Webinar shares how restaurants can enhance operations and engagement with geofencing.

In a recent webinar, experts discussed the future of location-based technologies in the quick-service restaurant industry, focusing on personalized experiences. They covered topics ranging from geofencing to mobile adoption and its transformative impact on customer experiences.

Geofencing creates a virtual boundary around a physical place to track user movements. It has grown in popularity among restaurants. Major brands like McDonald’s and Chick-fil-A have rolled out nationwide geofencing efforts. Yet, the technology is far from static. Experts anticipate it to evolve to cover more than just sending push notifications when a customer is near a restaurant. It could be instrumental in analyzing customer behavior more intricately to offer more personalized services. For instance, if the system knows a customer frequently visits around lunchtime, it could send a special offer before their typical visit time. It would not only drive revenue but also improve customer satisfaction.

On the operational side, we can use geofencing to optimize order preparation times. By detecting a customer’s location and estimated arrival time, the restaurant can time the order to be ready as the customer arrives, adding a personalized experience and ensuring customers receive their orders hot and fresh.

Mobile apps have gone beyond store locators to becoming platforms for mobile ordering, curbside pickups, and direct communication channels between brands and customers. The pandemic accelerated this trend, making digital experiences more mainstream. Now, quick-service restaurant brands have enough data to personalize experiences further and measure their strategies’ effectiveness.

To gauge the success of these technologies, quick-service restaurant brands often rely on A/B testing and ROI calculations. For instance, after running a targeted campaign, the brand would assess whether the offer successfully drove upsells and had a positive ROI. The data gathered would be used to improve future campaigns. Brands like Panera, Dairy Queen, and Whataburger have effectively implemented geofencing and other location-based technologies to enhance customer experience.

In an era where Amazon and Uber set customer expectations, the bar for personalized experiences is continually rising. Location-based technologies and data analytics offer quick-service restaurant brands a chance to meet these expectations and exceed them by offering truly tailored and efficient services.

In this webinar, experts also discussed the transformative role of Radar and mParticle in enhancing personalized experiences for quick-service brands. These technologies, which work in tandem, use real-time and historical location data to power real-time messaging and perform advanced audience segmentation.

Radar specializes in real-time location tracking. When a customer enters a designated geofenced area, like a parking lot, Radar collects this data and sends it to mParticle. mParticle is a real-time customer data platform (CDP) that can further analyze this information and channel it to other systems like Braze for immediate notifications or offers. This ensures timely and relevant messages are sent at the right place and time.

mParticle’s capabilities extend beyond conveying messages for Radar data. It also adds layers of customer profile information. For example, it can identify a high-lifetime-value customer entering a store, allowing the business to offer a uniquely tailored experience. The integration between Radar and mParticle is mature, bidirectional, and essentially plug-and-play, requiring just a couple of API keys for activation.

Balancing efficiency and convenience with personalized experiences can take time and effort for quick-service restaurants. However, the experts argue that these are separate priorities. Brands must responsibly collect data and use it in ways valuable to customers. One strategy is to offer loyalty programs, which create a win-win situation. The brand receives valuable data while the customer gets personalized offers.

Despite the opportunities, there are challenges, such as privacy concerns, implementation difficulties, and cost constraints. Radar and mParticle offer various tools to handle data responsibly and to ensure accurate and real-time tracking, mitigating many of these challenges.

Metrics for assessing success range from input metrics, like engagement stats, to output metrics, like average order value (AOV). A rise in AOV would indicate that personalized offers, driven by real-time context, result in more customers purchasing.

In summary, Radar and mParticle offers a seamless, real-time experience that can drive quick-service restaurants’ operational efficiency and revenue growth. The collaboration between these platforms enables brands to achieve a high level of personalization, ensuring that customers receive the right message at the right time, ultimately boosting customer engagement and satisfaction.

To learn more, watch the webinar.

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