This article outlines:
Order: Automated capacity management and personalized menu recommendations
Pay: Enhanced fraud detection and higher payment authorization
Engage: More actionable guest insights and less manual work
Everyone is talking about using artificial intelligence across industries. And, of course, Olo uses AI and machine learning, too. But good AI isn’t always easy to spot.
Keep reading to see how Olo’s three product suites leverage AI to help restaurants be more profitable, productive, and personalized—from eliminating the guesswork of capacity management to determining the legitimacy of digital transactions to personalizing marketing messages and menu recommendations.
Order | Automated capacity management and personalized menu recommendations
OrderReady AI
The OrderReady AI feature of Olo’s Ordering platform uses machine learning to analyze historical order data and provide guests with highly accurate quote times. By improving the accuracy of pickup or delivery estimates, OrderReady AI enhances operational efficiency and guest satisfaction. At P.F. Chang’s, for example, it has resulted in a +1.3% increase in order conversion, a +20% lift in lead-time quote accuracy, and a 50% reduction in manual lead-time extensions. Read the case study for the whole story.
Smart cross-sells
Smart cross-sells use AI to suggest relevant items to guests at key touchpoints in the digital ordering and checkout process based on contextual factors such as order history, location menu, and current cart contents. This enhances the ordering experience while driving higher average order value for restaurants. A recent test conducted by Olo showed smart cross-sells accounted for 10% more in basket value on average than static cross-sells.
Voice AI
Some restaurants have implemented voice AI technology at the drive-thru or for call-in orders using Olo’s Ordering API and partner ecosystem. With voice AI, brands can improve the ordering experience, increase order accuracy, and reduce staff workload.
Pay | Enhanced fraud detection and higher payment authorization
Risk assessment
Olo Pay’s machine-learning algorithm analyzes hundreds of signals to assess the likelihood of fraud, using historical data to create accurate risk scores. This helps prevent fraudulent orders from being processed and ensures legitimate transactions are approved.
Restaurant-specific fraud detection
Our Data Science team develops restaurant-specific AI models using Olo data to identify strong fraud indicators—ultimately reducing chargeback costs and enabling brands to keep more revenue. This approach is more accurate than general fraud solutions that rely on retail or industry-wide signals.
Case Study: honeygrow reduces fraudulent orders and chargeback costs with Olo Pay
Digital payment authorization
Olo Pay leverages machine learning and analyzes historical data from a network of millions of merchants to determine whether a transaction should be authorized, retried, or rejected. A higher authorization rate means more revenue for the restaurant.
Engage | More actionable guest insights and less manual work
Machine-learning-powered predictive analytics
Olo’s Guest Data Platform (GDP) uses machine learning to provide move-the-needle predictive insights, including guest lifetime value (GLV)—the total revenue a guest is expected to generate over their relationship with the brand—and churn risk. These AI-powered insights empower restaurants to segment hyper-targeted campaigns, boost engagement, and prevent churn.
Case Study: Sonny’s BBQ uses Olo Engage to personalize guest experience and make data-driven business decisions
AI Creative Assistant
Powered by OpenAI and built into the Email Design Editor of Olo’s Marketing solution, AI Creative Assistant uses generative AI to turn content ideas into compelling copy, saving restaurant marketers valuable time. Once the user provides a starter prompt, AI Creative Assistant instantly drafts relevant, attention-grabbing copy which they can refine to match their brand’s voice and styling. It takes one click to auto-populate the email copy.
SmartQuote algorithm
Olo Host uses machine learning to improve the accuracy of waitlist quote times, resulting in faster table turns. It also enables guests to be seated faster with a text and automated, customizable phone call.
Case Study: Olo’s SmartQuote algorithm increases wait quote accuracy for Ruby Slipper
AI-suggested review responses
Olo’s Sentiment solution uses the power of generative AI and machine learning to populate and auto-suggest relevant, personalized responses to guest reviews, saving operators time and ensuring brand consistency in replies.
Sentiment analysis
Few operators have the bandwidth to comb through dozens of reviews and respond thoughtfully, let alone identify trends before they impact sales. Sentiment analysis—the AI-driven process of determining whether guest feedback is positive, negative, or neutral—helps restaurants convert the noise of reviews from multiple sources into a crystal-clear signal that allows them to take one-to-one action with guests and team members.
Watch the video below to see how bartaco uses Sentiment to understand its guests, interact with them in more meaningful ways, and drive operational improvements.
How restaurants can harness the power of AI
At Olo, we view AI and machine learning as valuable tools that enhance our platform’s capabilities and further help restaurants increase orders, streamline operations, and improve guest experiences. From eliminating tedious tasks to surfacing critical guest insights, AI- and machine-learning-powered technologies can free up restaurant staff to provide personalized hospitality that keeps guests returning.
AI is already revolutionizing the restaurant industry—and we’ve only scratched the surface of what’s possible. Talk to an Olo expert to learn how our AI- and machine-learning-powered solutions can accelerate the future of your restaurant business.
