The Candy Aisle Renaissance: From Impulse Buys to Strategic Category Growth
Insights help arm a brand with the knowledge that can lift an entire category for a retailer, earning them category advisor roles at coveted retailers.
The candy category is much more than the Halloween season and the impulse rack at the checkout lane. It’s an innovative $43 billion business, increasing sales annually, partly due to inflation, but also due to consumers seeking an affordable way to treat themselves. Retailers too are developing a larger in-store presence for the category.
I know this from my days as SVP of merchandising at 7-Eleven, where we frequently leaned on candy to deliver innovative opportunities for sales growth inside the stores.
For candy brands, however, navigating the shifts in consumer behavior can be difficult, knowing that the products are largely bought on impulse. How do you effectively target a consumer who may not know they want that sweet treat yet?
On top of that, brands need to understand behavior shifts at a wide range of retailers such as mass merchants, club stores, traditional grocers, c-stores, drugstores, dollar stores and hard discounters — and even sporting goods and apparel are in the game.
Factor in consumer trends such as seeking smaller pack sizes and using social media for inspiration, and predictive analytics and machine learning can become major tools to help craft a winning candy strategy.
At 7-Eleven, I saw my fair share of wild flavors in novelty non-chocolate candies, sour chewy offerings and hard candies driving these sales and reaching a growing interest among millennial and Gen Z markets. But there are other behavioral trends and product trends to take note of, too:
Portion control. According to the NCA report, eight in 10 consumers seek smaller pack sizes to help curb how much they eat. The report also noted that consumers are seeking guidance from brands on appropriate portion sizes, factoring in calories, sugar and the impact of natural ingredients.
Healthier and functional candy. Consumers are increasingly looking for candies that offer health benefits, such as low-sugar, sugar-free, organic and fortified options. Functional candies with added vitamins, probiotics or other health-promoting ingredients are gaining popularity.
Nostalgia brands. Nostalgic or retro brand candies from the past continue to make a comeback, appealing to consumers who want to relive childhood memories through their favorite sweets.
Multi-channel purchases. The NCA report found nearly 60% of consumers said they buy candy at checkout in the impulse section, but they’re also buying in three to four different channels. Less than 10% of consumers exclusively buy candy online, but a third said they buy in-store and online.
Social presence. Candy consumers are active on social media, with nearly 60% of consumers surveyed in the NCA study saying they access their networks for inspiration on products to buy or use with recipes, and to simply engage with the brand. Candy brands are increasingly leveraging social media platforms and partnering with influencers to expand reach and engage with their target audiences.
Considering these trends, candy brands have a lot of shifting behaviors to wade through. However, this is where predictive analytics, AI, and machine learning can help them figure out which trends to pursue, at which retailers and in what ways. Brands can develop smarter strategies around pricing, promotions, and where to put products at checkout and in the candy aisle.
Brands can feed AI-powered engines a mountain of varying data: social listening, POS, shipment data, third-party global trend forecasts, loyalty information and more. The AI model reads the data and directives from the brand teams on price elasticity, promotions strategies, assortment optimization and other inputs to recommend decisions for their brand goals and category growth overall.
Let’s repeat that last part: the insights help arm a brand with the knowledge that can lift an entire category for a retailer, earning them category advisor roles at coveted retailers.
Sweeten sales for retail partners
As noted from the NCA data earlier, most consumers still rely on the checkout lanes for their impulse candy purchases. However, the data also states nearly 80% frequent the candy aisle, where retailers have been expanding assortments to bring more excitement to the category.
Major players like Walmart and Kroger have constructed expansive in-aisle sets for candy that push the retailers to become candy destinations, perhaps challenging c-stores and drugstores that have been often associated as a primary purchase destination for the category.
Part of this pivot from large format retailers is also to compete with value chains and general merchandise retailers also carrying candy. What’s more, the consumer behaviors around candy are much more than the impulse buy at checkout. Consumers are adding candy to their shopping lists as more wholesome ingredients make it a more acceptable indulgent treat.
