Decoding AI for CPGs: A Path to Category Management Success

Hosted by the Category Management Association

Curious about integrating AI into your category management practices? Join us for this panel discussion with retail industry veterans and former category and sales leaders at Coca-Cola, Walmart and Nike as they discuss AI adoption in the CPG world.

Our panelists will explore critical topics such as generative AI, strategic starting points on your AI journey, and the nuances of outsourcing AI solutions. Equip yourself with the knowledge to thrive in an AI-driven marketplace and stay ahead of the curve.

• Identify the best opportunities for AI integration in your category management practices
• What to look for in an AI partner and how to identify AI white washing
• Receive expert guidance on where and how to initiate your AI journey, tailored specifically for CPG companies.
• Benefits and challenges of outsourcing AI talent.
• Explore the potential of generative AI for CPGs

Get actionable steps and practical advice on how to execute an AI project, both with partners and gain alignment and support internally. Gain clarity and confidence in embracing AI to outpace your competitors in the dynamic CPG landscape.

Presented by:

• Capri Brixey, EVP, Strategy Consulting at Insite AI
• Kristine Joji, EVP, Strategy Consulting at Insite AI
• Marsha Shapiro, SVP of Client Solutions at Insite AI

How Retailers Can Work With Consumer Brands To Fit Their Private Label Strategies

In this StoreBrands guest post, we explore how retailers can collaborate with consumer brands using predictive analytics to customize assortments, optimize shelf sets, and predict sales trends. Private label sales are growing, and by leveraging AI-driven insights, retailers and consumer brands can work together to build assortments that align with shopper preferences, enhancing the overall shopping experience and boosting category sales.

Decoding Walmart Luminate: Leveraging Predictive Analytics for Success

Anything new takes some getting used to, and a new data engine is no different — especially one as robust as Walmart Luminate.

In March, Walmart will officially transition consumer goods partners into its tiered Walmart Luminate data platform, and supplier partners will need to adjust to this next-generation program. As I wrote earlier, Walmart Luminate is truly game-changing, providing an unprecedented look into the shopping behaviors of more than 140 million households, plus never-before-shared online pickup and delivery data. With Walmart Luminate, brands have access to a level of reporting to grow their businesses in ways they never could before.

Of course, managing and understanding data as complex and revolutionary as what’s inside Walmart Luminate takes time to grasp. AI and predictive analytics can support brands by harmonizing the data and turning findings into actionable outcomes.

Here’s a look at how predictive analytics and our CPG-tailored AI expertise can assist brands using Walmart Luminate.

Supporting brands using Walmart Luminate

Walmart began rolling out Walmart Luminate to brands this fall, providing some CPGs a trial in how they might to use the data, particularly the Charter version of the program (see below summary of the data plans).

Walmart Luminate Charter is the paid tier. It gives brands complete access to shopper behavior data from millions of households, including loyalty data and custom reports on brand-switching behaviors. The full package also debuts behavioral insights on pickup and delivery, and shares robust scoring and recommendations from the Supplier Quality Excellence Program (SQEP). As part of SQEP, all Walmart suppliers are scored based on the condition of packages, pallets and products shipped to their distribution centers, for example. Charter delivers in-depth metrics on how the supplier is performing in those areas. It also has historical data and custom reporting capabilities that’s not available in the basic versions.

Brands that pay for the full service receive an exhaustive and extraordinary set of data that can seem overwhelming at first. For that reason, some CPGs will need assistance sorting it out. Insite AI’s services range from data integration and harmonization all the way to predictive analytics and scenario modeling meant to support each supplier given where you are on your individual AI journey.

Here are four ways predictive analytics and our team of engineers can help simplify the data and get more out of it:

Linking Walmart Luminate to other data-management programs.

Some CPGs may want to integrate Walmart Luminate into other data tools that they’re already comfortable working with, and our engineers can help connect the solutions. For example, a brand may want to continue using Power BI, the data visualization platform from Microsoft, but not know how to integrate Walmart Luminate into the solution. Our team can export the data and insights from Walmart Luminate and link it to a program like Power BI. Brands can get the most out of Walmart Luminate without needing to upend their data analysis habits.

Harmonizing Walmart Luminate insights with additional data sources.

Walmart Luminate provides unprecedented access to customer segmentation data and e-commerce insights, but brands still want to leverage findings from other sources such as third-party panel data, programs like 84.51, macroeconomic data and other external sources. Insite AI’s AI modeling can take the data and harmonize it into one single version of the truth. No matter the source, it’s all big data that feeds into the AI, and our solution harmonizes the information and delivers insights in a format that’s meaningful and easy to understand.

Recommending strategic actions based on the Walmart Luminate insights.

