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AI and Machine Learning: The Secret Ingredients for Thriving QSRs – Part 1

Artificial intelligence (AI) and machine learning (ML) aren’t new, but they’re suddenly having a moment. ChatGPT is everywhere you look, frightening some and emboldening others. Will the technology replace humans? Not likely, but it just may get your drive-thru order correct and your pickup order out to your car at lightning-fast speed.

Revenue Management Solutions (RMS) is on board with the benefits of next-gen technology. In fact, our core methodology for pricing begins with AI.

We sat down with Michelle Miller, RMS’ Director of AI and ML, to ask a few questions about the role that AI and ML play in the quick service restaurant (QSR) world, what the technologies can do — and what they can’t do or won’t replace.

First, we hear about these terms all the time, but what exactly are AI and ML?

AI is a set of processes and algorithms that can simulate human intelligence. ML is a subset of AI that stores and analyzes data to assist AI technologies in learning and improving over time.

From a high level, what role do AI and ML play in franchise-owned QSRs?

AI and ML are most helpful when you have lots of data. Given that QSRs generate thousands of transactions daily, it’s a model environment for their use. We can examine the data to find insights present there. It doesn’t have to be complicated, either. AI/ML can be as simple as data mining —analyzing transaction data and P&Ls to pinpoint where a franchisor can cut costs based on where the data tells me they’re spending the most.

How can QSR brands leverage AI and ML to help improve profits and franchisee success?

AI can help you dig through information to pull out what’s most helpful, mine it for insights and identify patterns in the data. Ultimately, you can then help your franchisees act on those insights and patterns as they’re discovered.

What’s a low-hanging fruit example of how AI/ML can be applied? 

Think about bundles. With the help of AI, you could look at items often purchased together and then create valuable bundles for your guests. You can study which specific bundles are performing well and promote them to drive sales.

Another example of that doesn’t require a huge lift is supply chain forecasting. There are tools to help monitor and manage your orders and inventory. For instance, if you’re running low on something and can’t wait for the next shipment, you could boost your order and avoid a menu item being unavailable.

Be sure to check out part two of our conversation with Michelle for more examples of how QSRs can implement AI and ML into their business.

If you’re interested in learning more about RMS’ pricing and financial insights solutions, please reach out. We’re here to help.

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