Candy brands can help retailers make sense of consumer behavior changes by bringing AI-powered, robust data-driven insights such as:
Should chocolate continue to receive the amount of space it’s getting based on its space elasticity?
Is there room for expandable consumption inside stores, meaning can the store offer more candy even when they don’t need it, lifting a retailer’s bottom line?
How much play should mini-size packages get, and should they be in bulk packages for consumers buying for extended at-home consumption?
Fine-tuned predictive analytics can answer these questions, helping brands develop the right products for their company’s success and sweeten sales for their retailer partners.
AI-powered platforms can change how candy brands work with retail partners, elevating a category from checkout lane to major players with grand merchandising sets and powerful growth strategies.
Dig deep with data
In today’s dynamic and highly competitive market, candy brands are constantly seeking innovative ways to stay ahead. With predictive data, brands can accurately forecast consumer demand, anticipate market trends and tailor their assortments accordingly. Not only does this enhance profitability but it fosters a more personalized and satisfying experience for candy enthusiasts.
AI-powered platforms can change how candy brands work with retail partners, elevating a category from checkout lane to major players with grand merchandising sets and powerful growth strategies.
Accelerate Your Sales, Revenue Growth, and Category Management Initiatives
Groceryshop | September 19-21, 2023 | Mandalay Bay, Las Vegas
Connect with Insite AI at Groceryshop and find out how our revolutionary approach can accelerate your top initiatives. Our team of AI and strategic consulting teams have walked in your shoes, giving them unparalleled insights into your industry-specific hurdles. Our Strategic Advisors are consumer brand and retail veterans from Coca-Cola, PepsiCo, Mars, Anheuser-Busch InBev, Walmart, Target, 7-Eleven, Kroger, among dozens of others.
Let us guide you in tackling your organization’s distinct challenges head-on. Through our collaborative approach, we craft a tailored solution to elevate your product assortment, pricing strategies, trade promotions, and demand forecasting.
Don’t miss this opportunity to expedite your success and lead your organization toward a more efficient and profitable future.
Former SVP of Merchandising at 7-Eleven, Brooke brings nearly 20 years of grocery and convenience retail experience to Insite AI. She understands what it takes to build valuable partnerships with retailers, and in her role as EVP of Strategy Consulting, she advises consumer brands on ways to elevate strategic business planning, achieve category leadership, and create optimal shopping experiences for their consumers.
EVP, Strategy Consulting
Former leader at Coca-Cola, Dr Pepper Snapple, and Delhaize, Capri brings extensive strategic leadership experience from both retail and supplier roles in the consumer goods industry. She was recognized as a Senior-Level Top Woman in Convenience in 2022 and has also received recognition for her leadership in collaborative/joint business planning with top retailers across multiple channels and formats.
EVP, Strategy Consulting
Kristine is a highly accomplished retail executive and former VP of Merchandising at Walmart. Kristine led strategic initiatives that resulted in substantial revenue growth for the company across Grocery and prior to that Personal Care. Widely recognized as a visionary leader, she played a pivotal role in optimizing Walmart’s merchandising with large CPGs.
Why Insite AI?
A Consultative Approach
Our team becomes an extension of your team. Our Strategic Advisors are consumer brand and retail veterans from PepsiCo, Mars, Anheuser-Busch InBev, Walmart, Target, 7-Eleven, Kroger, among dozens of others. Our top priority is ensuring you have the guidance and support you need to achieve your goals and maximize the value of your investment.
Everyone else starts from scratch, yet Insite AI has already invested over eight figures of capital and several years into building leading edge technology; creating unmatched advantages for tackling your top initiatives.
We deeply tailor our engagements and fully configure our solutions to meet the unique needs of your brand. Insite AI is a true innovation partner providing CPGs with fully customizable solutions built to solve their unique challenges, enabling them to adapt quickly to changing market conditions and outperform their competition.
Do not report the news. Simply reporting out category performance as up or down in volume and dollars vs year ago is ‘news,’ not insights.
In the dynamic world of retail, collaboration is key to success. During a recent panel discussion, Mastering Joint Business Planning: An Insider’s Guide, we sat down with a former VP of Sales at Coca-Cola, Capri Brixey, and a former VP of Merchandising at Walmart, Kristine Joji, to share their experience and insights into what makes a successful JBP.
