Taming the Data Tsunami for Better, Faster Decision Making

Winning the Retail Space War with Predictive Modeling

One of the Largest Consumer Brands Achieves Category Leadership at Walmart

Tapping Real-Time Market Data and Performance Forecasts to Pick the Next Winners

How Brokers Can Lead the Way in AI Adoption

Positioned between brands and retailers, brokers can leverage AI and precise data to find a common truth — and pave the way for CPGs to adopt AI 

Brokers play a crucial role in the CPG and retailer community. They possess extensive knowledge of the market and categories across every store, including consumer preferences, trends, and pricing dynamics. Brokers effectively represent brands and lead as strategic partners in navigating the retail industry. Leveraging their expertise, brokers help retailers streamline their supply chains, expand their product offerings, and ultimately enhance customer satisfaction. Their ability to effectively bridge the gap between suppliers and retailers as a total solution makes brokers essential in optimizing retail operations and driving business growth.

By sitting between the CPG and the retailer, brokers hold a unique position, with an opportunity, or even a responsibility, to become leaders in how CPGs of all sizes adopt AI. The technology is currently in its infancy for effective adoption, with limited clarity on exactly how CPGs will allow AI to change ways of working. However, brokers can shape the ways this technology creates efficiencies, reduces the digital overload, and pioneers its broad application to the industry overall. In doing so, they differentiate themselves and fulfill their promises to their CPG partners in helping them gain a competitive edge in this dynamic retail landscape. 

Through business intelligence and predictive analytics, brokers can ascend to new heights among CPG partners. They can also strengthen their standing among retailer partners. Moreover, brokers can be a bridge between both, using high-powered AI to uncover common data truths and drive growth across the store.

Here are top ways brokers can lead the way in AI:

1. Present Accurate Demand Planning and Predictive Market Analytics

In 2023, retail sales are expected to grow more than 4%, generating nearly $5.23 trillion, according to the National Retail Federation. NRF also said more than 70% of those sales will be inside physical stores.

How close to reality will that forecast of 4% growth turn out to be? Brokers can provide a precise view of what’s happening in the market and what is likely to happen through AI-powered demand planning and market-level trend forecasts. These data and insights help inform forecasting from the highest level. Brokers can help predict future buying behavior across channels and subcategories. They can inform retailers of trends and shifts in the marketplace, and they can provide the most granular store-level view into inventory and click-and-collect service. All of these efforts, powered by AI, continuously learn, adapt, and create an enterprise environment enabling strategic decision-making, rather than an increased digital workload. Brokers can become a single source of truth in developing a precise view of enterprise market and demand planning.

2. Assist With Store Execution and Assortment

At a store-by-store level, across retail channels, brokers can leverage AI to customize insights for CPGs in any category. AI can be custom-tailored to each of the brands with which brokers work, to build the most impactful product mix and decision-enabled portfolio. 

Further, they have the unique perspective of working with brands at all points in their journey of scaling and growth. For larger brands, some brokers have a responsibility to effectively build a mature portfolio with multiple opportunities in the retail environment. In that role, they fill gaps where large CPGs lack visibility and provide solutions where larger CPGs cannot internally manage the need for additional capabilities. For emerging, growth, and niche brands, brokers have a different, more targeted set of responsibilities to deliver that those brands might not be able to generate themselves. 

All brands are looking to achieve category thought leadership and mutual growth with retailers they serve. AI application to assortment optimization, demand transference, and predictive analytics can help them achieve a greater share of the category and effective increases in visual inventory. Smaller brands aiming to get a stronger foothold in a category can tap into brokers and their ability to lead with AI-driven insights to bring retailers data-informed strategies on how they’ll grow a category overall.

3. Optimize Promotions and Trade

Even without a robust services suite, as sales partners to CPG brands, brokers, enabled by AI, can boost acumen in understanding elasticities of price, space, and market. AI modeling shows how the interconnected dynamics in availability, leakage, allocated category space, pricing and promotions impact sales and profitability. 

Brokers that embrace this technology will lead by using learning models to predict the most effective promotional outcomes, optimized for their partners’ established goals and the current macroeconomic environment. 

The technology allows for actionable insights on how to execute the best overall plan, and the best use of promotions, in the most impactful locations, and in the most deserving regions. The technology backs brokers with the unique and differentiating capability to plan efficiently as partners and lead with the optimization of portfolios, brands, and categories, in ways CPGs are currently not leveraging themselves. Brokers can align a pricing strategy that maximizes sales, revenue, and profits for their partners.

4. Become a Bridge to a Common Truth

Possibly the greatest strength a broker can leverage through AI is an ability to lead the data capabilities that solve problems and enable more efficiencies for CPG clients, in addition to relieving their own ‘digital debt’ that continues to grow for the industry overall.

