Brooke Hodierne is executive vice president of strategy consulting for Insite AI, a CPG-tailored solutions and strategic advisory firm. She previously was senior vice president of merchandising for 7-Eleven and spent more than a decade with Giant Eagle.
Over the last six months, consumers, businesses and even the U.S. government have been showing an increased interest in AI and machine learning — and imaginations have run wild thinking about the future applications of this technology.
The advancements are exciting — from generative AI automating brand-new software code or writing a short story to creating video content. But it’s important, especially for those in the retail space, to not get carried away with visions of what AI can do in the future. Instead they should focus on what it can do now. And what AI can do now is grow businesses and drive increased efficiencies.
Several practical uses of AI and predictive analytics can benefit CPGs and c-stores, such as enhancing in-store space planning and allocating trade dollars. The applications may not sound as exciting as something like Coca-Cola’s awe-inspiring “Create Real Magic” campaign, where the company built a platform for consumers to create AI-powered art, but the business results can be equally magical.
For consumer brands and c-stores, seeing the potential of AI begins with demystifying the technology and understanding how it can work for their businesses.
Demystifying AI for c-stores
In the c-store space, even some of the practical uses of AI may seem too futuristic for the channel. After all, more than 60% of the c-stores in the U.S. are single-store operators, and the stores tend to have small footprints. But, when taking a step back, there’s a lot that any c-store or manufacturer can do with the technology from a practical sense.
First, to define it, AI is a set of systems or machines that can perform complex tasks that require human input. The machines don’t go rogue, but rather provide answers based on data inputs. The AI tool then delivers a machine-enhanced version of human intelligence. Think of AI as an accelerant to our human processes.
From a brand’s point of view, the AI-powered tool can think like a data analyst, running numbers and generating highly informed projections or outputs. Additionally, it continuously learns as more info gets added into the machine and gets smarter with each projection, and it can harmonize data quicker and with more accuracy.
"Retailers should ask internally what their goals are and how AI would work within the larger organization. Are there internal leaders who can back the importance of using AI, and is there talent in place who are eager to embrace AI?"
Brooke Hodierne
Executive vice president of strategy consulting for Insite AI
The difference between AI and the humans who have been analyzing data for years is that AI delivers more than an educated guess. Instead, the data and computing power offer a level of granularity that puts facts behind projections. AI will provide scoring and sensitivity to the “why” of the projection. For CPGs working with c-stores, brand teams can run an endless number of scenarios with AI that helps retailer partners grow overall categories and get smarter inside stores. Each time, the AI rigorously evaluates enormous quantities of data and delivers quick and accurate results.
Now, knowing all that, two questions should come to mind: How is this different from advanced analytics platforms that already exist, and will AI replace jobs?
- Myth: Brands and retailers don’t need AI because they already use advanced analytics platforms. Yes, there are programs like Microsoft’s Power BI that ingest data and deliver analysis and designed reports, and those programs are great. But, AI delivers forward-looking data,while other programs are focused on historical data. AI also enables an optimization and goal-seeking element. Teams can integrate AI-powered findings with other data programs for greater overall support and simultaneously continue to use programs like Power BI to build charts and reports.
- Myth: AI will replace human workers. Similarly, the power of AI is to assist teams, not replace them. Teams in departments such as category insights, revenue management and brand marketing can use AI to do the heavy lifting of analyzing numbers and free up their talent to be more innovative in how they study data and consumer behavior. AI is a tool that better educates departments across the organization and helps them make their final, more accurate decision.
Putting AI to use in the c-store channel
The convenience channel has gone through a lot of change in the last few years. High fuel prices and the black-swan event of the COVID-19 pandemic have slowed traffic to stores, inflation has impacted what consumers buy and mergers have disrupted category plans.
When faced with complex issues like these, c-stores can lean on AI to study data and recommend solutions. AI relies on first-party data such as internal sales numbers, performance data and market-share metrics, and also ingests data from third-party partners. Retailers can run their own AI programs or they can work with brands in a category captain role, running test-and-learn scenarios that set out to grow the overall category.
The data helps c-stores and collaborative brand partners in a myriad of ways, but here are three primary uses of AI:
- Assortment planning. Retailers can share sales data, loyalty data and any inputs with their AI-powered brand partners to model a recommendation of what energy drinks should go where — and in this case — grow the total category. The AI can forecast sales for the category and analyze trends to tell the retailer what brands need more space and which ones can be removed.
- Price management optimization. A candy brand can work with its c-store partner to use AI modeling to examine the price elasticities of products in its portfolio, forecast demand and justify price increases or decreases at certain locations to maximize revenue. C-store operators working closely with brands can identify the prices that work best for both.
- Trade promotion optimization. A snack brand can test various promotional levers to see which will drive the highest sales outcomes for its retailer partner — and a retailer can see what promotions work best by store cluster, or down to the individual store level.
While these are just a few examples of how c-store operators can grow their overall categories through the help of select category-leading brands, the key to that result is to remember that the AI itself is agnostic. Retailers can trust a brand bringing AI insights because machine learning reviews data without bias. The results are the results — and retailers can take it a step further and direct their brand partners to come to the table with AI and a clear focus on how to enhance the overall category.
Retailers and brands don’t both need to launch massive, consumer-facing events with generative AI, but they should be collaborating to get smarter about the decisions they make inside stores so they can increase sales and margins in the c-store channel.
Weighing the merits of AI
The battle for space is tight inside c-stores and they’re looking to bring foot traffic back to the channel. To that end, the questions for retailers to ask of this technology include: Where can AI build my business? And how can brands play a collaborative role in this process? This will ultimately help them demystify and understand the technology.
Even without AI, c-store operators should be asking brand partners what data and insights they have that will grow the category overall. Then, using AI, the two can test scenarios that identify powerful business recommendations. AI can be a bridge in the retailer and brand relationship.
Secondly, retailers should ask internally what their goals are and how AI would work within the larger organization. Are there internal leaders who can back the importance of using AI, and is there talent in place who are eager to embrace AI? Brands working with c-stores who don’t have the backing to run AI should ask the same questions.
There’s a lot of noise around AI and what it can or cannot do, so it’s critical that retailers and brands take time to pause and understand how it fits within their current business and how it can grow the c-store channel overall. Those who educate themselves will have a clear picture of its benefits, and emerge better off.