the growth of the whole category.

How can HIVERY help you?   

HIVERY is the pioneer of hyper-local retailing – combining artificial intelligence, machine learning, optimization, and design to help CPGs and retailers generate an increased return on physical retail space investment.    

Related resources you might be interested in:

Webinar: Leveraging AI towards locally relevant shelves: Why data has a better idea about your store clusters

Guide: Retail Store Cluster Strategies: Leveraging AI Towards Locally Relevant Shelves

To learn more about Heather Martin