Below are some key “do’s” and “don’ts”—both practical and technical—that they shared, which can help CPGs master JBP scenarios, improve your retail partnerships, and grow your mutual profitability:
1. Understand the retailer’s plan
Entering a planning session with just the CPG’s agenda can quickly derail a conversation and lead to an unproductive meeting. Bringing a true desire to understand both parties’ needs (and being equipped for effective discovery to that end), CPGs can ensure that their own plans align with the retailer’s strategy and priorities.
2. Use credible insights
Do not report the news. Simply reporting out category performance as up or down in volume and dollars vs year ago is ‘news,’ not insights. Data is just data. Retailers need to understand the why and the what. Indicate what happened, why it happened and what should be done next. Anyone can pull a report. The beauty is in taking numbers, overlaying and integrating insights, trends, data and analytics and helping people understand what happened and what is happening so they can create meaningful action for the future. Insights should be foundational to every phase of the planning process, from the beginning when both organizations are trying to understand priorities, to the end when tactics and solutions are being created to drive business.
3. Don’t always paint a rosy picture
Insights may reveal, for example, that while a product was projected to perform well and provide incrementality, instead performance was below expectations and demand transferred to another product or was cannibalizing existing items. Bringing objective, robust data and facts helps build trust and transparency. Being willing to collaboratively find mutual wins through data elevates partnership and strategic thought leadership. It shows that a CPG is data led and insights driven, that it understands the customer, environment and what is happening now.
4. Offer potential solutions
Use of AI tools allows CPGs to stitch together myriad pieces of data in real time, aligning them with trends and insights. This lets CPGs accurately tell retailers:
What their theory was.
What the data is.
What they know is really happening.
What can be done about it.
What the CPG’s recommendation is so the partners can mutually grow their business and the category.
5. Build a specific, tactical plan to deliver on what was committed
This aligned plan should be the foundation of the partnership. It should involve everything that was agreed upon, as tactical as shelf placement, pricing and promotions, or as strategic as broad expectations for overall contribution/performance and how the organizations will engage. Then, regular checkpoints should be set to ensure the strategy remains on track, with flexibility and agility to respond to events and trends in the market. Disruptions can be small or on the scale of the war in the Ukraine or Covid-19. In these types of cases, both organizations must ask—and answer—“Where are we now and how do we pivot to ensure we can still deliver our plan together?”
6. Leverage AI to run “what if” scenarios
CPGs can leverage AI to run “what if” scenarios in real time. This can foster forward thinking, collaborative conversations with retailers. Data accounts for the many moves retailers can make on their chessboard. This gives them more clarity, so they can develop rich category plans. Using technology to detail the “why” and sharing explanations also helps buyers explain decisions to their leadership teams.
7. Drive collaboration
The goal of JBP is to drive collaboration. If CPGs are not weighing mutual growth, mutual priorities and planning ahead, they can be derailed by many unforeseen events. They need to be agile. Working through the process and knowing where the finish line should be and planning towards it are key components of success.
8. Deliver a better shopping experience for consumers
Retailers want to know how their CPG partners will be more consumer centric.CPGs can create a more personalized consumer experience by leveraging advanced AI capabilities. These AI-driven assortments, pricing, and promotions empower CPGs to craft shopping experiences that not only satisfy customers but also foster long-term loyalty.
Thoroughly analyzing data reveals a predictive view of entire product categories, going beyond just looking at individual brands. A supplier that is driven by insights and data, promoting its own growth as well as that of the category and the entire industry, stands out as a clear trailblazer. These carefully obtained insights not only have weight but also solidify the supplier’s image as a strategic thought leader. Retailers will naturally lean toward their most developed partners, elevated by trust and true transparency in insights and data.
The insights shared in this article were presented at a recent panel discussion featuring Kristine Joji and Capri Brixey, EVPs of strategy consulting at Insite AI. The event was moderated by Jackie Lewis, VP of content at the Category Management Association. To view the full presentation, click here.