Digital debt is costing us innovation. According to a recent Microsoft study, 64% of people struggle with finding time and energy to get their work done, and those workers are 3.5x more likely to say they struggle with innovation. 

Common truth, or insights driven by the integration of multiple sources of data, narrow the focus to that with the greatest impact on the outcome. And those that excel at — or adopt these integrated models to find the common truth — will be the bridge-builders and the leaders in the industry. This becomes a powerful position for brokers, solidifying them as intelligence-driven category advisors.

Brokers have a tremendous opportunity to enhance their offerings to CPGs through the adoption of AI. AI and machine learning solutions can enable brokers to analyze vast amounts of data, including market trends, consumer behavior, and competitor insights down to the store level. By harnessing these insights, brokers can further establish themselves as thought leaders and strategic advisors, providing CPGs with valuable market intelligence, helping them to be more agile, make more data-driven decisions, and outpace the competition.

For more on how Insite AI can help brokers become innovation leaders in the industry, contact us here.

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:

1. 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.

2. 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.

Another Summer of Hard Seltzer?

How you can leverage AI to identify your top performers and revamp your product portfolio

In today’s highly competitive market, it is more important than ever for businesses to continuously analyze and optimize their product portfolios to stay ahead of the game. With the help of AI and predictive analytics, companies can gain valuable insights into their product performance and make data-driven decisions about which products to keep, which to improve, and which to remove from their portfolio.

In this blog, we will explore how AI can help you identify your top-performing products and eliminate the underperformers, using the example of the hard seltzer craze to illustrate the importance of portfolio rationalization in the ever-evolving landscape of the alcoholic beverage industry.

Hard Seltzers Won’t Fizzle Out

A category that got its mainstream footing just a few years ago, with early days powered by brand darlings like Truly (Boston Beer Company) and White Claw (Mark Anthony Brands), hard seltzers are credited with driving overall category growth. With last year’s off-premises sales increasing a whopping $900 million — quadrupling year-over-year — it’s hard to believe that at the start of 2018, just 10 hard seltzer brands were on the market.

Since then, more than 65 brands have entered the space, which continues to grow at a rapid pace, most recently enjoying a 33% increase in sales earlier this year (January – April 2021) versus the same period in 2020. This explosive growth has accelerated the sub-category from new entrant to what’s now becoming a mature mainstay.

While the growth of hard seltzers is starting to stabilize, we can expect to see on-premises sales continue to be a boon to the sub-category’s ongoing evolution as bars and restaurants welcome back patrons. For brand leaders, this means shifting strategies to plan for and accommodate changing consumption behaviors.

Another factor to account for in assortment planning is consumer preferences and flavor profile trends, which will drive category dominance and innovation as hard seltzers themselves become less of a novelty. Today, citrus- and raspberry-flavored hard seltzers prove most fruitful in sales, whereas blueberry does not fare as well.

Ready-to-drink (RTD) and Canned Cocktails

Ready-to-drink cocktails: Ready-to-drink (RTD) cocktails have been growing in popularity in recent years, particularly in the canned format. RTD cocktails are pre-mixed and often packaged in convenient, portable cans or bottles, making them a popular choice for outdoor events and activities.

The canned cocktail trend has been gaining popularity in the US in recent years, as consumers look for convenient and portable options for their summer drinks. Canned cocktails are pre-mixed, ready-to-drink cocktails that are packaged in cans and sold in packs. They offer a convenient alternative to traditional cocktails, which can be time-consuming and require multiple ingredients and equipment.

One of the main advantages of canned cocktails is their convenience. They can be easily transported to outdoor activities such as picnics, concerts, and beach trips, making them a popular choice for summer events. They are also easy to store and serve, requiring no additional mixing or preparation.

Canned cocktails are available in a wide variety of flavors and styles, from classic options like margaritas and mojitos to more innovative and creative combinations. Many brands are also emphasizing the quality of their ingredients and the use of premium spirits to appeal to discerning consumers.

Overall, the canned cocktail trend is expected to continue to grow in popularity, as consumers seek out convenient and high-quality options for their summer drinks.

Beer Will Begin to Bounce Back

While the early part of 2021 (January – April) saw certain segments of beer sales decline, including craft beers, which saw a 1% year-over-year drop, we will see some segment growth return. For premium beers, markets like Denver, Little Rock and Houston have all delivered segment growth, which underscores the importance of localizing assortment plans to maximize potential pockets of development.

Other category sub-segments, including hard tea and ciders, do not show as much promise for the short-term, coming off annual sales declines of 3% and 4% respectively.

‘Healthy Choices’ Rule

In this age of information, today’s knowledgeable consumer is increasingly mindful of what they are putting into their bodies (and mouths). Newer generational values of millennials and Gen-Zers who are coming of drinking age are focused on wellness — one reason hard seltzers, with lower calories often touted as a brand benefit, have performed so well.

