OpenTable has unveiled its AI-powered tracking capabilities, allowing the platform to gather detailed insights into customer dining habits. This advanced feature, combined with integrations with Point of Sale systems like Toast and Epos, enables the system to collect data on various aspects of diners’ visits, including order details, arrival times, and spending behaviors. These data points are used to generate anonymized insights that help restaurants tailor their services to better match diner preferences. For example, consistent choices such as favoring sparkling water or dining early could lead to personalized recommendations or adjustments in how a restaurant manages its service. Nonetheless, OpenTable states that all data is processed in a way to prevent individual identification, ensuring privacy.
The introduction of these AI insights came to light when restaurant host Kat Menter noticed the system’s ability to label diners with AI-assisted tags on her TikTok page. She described an incident where an AI tag incorrectly labeled someone as a high spender due to a business dinner, highlighting the potential inaccuracy of such data. This led to a broader conversation on social media about the implications of this level of customer tracking. Other users who reviewed their data found it to be limited to basic contact details and a list of past reservations, suggesting that the depth of insights may vary depending on the restaurant’s integration with POS systems and how long they have used the feature.
Despite concerns about data privacy, the company maintains that the use of these insights is optional, and users can modify their privacy settings to control what information is shared. OpenTable’s representative stated that these insights come from a mix of sources, including restaurant partners and POS systems, and are limited to non-confidential information. The AI helps streamline restaurant operations by identifying common behaviors and suggesting ways to enhance the guest experience, such as recommending dishes or maintaining a relaxed pace. Users who are concerned about data exposure can opt out of sharing their information with restaurants, ensuring greater control over their personal data. This technology marks a shift in how restaurants engage with their customers, leveraging data science to offer a more personalized and efficient service without compromising individual privacy.