Winning the Retail Space War with Predictive Modeling
40% improvement in assortment trade-off accuracy
What we did
One of the largest brands in the consumables sector wanted to understand how to utilize its store space within Target for optimal results. Applying innovative AI components to develop space elasticity models, we refined the brand’s planning process with calculations and forecasting that identified how space affects profit- ability and sales demand to arrive at their ideal strategy. Insite AI become an extension of their team, providing the support and resources they needed to ensure they achieved their goals through data, adoption, and guidance.
2% increase in profit with the same amount of shelf space
We empowered the Category, Assortment, and Space planning and analytics leaders with critical insights to rapidly simulate multiple scenarios and accurately forecast effects on sales, margins, volume, and demand. Leveraging predictive modeling, our platform delivered insights for maximizing productivity and profitability so the team could determine the ideal plan for each store layout.
Reduced planning cycle time from months to days
With Insite AI, this major consumer brand quickly identified the best use of in-store space. The brand can now swiftly hone its on-shelf facings, arrangements, and structures at the planogram level and defend its plan within Target. Even with competing priorities, limited budget, and resource constraints, the company priori- tized working with Insite AI. This technology has been identified as mission-critical at the executive level and the team members involved have received recognition internally for their efforts.
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One of the Largest Consumer Brands Achieves Category Leadership at Walmart
Became category leader at the world’s largest retailer
What we did
One of the world’s largest brands in the consumables area wanted to elevate its category advisement at Walmart. Applying powerful predictive and AI components across multiple data sources, we enriched and accelerated the brand’s planning and decision-making processes to present Walmart with the best assortments at a planogram level for all 4,600 stores.
Reduced planning cycle time from months to days
We deployed assortment capabilities in the brand’s cloud environment to ensure data never left. Merging multiple data sources, our platform delivered insights on demand transference so the team could understand the incrementality associated with product additions, deletions, and resulting effects on demand.
5-15% sales improvement
With Insite AI, this major consumer brand developed very clear forecasts on how their category—and others in the category—are performing at a planogram level within Walmart. The brand can now create multiple assortments within seconds and recommend the best one. As a result of their adoption of AI, they have delivered a better shopping experi- ence for their consumers, growing their joint profit pool, and achieving category leadership. They are now expanding into other retailers.
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Tough Questions to Answer If You Want Category Captaincy
Retailers expect more than ever from their CPG partners as they face growing shopping challenges, keeping up with consumer demand, and adjusting to ever-evolving trends. If you want the ever-valuable category captaincy, be prepared to answer these questions.
If You Want Category Captaincy, Prepare to Answer These Tough Questions from Retailers
As retailers face growing challenges, keeping up with demand, and adjusting with ever-evolving trends, they’re starting to question the role of their category captains. These people or teams have traditionally assisted retail buying departments, acting as unbiased analysts who worked to deliver the retailer’s goal for the category. Mike Gervasio, President of Category Leadership at PepsiCo and Chairman of the Category Management Association, was quoted in Retail Wire as saying, “It took the pandemic to really shake the behavior of the CPG industry; there’s entirely new problems to be solved.” He said that the industry has been accelerated by 5 years in just a matter of months and that companies have to acquire new sets of data and tools in order to deal with new challenges.
Against the shifting backdrop of consumer behavior, retailers have a real need for a different kind of category captaincy from their CPGs in order to keep them onside. CPG leaders need to prepare for these tough questions from retailers.
Is Your CPG Prepared for These Retailer Questions?
How can we grow the joint profit pool?
Relations between CPGs and their retail partners have fallen to their lowest levels in 5 years according to Bain & Company (2021). However, a well devised joint business plan can deliver more than 10% of incremental profit pool growth for both parties in a single year, helping to strengthen relations.
How can CPGs help us to glean better insights from our mass of data?
Whilst retailers sit on huge amounts of EPOS and loyalty card data, they are not as advanced when it comes to AI, data, and analytics. In return for closer collaboration, there is an opportunity for CPGs to use AI platforms to add value for both parties at a much more granular level to grow the joint profit pool.