One newer sub-segment marketed as a “healthy” option that is showing tremendous potential for continued growth is hard kombucha. According to Kombucha Brewers International, hard kombucha sales grew from $1.7 million in 2017 to more than $12 million in 2019, and Insite AI data indicates an 85% year-over-year increase in growth for these beverages during January through April of this year.

The fermented tea has been compared to light beer in terms of taste, but like hard seltzers that showcase fewer calories — or in the case of Vizzy hard seltzer (Molson Coors), antioxidants — hard kombucha touts its digestive benefits, an attribute that is increasingly resonating with health-conscious consumers today. Expect to see more innovation in this sub-segment, especially with major players like Anheuser-Busch InBev getting in on the action by backing the fast-growing Kombrewcha brand.

Data-Based Decisions Will Drive a Profitable Future

As America continues down its path of pandemic recovery, the alcohol category — including hard seltzer, canned cocktails, beers, flavored malt beverages and more — will continue to grow in both in-home and on-premises consumption as consumers figure out and embrace what the “new normal” is in their lives. However, after the next six to 12 months, the category will begin to see a reckoning and rebalance as long-term patterns begin to emerge.

For consumer goods brands, that means now is the time to prepare for potential shifts and to be ready to make the right decisions in category planning for future success. Brands that embrace innovative technology solutions like artificial intelligence and machine learning will be well-positioned to bullet-proof those plans, especially when they can make decisions based on predictive recommendations with granularity down to an individual SKU on a shelf in a single store location. Such decision-making power will be critical in navigating the ever-changing landscape, uncertainties like supply chain disruptions and inflation and evolving consumer behaviors.

Let us help you identify your top performers and eliminate the underperformers. Contact Insite AI today.

How Nestle-Purina and Boston Beer are Navigating the AI Journey

Presented in conjunction with the Promotion Optimization Institute.

Artificial Intelligence (AI) is the hot new thing for planning, Category Management and Revenue Growth Management.

Wherever you are a top CPG or an emerging brand, getting game-changing results takes vision, planning and the right partner.

In this panel-style session you’ll hear from two segment leaders, Nestle-Purina and Boston Beer along with AI innovator Insite AI.

They’ll talk about their visons for transforming planning and how they are navigating the AI journey. Q&A included.

Watch The Webinar

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Avoiding Disastrous Category Management & Assortment Decisions

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.

How AI Helps CPG Leaders Optimize Shelf Space

The stakes for shelf space are high, and the competition for it is fierce. Optimizing space is complex and nuanced, but using the right tools to analyze space elasticity helps CPGs win big.

Your brand of tomato ketchup – does it have a high sales velocity because of its huge on-shelf presence, or would it achieve the same sales with half the space? Does it need two facings or three? These questions have perplexed retail and brand leaders for decades. When a CPG has hundreds or even thousands of products in a single retail store, spacial decisions are crucial to maximizing sales and building brands. Position on shelf can be the difference between winning and losing, and CPGs often pay significant fees to retailers to secure prime shelf positions.

Optimizing space is complex and nuanced: too many facings could be a waste of space, whilst too few could mean risk of out-of-stocks and lost sales. There are many variables to consider when it comes to space elasticity and demand, and the top considerations are both quality and quantity of space. Space quality can include factors such as in-store location, shelf height, and which other products are in proximity. According to Nielsen, there were 20,000 new product launches in the US between 2008-2013, but 85% failed and stole spaces. In 2017, out-of-stocks led to $54 billion of missed opportunity.

So what is space elasticity exactly? Put simply, it’s the relationship between rate of sale and space allocation, but it varies across different products and categories. Elastic products show a substantial increase in sales when more space is given to them. As you allocate more space to elastic products, a point of diminishing returns is reached, where the sales increase rate drops dramatically. In contrast, inelastic products show little or no increase in sales when more space is given to them. To maximize your returns, you want to hit a sweet spot, and that can be challenging.

Optimization of this across all your SKUs can represent millions of dollars in additional revenue. With inelastic SKUs, you have the opportunity to maintain sales even after reducing footprint in store. With elastic SKUs, you want to increase their space in store to the sweet-spot point.

AI and data science are helping CPG players make these decisions fast and at scale. The right platforms incorporate spacial awareness, using computer-generated, 3D representations of stores to optimize space allocation and shelf-placement decisions. Using advanced algorithms, they crunch through millions of data points and what-if scenarios in a matter of hours, using a combination of historical sales data, EPOS data, 3rd-party data, and consumer insight data. This is done together with information about product margins and the costs of various in-store locations.

The output is tangible, optimized, go-to-market recommendations. Instead of seeing countless and meaningless possibilities, you need to get to the best decisions that will build your relationship and business case with the retailer. Further, you need to be able to understand space elasticity down to the most granular level: by SKU, by store format, andby retailer. The prize is the ability to drive millions of incremental value rapidly and at scale, driving your growth in the categories that matter.