With Large Language Models (LLMS) steeped in retail knowledge, our CPG-focused AI-powered solutions and services can help explain the data. Predictive analytics and AI models can take Walmart Luminate data, create accurate forecasts on a product’s demand and explain why sales may spike or decline in the coming months. Perhaps a rise in gas prices will increase online sales of a product? AI can add a layer of “explainability” to the robust Walmart Luminate data stream. By uncovering the in-depth meaning behind the insights, you can see the trajectory of your business and discover talking points for sales and merchant teams to help drive the business forward.

Enterprise solutions tools that solve business needs within revenue growth management, assortment planning/modular planning, macro/micro space optimization, pricing, pack architecture, forecasting and strategic business planning. By leveraging AI/ML powered solutions, brands can set and visualize multiple goals and obtain proactive and prescriptive recommendations with data explainability. These solutions are embedded within your cloud so your data never leaves the safety of your environment.  Let’s say you are wanting to run TPAs (Temporary Price Adjustments) across a few brands or items to see if it will generate a lift in volume and revenue and if that lift will be maintained if you decide to make that your new retail. Our enterprise pricing tool integrates Luminate data alongside other internal and external disparate data sources and utilizes our price elasticities model, using forecasted vs historical data, generating the ideal retail price points to drive the goals of increased volume and revenue.

Walmart Luminate will be a force in 2024 as brands take advantage of the data to learn more about their shoppers and product performance online and in stores. Leveraging AI and predictive analytics, consumer goods companies can harmonize the data and get insights explained.

Whether it’s bringing expertise to sync Walmart Luminate to other internal data solutions or tailoring predictive analytics models to meet backend technical needs, we can craft custom solutions that meet a brand’s specific business goals.

Tailored to Perfection: Creating a Hyper-Local Shopping Experience with AI

Nearly 60% of consumers are more likely to shop at a store that has personalized content.

When done right, retailers can reach higher sales, volume and profit margins, as well as build customer loyalty, by localizing assortments to each store’s shopper preferences and needs. AI-powered insights will help retailers forecast demand around what shoppers are buying by each store beyond just a zip code, and identify which items will perform best, when and at which stores. CPGs that bring these insights demonstrate category thought leadership and will set themselves apart from their competition.

About the Author

Kristine Joji serves as EVP of Strategy Consulting for Insite AI. She spent 20 years at Walmart where she was recognized as a visionary leader playing a pivotal role in optimizing Walmart’s merchandising strategies.

Four Trends That Will Drive CPGs To Adopt AI in 2024

While food retailers have been actively utilizing AI to forecast shopper behavior and streamline supply chains, the adoption rate among consumer brands lags behind. In this article, we discuss four key trends that will drive CPGs to adopt AI in 2024 and beyond.

About the Author:

Brooke Hodierne serves as EVP of strategy consulting for Insite AI. She previously worked at 7-Eleven as SVP of merchandising for the leading c-store. Before joining 7-Eleven, she held multiple positions at Giant Eagle, notably as VP of own brands.

Food Navigator: Insite AI Harmonizes Retail Data Into Actionable Solutions for Brands

Insite AI leverages artificial intelligence and predictive analytics to identify actionable recommendations for brands from data insights, like those provided by Walmart’s recently upgraded Luminate data platform, which tracks the behaviors of its 180 million weekly shoppers and provides suppliers with insights into their business, including customer behavior, product performance and category trends, Kristine Joji, EVP strategy consulting, Insite AI told Food Navigator-USA.

About the Author

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.

More than Halloween: Maximizing consumer trends in candy

A recent Advantage Solutions survey of Halloween shopping habits found that more than a third of shoppers reported price as their main purchase driver—the top ranking influence within the survey.

In this article, Brooke Hodierne (former SVP of Merchandising at 7-Eleven), shares recommendations for candy brands can make more informed pricing decisions, maximize their presence in stores, and collaborate with retailers to foster continued growth in the candy category beyond Halloween.

View full article featured on Candy Industry.

About the Author

Brooke Hodierne serves as EVP of strategy consulting for Insite AI. She previously worked at 7-Eleven as SVP of merchandising for the leading c-store. Before joining 7-Eleven, she held multiple positions at Giant Eagle, notably as VP of own brands. 

CPG Matters: Providing Opportunities for Wine Brands Using Machine Learning and Predictive Analytics

With so many entities at play and data sources from retailers, distributors, third-party providers and much more, brands can leverage AI to harmonize the data and deliver recommended strategies on what wines will sell best in what regions. In addition, AI can be modeled by brand teams to factor in state regulations and insights such as product availability within the distributor networks.

View full article by Capri Brixey.