How do we get to grips with category management for e-commerce channels?
Retailers are having a tough time adapting to e-commerce, curbside delivery, and marketplaces where category management becomes even more complex. In theory, online sales could give consumers access to endless long-tail choices, but at the same time this creates a logistical nightmare. Retailers need support on how to optimize choices when it comes to assortment and pricing for the online world whilst meeting customer needs.
How can you help us to make assortment adjustments faster and in a more agile way?
Retailers are working to adapt their offers and store formats quickly as the trend toward smaller store formats and neighborhood markets means difficult choices need to be made. How much space should be allocated per category? How can we get the most out of everyinch of that space? Retailers and CPGs need the ability to make assortment decisions in real time. Waiting for annual or bi-annual reviews means potential revenue is leaking away.
How do we ensure the category is managed properly?
When one CPG is the captain of a category in a key retail account, there is always the question of how impartial their recommendations are. AI and machine learning can support CPGs with business case modelling so category decisions are transparent and scientific.
How do we deal with such high levels of product innovation?
Record numbers of product innovations are launched every week. New categories, brand extensions, and even new flavor or fragrance variants mean there’s no shortage of variety. Meanwhile, shelf space is shrinking. Retailers need assistance to model every change made on the shelf to make sure they can maximize revenue.
We how can we localize our assortments at scale?
Over the years, retailers have become better with store clustering and assortment localization. But many want to take their assortments to the next level, delivering even more value to shoppers based on local needs, preferences, cultural differences, and even price elasticity. This is an area where technology can help.
You want to raise your prices, but can you help us understand price elasticity?
One of the biggest tensions between retailers and CPGs is price increases. As a CPG, you face pressures on cost of goods, logistics, and marketing. Meanwhile, retailers want to protect their value proposition and price perception. You can help retailers understand price elasticity down to individual store level using a platform like Insite AI.
Can you help us to develop new store formats and optimize the space?
Spacial optimization is key, especially with increasing smaller store formats where every inch needs to count. Add value for the retailer by helping them understand the spacial elasticity of your products. Prove to them the profit opportunity of allocating additional facings to your SKUs.
Shoppers only buy your products when they are on promotion – Help!
Getting pricing right from the start is crucial. Some products are priced too high, so they tend to only generate volume when on promotion. Likewise, a low everyday price that’s too low means that promotions erode margins even further. Use technology to optimize pricing and understand the demand transfer that happens when prices go up and down. Create appropriate promotional strategies accordingly for the optimal revenue outcome.
Funding Incremental Growth With AI
Selecting the right AI solutions to for your category, pricing, and assortment decisions can reduce inventory costs, improve forecast accuracy, and enhance the customer experience. By leveraging these solutions, CPGs can fund incremental growth and achieve their business objectives.
How to Choose an AI Solution for Pricing and Assortment Optimization
Choosing the right solution for critical assortment and pricing decisions means a CPG must practice a lot of due diligence to find the right fit. Having worked across CPGs and teams at all levels, from the c-suite to VPs and category managers, here are some of the questions you should be asking as you evaluate a data science, analytics, or AI-based solution:
Protect the IP that is the heart of your CPG’s strategic competitive advantage
There is nothing more precious than the capabilities, knowledge, and unique intellectual property that’s been crafted over decades (or even hundreds of years in some cases). You want to be sure that any analytics, data-science, or AI-powered solution is going to protect the integrity of these hard-won trade secrets. Therefore, choose a solution that sits within your own private cloud, where no data, learnings, or proprietary information is ever going to leave the organization.
Choose a solution built for CPGs and Consumer Brands
AI is often misunderstood. Some of the world’s largest software companies have promised it as being the remedy to an endless number of business challenges. While some of that might be true, they haven’t always done a good job of explaining what AI or data science actually means for specific business functions in a tangible, applied way. Some promote an AI or data science platform that ends up being completely generic – these solutions are often sold as solving any type of business problem. But, we’re often shown that being all things to everyone makes a master of none. Software and technology without consulting is just a tool, and that tool often ends up being challenging to use and without the promised results. Rather, it’s important to look for a purpose-built solution that’s able to be customized for each unique business case, that serves specific needs, and is able to be intentionally constructed to solve CPG-focused assortment, pricing, demand, and category management challenges.
