Creating Convenience Focused on the Customer
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The reason we pursued this initiative was to explore what could happen if small operations combined their market knowledge with state-of-the-art technology. This led to the development of our consumer app, Earnify, which functions similarly to popular loyalty programs. Rather than naming it after existing brands, we created a standardized loyalty program that works nationwide, attracting more loyal consumers and increasing their visit frequency. In just the past year, we’ve scaled to approximately 8,000 stores, achieving impressive results—68% more active, loyal consumers are engaging with Earnify across the country.
Another crucial component we focused on is a simple, cloud-based retail operating system, essentially a point-of-sale system, that integrates the products sold to customers and the payment systems. We’ve implemented AI to automate many tasks within this retail operating system, resulting in a 20% reduction in operating costs for small store operators. This savings directly benefits their bottom line, allowing these operators to enhance customer experience, reduce operational expenses, and ultimately spend more time serving guests rather than managing the store.
Megan: Absolutely, it’s impressive to see the results you’ve already achieved. You’ve touched on some technologies you’ve implemented. Can you provide more details on what additional technologies, like cloud and AI, you’ve adopted, and what barriers to adoption you’ve encountered?
Tarang: Certainly! We started by enabling small store operators to enhance customer experiences through a basic points-based loyalty program. Customers earn points for both fueling at the pump and purchasing items inside the store. Once they accumulate enough points, they can redeem them in various ways, providing value throughout their shopping experience.
We also leveraged data, machine learning, and AI to personalize customer offers. For example, if a user is in New York and is a bagel enthusiast, they would receive offers for bagel and coffee combos. Personalization extends to different preferences, accommodating individual shopping habits.
Additionally, small store operators can create their own seasonal offers that become instantly available to customers, enabling them to enhance guest satisfaction. However, one challenge for many small operators is technology failures, which can lead to lost sales. We’ve addressed this by establishing a proactively monitored help desk. Utilizing AI, we can identify patterns that indicate potential issues before they significantly affect operations. For instance, if a PIN pad shows signs of failure, we can notify the store ahead of time, helping to mitigate downtime and lost revenue.
Our solution also simplifies customer support, allowing store operators to contact a single number for assistance, effectively outsourcing their IT needs while leveraging AI for proactive monitoring and faster problem resolution.
Furthermore, we’ve implemented a cloud-based POS system that connects with back-office pricing systems, enabling precise and rapid adjustments to product pricing. This connection allows the stores to quickly analyze performance metrics in near real-time, facilitating quicker responses to customer needs. With the scale we provide, operators can access technology that is not only 20% more affordable but also significantly more effective.
Megan: Fantastic. Those are some impactful examples of technology usage. Thank you for sharing. How has the organization responded quickly to the data collected during this campaign?
