If you’ve spent any time toying with ChatGPT or Meta prompts in the past, you may find yourself wondering about artificial intelligence’s (AI’s) potential for real marketing work. Ninety-one percent of marketing professionals are “already using AI in their jobs,” according to Ad Age/Wakefield. It’s clear that AI is here to stay, and its impact will only expand in terms of how brands engage with their customers.
Inherent Advantages Of AI For C-Stores
The high frequency of customer visits puts c-stores in the driver’s seat for AI as frequent engagement provides more data to train AI models effectively. A c-store that sees a customer three times a week can leverage AI far more effectively than a quick-service restaurant that sees a customer only once a week.
Additionally, c-stores, like other retailers, own a valuable flow of customer data, an often-overlooked advantage compared to consumer packaged goods brands, which typically lack direct data ownership. Most importantly, AI-driven messaging within loyalty programs and mobile apps allows c-stores to enhance customer engagement by connecting directly with their customers.
Why Now Is the Time To Get Started With AI
When unpacking the effort to run complex, multivariate marketing campaigns, retailers will quickly find it takes an army of resources to tackle the task. Conversely, AI-driven marketing ties directly to your own customer data, removing much of the manual effort.
Additionally, AI yields more effective messaging. This is accomplished by sorting through your customers’ behavioral data to determine which type of message will resonate.
Paytronix cites a 50% increase in spend and frequency from messages optimized with AI. NexChapter engagements in the c-store space align with this magnitude of impact.
The Best Marketing Use Cases for AI
Before becoming overwhelmed by the applications for AI, consider these three marketing use cases to get started.
1. Craft personalized messaging tailored to specific segments or individual customers.
This is an obvious starting point for convenience stores. This type of deployment for AI typically provides the strongest and most immediate return on investment by positively impacting open rates, click-through rates and conversions.
2. Use customer data to optimize the time and channel for sending messages.
This is another way to maximize the impact of AI in your marketing systems. AI excels at this type of task given its ability to process massive amounts of data and turn it into individualized guidance.
3. Create product or offer recommendations based on an individual’s purchase behavior.
This approach is similar to Amazon’s product recommendations, enabling you to boost customer engagement in a significant way.
Utilizing personalized trigger promotions is a real-world example of how to combine all three use cases into one. These AI-enabled promotions, using time optimization and product recommendations, engage a customer that has carried out a specific purchase that is missing a natural-fit product for that type of behavior (i.e., buying a slice of pizza plus a dispensed beverage).
The customer who purchases one item is presented with savings on a slice and a beverage for their next visit. The key concept in the trigger promotion is to engage the customer in the moment with a relevant solution, thus dramatically increasing the chances the customer will carry out the desired behavior on their next visit.
While marketing’s potential for AI is nearly endless, what’s clear is that AI represents an amazing opportunity to bring more efficiency and efficacy to marketing practices. In an environment where marketers often find themselves asked to get more out of their limited resources, AI is especially well positioned to deliver.
Matt Sargent, VP of loyalty analytics at NexChapter, has a 20-year history working at the intersection of consumers and brands at retail.
Sargent has led consumer-focused strategy at retailers, including Target, Best Buy and, most recently, Casey’s, where he initiated a loyalty analytics practice resulting in a doubling of program enrollments.