About the Author

Capri Brixey (a former VP of Sales at Coca-Cola) is currently EVP of Strategy Consulting at Insite AI, which focuses on enabling sales, revenue growth and category management for large consumer brands.  For more information, please visit www.insite.ai.

Unlocking the Full Potential of Walmart Luminate through AI

Walmart Luminate highlights what’s happened inside the store and online like never before. Insite AI emphasizes what to do next with the data.

Walmart Luminate is a game-changing data platform that shines a light into a deep, dark data void, where no CPG has had visibility before. The platform delivers shopper insights, product performance and channel data such as pickup and delivery orders across 140 million households — weekly.

The platform is revolutionizing how brands use data to reach their consumers, but Insite AI can help unlock even more potential within the data. For example, Walmart Luminate highlights what’s happened inside the store and online like never before. Insite AI emphasizes what to do next with the data. Insite AI’s machine learning and AI models provide a forward-looking tactical layer on top of the Walmart data. Brands can see how a change in pricing, promotions or pack sizes will alter their course in the marketplace.

Walmart Luminate delivers the data. We help you put it in motion.

Walmart Luminate and Insite AI at work

Having spent nearly 20 years of my career at Walmart, most recently as the VP of merchandising in dry grocery, as well as working within bakery, personal care and other categories, I have been fortunate to see Walmart pilot and cultivate the Walmart Luminate program.

I also have a tremendous amount of experience working with brands to grow and maneuver within Walmart. I mention this, because alongside Brooke Hodierne, who was SVP of merchandising at 7-Eleven, and Capri Brixey, who was a former leader at Coca-Cola, we add a human element to the numbers. We overlay business intuition and consultation as a result of our deep and diverse business backgrounds.

With that said, let’s look at some hypothetical scenarios where Walmart Luminate and Insite AI can work together to help brands get better results.

• Product innovation. A snack food brand uses Walmart Luminate to look at larger category trends and in the process identifies a competitive product making waves. The new challenger brand delivers higher protein content and is more affordable. In response, the snack food brand has decided to create a new line of products with 10 more grams of protein. Insite AI can help that brand forecast a range of scenarios on how a certain pack size would perform against that competitor. What pricing would work better? Would a specific promotion generate more sales at launch, and how will it be performing months down the line?

• Brand-switching behavior. Walmart Luminate delivers a weekly report to a detergent brand that shows the detergent was out of stock in a specific region of the country. It also shows what percentage of households switched to a new brand because of the out-of-stock product, highlights what brand the households bought and shares more in-depth analysis. Insite AI can then layer in predictive market analytics around demand forecasting in consumer segments and parts of the country to help the detergent brand see where its brand loyalty lies and how to effectively respond.

• Delivery trends. Within Walmart Luminate’s data is a look at online transactions for delivery and pickup at the store, and a beer brand, for example, can narrow in to see if there was a spike in delivery during the first Sunday of the NFL football season. What brand had the highest delivery? Which brands lagged? At what time of the day did the deliveries occur most? Insite AI can layer on the tactical to see if the trend will continue and deliver efficient forecasts on what types of promotions or moves can be made to accelerate the trend and predict when out of stocks may occur.

Factor in all the categories and shopping behaviors happening daily inside a Walmart, and the scenarios facing brands are endless. Walmart Luminate works with brands of all sizes, offering a free package with limited insights. There is a monetized version which provides customer decision trees, leakage trees and real-time insights across 140 million households.

No doubt, the data platform will grow. Insite AI will grow alongside it, working with CPGs to help solve their challenges.

Unprecedented data and insights

No other data platforms deliver a view into online delivery and pickup behaviors, giving Walmart Luminate a major competitive advantage. Before Walmart Luminate, CPGs had to rely on panel data and qualitative data sets to try and spot a trend.

But the panel data is tens of thousands of households, and the data is months old. Brands have done excellent work with panel data but it can also be tricky. The results rely on how the panel responds, and sometimes people say what they want you to hear, or the subset of people in the panel isn’t very broad, in my opinion.

Walmart Luminate offers brands data at scale, and the data presents a complete picture of shopper behaviors and households. The data withholds any identifiable information of a shopper, but it represents 140 million households across income levels and ethnicities shopping at Walmart stores. CPGs have at their fingertips truly robust data.

Insite AI can help brands take this data even further. Contact us to see how we can leverage AI and predictive analytics and help you turn insights from Walmart Luminate into immediate action.

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.

Uncover candy trends

According to a report this year from the National Confectioners Association (NCA), annual sales in both non-chocolate candies and the gum/mints categories increased by nearly 14%, comparing 2022 annual sales to 2021.

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.

Sweeten your brand’s success and elevate your brand with AI-powered insights, contact us to learn how.