OpenTable’s AI Tracks Dining Habits for Enhanced Restaurant Insights
OpenTable, a leading restaurant reservation platform, has recently introduced an AI-powered system that tracks customer dining habits and shares insights with participating restaurants. This initiative aims to enhance the overall dining experience by providing restaurants with valuable data on customer preferences and behaviors. However, the use of AI in tracking such habits has sparked discussions about privacy, data usage, and the potential for misinterpretation of the collected information.
The AI system collects data such as drink categories, spending levels, review habits, and even last-minute cancellations. These insights were first brought to light by Kat Menter, a host at a Michelin-starred restaurant who noticed the new ‘AI-assisted tags’ in action. She shared her experience on a TikTok video, which gained significant attention from the media. The system’s ability to analyze large datasets and provide actionable insights has been a game-changer for restaurants looking to streamline their operations and improve customer satisfaction.
OpenTable integrates with various POS (Point of Sale) platforms such as Toast and Epos, which handle orders, payments, and customer timing during a meal. When a customer’s contact details match their OpenTable profile, the platform can link their visit to their account. This integration allows for detailed reporting on arrival times, order details, time spent, and bill totals, which are then used to generate AI summaries of non-identifiable guest data. These insights are shared with restaurants to help them tailor their services to individual preferences.
Despite the benefits, the system has faced criticism for its potential to misinterpret data. For example, a single business dinner could incorrectly categorize someone as a high spender, while dining with friends who order cocktails might lead to a misleading tag as a cocktail lover. As a result, experts suggest that these insights should be treated as general suggestions rather than precise indicators of dining habits. OpenTable claims that the AI processes anonymized data and does not interact with specific guest profiles, aiming to provide a simplified version of the insights gathered from both OpenTable and POS data sources.
Users are encouraged to review their privacy settings and manage their data sharing preferences to maintain control over their information. OpenTable emphasizes that the use of POS data relies on the privacy settings chosen by the user, and individuals can adjust or opt out of data sharing at any time. However, the privacy policy uses broad terms like ‘dining preferences,’ which may not provide a clear understanding of what data is being collected and how it is used.
The company’s representative stated that guest insights are the core of personalization, allowing restaurants to optimize their service and deliver thoughtful hospitality. These insights come from a mix of sources, including OpenTable, restaurant partners, and POS partners, and are limited to non-confidential information. The goal is to help servers suggest dishes that a customer might enjoy or recognize a preference for a more relaxed dining pace. These insights are shared across the OpenTable network, enabling restaurants to learn and improve the hospitality experience for all guests.
It is important for diners to be aware of how their data is collected and used. By monitoring privacy settings and opting out of sharing POS data, customers can maintain more control over their information. This awareness helps customers understand what their apps track and how they can adjust their privacy settings to stay in control of their data. The balance between personalization and privacy in the dining industry continues to be a topic of discussion, highlighting the need for transparency and user control in data collection practices.