Merchandising used to be described as a balance of art and science. The metaphor worked for an era when the experience and instincts of individuals were blended with technology and data-driven insights to make decisions about product assortments and category space allocations. The balance ultimately tipped because technology advanced rapidly and data volumes increased exponentially. Merchandising is now fully on the side of science and AI is transforming how optimal space and category decisions are made.
For CPGs, the increased use of AI is a good thing because it means retailers can make objective, agile decisions based on science. That means CPGs need to elevate their use of AI to optimize decisions, analyze interconnected variables and improve the predictability actions recommended to retailers. Here’s a look at eight key areas where CPGs can put science on their side to master the modern art of merchandising:
Assortment Optimization: This is a broad area with many components, but ultimately the assortment end game is about retailers and CPGs working together to serve a mutual shopper while achieving their respective business goals.
It’s a lofty goal, but CPGs who embrace science can become trusted advisors to retailers because their recommended actions are rooted in facts which retailers can trust. One way CPGs can demonstrate their expertise involves developing and recommending planograms that balance days of supply, facings and the breadth and depth of the offering across all stores. AI gives CPGs the ability to adjust these variables, and others, in an iterative process based on the requirements of individual retailers to demonstrate different outcomes and recommend the optimal path forward.
Optimization for All
Another way CPGs put science on their side is with the use of solutions that support the complexity associated with working a broad range of retailers. The unique requirements and value propositions of different retailers challenge CPGs’ ability to make optimal assortment and trade promotion recommendations.
That’s why it is important to take advantage of technology that addresses the wide range of use cases that demand flexibility of CPGs. For example, a CPG may want to optimize and determine core assortments at a national level and then further optimize at a regional and local level. Then AI can optimize against different fixturing and shelving configurations found at various retailers. The types of optimization can vary widely depending on the retailers and use cases, which is one reason why AI is essential.
Space Elasticity & Incrementality: Bringing the concept of elasticity to the shelf is a key element of the optimization process and an area where CPGs can demonstrate leadership. Elasticity is most commonly associated with how price and promotion changes affect demand, but the principle also applies when facings are increased or decreased.
Leveraging science gives CPGs the ability to understand how the incremental addition of space affects demand for an item when facings are adjusted and how those changes impact demand for other items. For example, if facings are removed and demand transfer is substantial, then adjustments could be required for facings and days of supply for other items.
Demand Transference: Key to a CPG’s ability to develop and confidently recommend optimal assortments is understanding demand at the item level. In most categories, the majority of sales of any individual product comes from customers who share their spend across a range of products. Understanding the drivers of these decisions is key to how CPGs can optimize assortments. However, attributes can vary dramatically by item and category and some customer segments may shop by attribute based on specific lifestyle or dietary needs.
AI can understand these interactions and correlations that exist, giving CPGs the ability to understand what happens to certain products in the presence or absence of others. From an assortment planning perspective, this demand transfer capability means that as a new product is introduced it is possible to know with a high degree of precision where exactly demand would come from and where that demand would transfer to.
New Item Forecasting: AI improves the accuracy of forecasts for new product introductions, which have notoriously high failure rates. There are two components for CPGs to consider.
First, there are the characteristics of products and understanding shared demand as well as the role of those characteristics within categories and their importance to different groups of customers. Equally important are the characteristics of retailer outlets and regions where the products will be sold. AI gives CPGs the ability to understand how a product will perform by retailer and region, thus greatly enhancing new item forecast accuracy.
Second, it is also important to distinguish genuine new item introductions from products seeking increased coverage within existing or new retailers. The distinction is important because with genuine new items that lack sales history, CPGs can improve forecast accuracy by leveraging AI to assess combinations of attributes and characteristics that exist with other items in the marketplace.
Customer Decision Trees: Different customer segments shop categories differently and decision trees provide a hierarchical view to improve understanding by customer type. This ability is powerful because decision trees can be leveraged within the assortment planning process to analyze and optimize from multiple angles. For a CPG, it’s also very powerful because if you leverage the consumer decision tree and combine it with other optimization capabilities, it is possible to optimize based on manufacturer or brand and compare performance. That goes a long way toward lending credibility to recommendations made to retailers.
Days of Supply: Another area where science plays a significant role is optimizing days of supply. Often with retailers’ days of supply constraints there is some flexibility which can affect a CPG’s ability to secure additional facings for existing products or expand distribution of new items. Leveraging AI allows CPGs to analyze and understand whether a retailer has established the optimal days of supply and whether rules should apply to an entire category.
With days of supply optimization, a CPG can use science to understand the interplay of variables among items and categories and make a fact-based days-of-supply determination. For example, CPGs can analyze assortment breadth, item performance and various days of supply numbers to make highly accurate recommendations to boost overall category performance.
Shelf Intelligence: A longstanding source of frustration among CPGs is the gap between the creation of planograms and their execution in stores. The issue has been compounded due to the increasingly dynamic nature of shopper demand and the tactical levers retailers pull to increase sales that can cause planograms to vary store to store. As a result, CPGs have a heightened need to understand what is really going on in stores, which is one reason why shelf intelligence solutions are gathering momentum.
By gaining shelf intelligence, CPGs can capture the reality of what is happening across a large number of stores to understand planogram compliance, product distribution, pricing, on-shelf availability, fixturing and adjacencies. These type of insights – the ability to identify in real time where problems are and what to do about them – are valuable to retailers and help elevate the status of CPGs able to provide them.
Ultimately, shelf intelligence can also influence the timing of category resets because CPGs who rely on AI solutions are able to make recommendations to retailers based on category needs rather than rely on the traditional calendar-based approach.
Put Science on Your Side: CPGs face an abundance of challenges when working with retailers in an environment with fast-changing shopper and market behaviors. Many CPGs are familiar with AI but others are new or evolving rapidly as technology advances to offer new capabilities. CPGs who win the shelf will be those who master the modern art of merchandising by leveraging the latest tools and techniques to elevate their status as trusted retail partners.
Want to learn more about the modern art of merchandising? View a replay of the Category Management Association webinar “Win the Shelf: Making the Case for Space,” or access the whitepaper, “Assortment and Space Optimization for Competitive Advantage.”