Abstract
The discipline of category management has always played an important role within retailers as well as their CPG manufacturer suppliers. While the eight steps within the category management process (category definition, category role, category assessment, category scorecard, category strategies, category tactics, category implementation, and category review) have remained the same, with digitalization the discipline is undergoing a massive transformation, and the approach to the process is getting disrupted through the availability of huge volumes of transactional data, customer loyalty data; advancement in hardware technology through better scanners, image recognition devices, sensors and IoT devices and machine learning, and artificial intelligence. In this chapter, the authors take a closer look at the eight-step category management process, the traditional approach, the enabler for disruption, the new approach, and its benefits and what the future may hold.
TopIntroduction
Category Management is the discipline of managing a related group of products as a category or a business unit whereby its performance with respect to metrics such as sales velocity, margin, revenue, market share, etc., are closely monitored to meet the overall objectives of the business. While there are several reasons for the existence of this discipline, one of the primary reasons is that it allows retailers to take a holistic view of their categories rather than a brand-centric or a product-centric view thereby promoting better alignment with corporate financial objectives. Also, it enables retailers and suppliers to collaborate enabling them to take advantage of each other’s strengths, for instance retailers have plethora of data on shopper insights whereas the suppliers have deep expertise related to the products.
Although this practice has been in existence for centuries, the term Category Management was formally coined in 1989 by Dr. Brian Harris, co-founder of The Partnering Group. Over the years, this concept has received several definitions. According to the Category Management Report (1995) published by the Joint Industry Project on Efficient Consumer Response, or ECR, it may be defined as “The distributor/supplier process of managing categories as strategic business units, producing enhanced business results by focusing on delivering consumer value”. Nielsen (1992) takes a slightly different approach - “Category management is a process that involves managing product categories as business units and customizing them [on a store by store basis] to satisfy customer needs.”
Although Catman (Category Management abbreviation) has evolved significantly over the last thirty years, it still retains its fundamental purpose to push manufacturers and retailers to work collaboratively to grow categories by understanding and responding to market trends and shopper needs. This evolution has been driven in great part by two important factors, first the needs and challenges of the retailers and second advancement in technology, especially Digitalization. More than ever, technology is allowing retailers to address historic problems or even recreate some market ecosystems. It is important to mention here a few of these aspects to provide some perspective on how the consumer landscape is evolving and how it is important for the Catman process to be adapted to these new circumstances. In the article “Retail Trends 2018 – A transformative time for retail” published by Deloitte (2018), the authors highlight 3 important “themes” which every retailer should be aware of and suggest they have a clear set of actions to address the same. The themes highlighted are as follows:
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First, stores need to be reinvent themselves to be more than stores, providing also customer experiences. They need to be able to “put digital in the physical” by making digital part of the core, replicating part of the ecommerce experience in the offline environment.
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Second, innovation needs to be applied though experiments, since new technologies such as augmented / virtual reality, artificial intelligence and others will demand a “trial and error” approach in order to find the right balance in every company.
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Third, companies should be willing to transform their businesses, since customer, competition and culture are constantly changing. Trends like “Try before you buy”, “Direct to consumer” and “Brand purpose” need to be understood, evaluated and applied carefully.
Key Terms in this Chapter
Customer Decision Tree (CDT): It refers to graphical representation of a customer’s buying decision process expressed in a tree format. For example, when a customer is choosing an ice cream an example of the decision tree could be size, followed by flavor followed by brand.
Click and Collect: Is a hybrid e-commerce model in which people place orders online and go to physical location to collect which could be stores or parking lot or any other location.
Cash and Carry: It is a store format resembling a wholesaler which originally used to focus on B2B but is also now available to end consumers. Its hallmark characteristics are low prices and limited assortment and services.
Conversion Rate: In the category management context refers to the percentage of people entering the store that have bought something.
House Panels: Group of houses that routinely participate in surveys and research to answer questions related to wide ranging topics from political inclination to consumer preferences.
Cannibalization: In the category management context, this term denotes a negative impact a new product has on the sales performance of its related products. When this happens, the demand from existing products shift to the newly introduced product potentially reducing overall sales.
Social Sentiment: It is a way to measure the emotion behind mentions on social media. It is important to understand not just if some subject, brand or person is “trending” but also in which direction, positive, negative, or neutral.
Trade Up: Category strategy where the retailer tries to encourage current customers to spend more by changing products in their baskets to bigger sizes and/or premium versions.
A/B Test: Also known as split testing, is an experiment comparing two versions of a single strategy, typically by testing a subject's response to variant A against variant B and determining which of the two variants is more effective. This can be used, for example, to compare different versions of a promotion that were implemented in two distinct store groups.
Perfect Information: Economic term to define a competition scenario where all consumers and producers have perfect and instantaneous knowledge of all market prices and other important information.
IoT Devices: IoT is short for internet of things and refers to a growing network of physical devices featuring internet connectivity using with they can communicate with other devices and programs.
Shopper Behavior: Actions taken by consumers at the point of sales or while shopping online. Not to be mistaken by consumer behavior, since the person buying a product is not necessarily the same who will use it afterwards.
Planogram: Also known as plan-o-grams or POGs. They are visual representations of store products and their shelves, strategically organized in order to achieve category goals.