Think about the importance of solving specific problems instead buying a piece of technology
Start with your specific business problems and translate those into a custom solution that works for stakeholders across your enterprise. This allows for a bespoke solution to be built for individual needs, rather than trying to solve individual problems with a broad solution. CPGs may operate in the same industry, but their IP, modes of operation, and go-to-market strategies vary wildly. Solving big, unique problems is never going to be about buying a piece of technology or a solution that works right out of the box. Instead, look for an AI company whose domain experts will get to know your CPG’s business, its unique challenges, and how best to solve them. Then, get those experts to build a custom solution to do the job by producing desired outcomes.
A harmonious tale: Strengthening the retailer-CPG relationship
Ryan Powell, SVP retail strategy and consulting at Insite AI, explains why the relationship between retailers and CPG brands goes beyond breaking silos of data and understanding each other’ strategies. Success is tied to collaborative planning processes as if they were a single entity.
For decades, the relationship between retailers and their CPG brands have been a critical, albeit complex one to navigate. Both share mirrored desires to remain competitive, capture consumer loyalty and spend, and drive greater market share.
At the same time, they both face very similar challenges from increasing cost pressures, defense against new entrants, the rise of direct to consumer marketing, and ever-evolving consumer demands.
But the two are often at odds with different business objectives and goals, especially when it comes to pricing, and they have historically remained distinct in their pricing strategies. According to a report by Bain & Company, relations between the two actually fell to their lowest level within the past five years in 2021, mainly driven by approaches that favored short-term sales.
The fact is, though, that there’s a huge opportunity for both parties to work more closely together, break down those detrimental silos, and ultimately increase profitability for all. With record numbers of new categories and brand extensions launched every week, pressures from online shopping, and ever-shrinking shelf space, making smarter choices for in-store together will be imperative for success moving forward.
Considering CPGs and retailers have monthly, quarterly, and annual revenue and profit targets to hit — plus shareholders and stakeholders to satisfy — it’s important to acknowledge that delivering a joint business plan wouldn’t necessarily be a simple, quick fix. It requires bold leaders from both sides prepared to invest time and energy in order to properly execute against this sort of strategy. For those willing to make this change though, the benefits could be significant. In fact, that same Bain report cited a more than 10% increase of incremental profit pool growth in just one year if retailers and CPGs build intelligent and well-devised, joint business plans.
So, where to start?
Establishing trust and transparency
The strongest relationships are built between people, and although written business plans and agreements are necessary, the most important investment is establishing the utmost trust, transparency, and rapport with all involved retail and CPG parties. This isn’t just limited to C-suite executives or VPs. In fact, it is even more important that the people who will actually deliver the day-to-day execution like category managers, buyers, and shopper marketing directors trust one another and recognize they are working collaboratively for a common business goal. This, in turn, requires conversations around, and deep understanding of, each other’s needs and goals: What does success look like? How are they being appraised? Aligning on these points up front is key to successful collaboration.
Another success factor is the use of data. Both retailers and CPGs have access to unique data sets that, if combined, could change course for their businesses. Retailers are typically armed with incredible intelligence and analyses around shopper behaviors and engagement through Electronic Point of Sale, loyalty card, and large amounts of consumer data.
On the flip side, CPGs have much more granular figures and expertise surrounding their specific brands and overall categories (i.e., factors like pricing, assortment, and space optimization). Many CPGs also have greater capabilities when it comes to AI, ML, and analytics that help improve forecasts, recommendations, and decision-making to provide enormous value for the retailers.
As part of this though, trusting CPGs data’s accuracy and value and demonstrating a willingness to use it will be the first step in driving paired success.
Those who plan together, stay together
Moving forward to satisfy the consumer goes beyond breaking siloes of data and understanding each other’s strategies, or even discussing mid- and long-term goals. For success it is critical for retailers and CPGs to actually conduct their planning processes together as if they were a single entity — particularly focused on category planning.
