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
Analytics
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
Results
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.
Contact Us
"*" indicates required fields
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.
3 Ways CPGs Use AI to Increase ROI
Every CPG strives to maximize its return on the money and effort it places into investments. The question is:
Which parts of these investments will drive the biggest and most certain returns?
Optimized category management, assortment planning, and revenue growth management are the key factors to success, profits, and market share.
Don’t take chances on your success – using artificial intelligence to make decisions ensures optimal outcomes. Here’s how CPGs are using it:
1. Category Management
Spend precious technology and data dollars on the product most likely to help you succeed. This means using a solution that continually monitors and uses data to create all outcome scenarios possible.
These scenarios use past, present, and future-possible data to show you and your retail partners which products should be on shelves and at what price.
Key benefits of AI-driven forecasting in category and assortment:
Selling the right quantity of product that accounts for upcoming sales, trends, advantage over competitors, and promotions
Better optimization of assortment ratios
Improved understanding of demand drivers and customer behavior, right down to the SKU level
Decreased lost sales / missed sales opportunities
Better alignment between products and locations where demand exists
Improved GMROI
An AI-based forecasting system, is a focused on the CPG major upgrade to existing systems where brands attempt to manually cluster and define data and patterns. Unsurprisingly, results are often disappointing and lead to lost sales and market share.
Store-level forecasting is a difficult endeavour with traditional systems, especially when CPGs are dealing with millions of possible product, price, and store combinations.
By alleviating the need for so much manual intervention and by accounting for so much information at any given time, artificial intelligence-based forecasting can deliver far more accurate decisions.
2. Revenue Growth Management
Advanced forecasting combines with historic sales with seasonality, trends, product lifecycle effects, and statistically-tested assumptions to improve accuracy. Increased accuracy is the single biggest driver of direct savings, revenue, and total return on investment. Improvements to revenue growth management will be realised in the following ways:
Customized decisions for granular levels such as individual store, SKU, particular time, price elasticity, and demand changes
Making optimal pricing decisions to make you more money and take market share away from your competitors
Opportunity for improved use of strategic discounting
3. Operational Efficiency
In the face of increasing competition, CPGs are all looking to ensure their products remain a focus over their competitors, and that their retail accounts keep them top of mind.
More accurate simulations for decisions can help CPGs optimize category, assortment, trade fund, and pricing/promotion. This is while ensuring they’re able to offer retailer partners the right discounts and provide exact pricing recommendations for optimal outcomes on either side. It’s important that assortment is accurate at individual store levels, using both micro and macro views for trends, seasons, demand, and changes to ensure customer demands are being served at a granular level. Product imbalances often occur right after seasonal peaks. One of the biggest reasons CPGs fall into this trap is because they’re often forced to act retroactively with top-up orders, transfers, or pricing changes. Providers such as Insite AI provide highly accurate, data-driven scenario decisions at store levels ahead of time to keep ahead of competitors.
Contact Us to found out how you can increase ROI with the power of AI.
Manage Consent
To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions.
Functional
Always active
The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network.
Preferences
The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user.
Statistics
The technical storage or access that is used exclusively for statistical purposes.The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.
Marketing
The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes.