Sure, CPGs could very well grow specific brands and drive that short-term success for their retailers on their own, but true long-term success requires strategic initiatives and decision-making centered around entire category growth, building strategies that are right for the retailer’s DNA and for the consumers that shop there.
One way to achieve this is for CPGs and retailers to work cohesively in the same platforms to co-develop the numbers, projects, predictions and co-manage the data. Through greater collaboration at the planning stage and increased transparency the two can more effectively and efficiently ensure true optimization of assortment, pricing, and shelf space, and make sure consumers get the value they need.
Knowing your work isn’t done
Above all, one of the most important things for CPGs and retailers to keep in mind once they’ve implemented this connected approach is to remain continuously innovative. Considering how volatile the retail industry is and every variable involved, remaining stagnant or complacent in tactics is a recipe for disaster. Being inquisitive and consistently asking questions, analyzing data through different lenses, introducing new data sets into ecosystems, and having a real-time understanding of customer sentiment and trends will be essential in staying agile, smart, and one step ahead against other industry players.
While this collaborative approach appears a daunting task, one that will require unprecedented levels of cooperation and even change management, the potential for market success makes the effort well worth it. By working in true partnership, retailers and CPGs have the greater potential to strengthen profit margins, shopper relationships, and overall success. As the pandemic rages on across the globe and disrupts previous operations, alters consumer behaviors, and challenges retail and CPG execution more than ever before — taking the leap of collaboration could prove more beneficial not only now, but in the many years to come.
Ryan Powell is SVP retail strategy and consulting at Insite AI
There have never been more choices available for consumers, which leads to massive challenges for category and assortment managers. Which means being able to predict what happens when product change decisions are made is critical.
How to Avoid Disastrous Category Management and Assortment Decisions
Category management as a discipline started to become popular in the 1980s. Fast forward to 2021, and there’s never been more choice for consumers, creating even more of a category challenge for both CPGs brands and retailers.
The number of SKUs in a given category has exploded, particularly over the last 10 years. According to Nielsen, there are 58% more baby food SKUs, with up to 300 for the largest assortments. Similarly, there are +81% coffee SKUS and +42% in healthcare.
There are new products coming into the market all the time, and making the wrong SKU rationalization decisions can be disastrous for a CPG. For the retailers carrying your products, it’s a complex situation. They want to integrate new products into their assortment, sometimes whilst maintaining the same or shrinking available shelf space. Removing a product can have unintended consequences and can lead previously-loyal shoppers of that product to ditch your entire brand for your competitor, or even leave the retailer entirely.
A retail category manager might choose to remove an obscure, low-margin, and slow-selling product variety – logic often dictates that’s the right thing to do. But that item could be the reason that some of the store’s most profitable customers visit in the first place.
One of the dangers of traditional category management for both brand and retailer is that decisions are made in a simplistic manner by looking at metrics like sell through and margin, but without looking at the assortment from a shopper’s perspective. Then there’s the highly complex task of looking at the store holistically and getting to a granular understanding of how a single change in one category can affect the performance of multiple others. Simultaneously, shopper segmentation and profiling is becoming more complex, as are their tastes, preferences, and behaviors.
It’s becoming clearer all the time that, for many established CPGs and retailers, decades-old approaches are still being used to make critical assortment decisions. Often these decisions use primarily historical data, which in today’s faster-and-faster-moving environment, is like looking in a rearview mirror.
Instead of looking back, the top CPGs use all available data, analyze it in real time, and then make well-founded decisions on which moves to make by being able to accurately predict the effects of change on sales, margins, and revenue. Understanding how categories work together and how changes to them impact consumer behavior and satisfaction are the keys to category and assortment success. Not only will your CPG come out ahead, but accurate forecasts that present the most compelling business case to your retailers and channel partners will build and strengthen hard-won, long-term relationships. Simultaneously, you’ll be able to hone in on optimal plans forpricing and promotions and know which marketing levers to pull in order to grow your market share in the respective category.
Talk to the category management experts at Insite AI to learn how our solution will give you the edge you need.