5 Customer Data Platform Use Cases for Quick Service Restaurants

The quick service restaurant industry is up against a mounting number of challenges from greater costs and lower margins to consumer demands for higher quality, more options and increased expectations for how they interact and engage with brands. It’s no easy feat to deliver that one-of-a-kind customer experience that consumers have come to expect in an omnichannel world, especially when many QSRs are stuck with legacy technology that limits their ability to gain a single view of the customer and deliver personalized engagements on the right channel at the moment of impact. Here’s the good news though: the birth of a new category of technology–the Customer Data Platform (CDP)–is making it possible for brands to execute all that and then some. Not a believer? Keep reading to learn five CDP use cases for quick service restaurants!

Targeted Offers

Sending your entire customer base the same, generic offer won’t help you build the type of deep, long lasting relationships with customers that will help you keep competitors at bay. In order to succeed at this, marketers need to be able to send targeted offers and promotions to drive incremental sales and use a customer’s purchase history, engagement pattern, demographics, geo location and more.

An advanced CDP can leverage machine learning algorithms to take that historical purchase data to calculate the products the customer is most likely to purchase or “the next best offer.” These calculated values can then be sent as offers through campaigns created in the CDP. For example, send customers who haven’t made a purchase in the last 30 days a push notification or email with specific offers or display a personalized offer in the mobile app related to a customer’s product category affinity.


Customer Experience Feedback

Brands need to be able to receive feedback from consumers about their experiences with your company and respond in real time.

With a CDP, brands can send the right engagement to a customer based on a signal that the customer exited a specific geo-fence. For example, send all customers located in Southern California a post-visit survey with creative X, and send all customers located in Boston a post-visit survey with creative Y.

Personalized Menus and Content

It’s crucial for quick service restaurants to personalize and tailor every stage of the customer journey. Using purchase history and data, advanced CDPs enable marketers to display menu items and content on any channel that is relevant to the customer.

For example, show a featured menu item based on an item the customer hasn’t yet purchased; show a featured menu item based on an item the customer has purchased often; or show the top three menu items the customer is most likely to purchase, as determined by machine learning algorithms.

Closed Loop Point-of-Sale Redemption

Marketers long to be able to send targeted promotional offers to customers and enable those offers to be redeemed at the POS, in-app ordering, or web ordering.

For example, using data points like customer behaviors, demographics, purchase recency or frequency, marketers can create offers such as BOGO, % off or $ off. Customers can then provide the offer code sent to them through any number of channels to redeem the offer. For example, send customers that typically visit in the morning a targeted offer to drive them back in the afternoon when store traffic is weaker.

Machine learning algorithms can predict a customer’s product preference rating by passing POS data back to the customer’s profile, analyzing the person’s preferences and correlating relationships between products purchased and other items within the product catalog. Then, customers can then be segmented by other user-specific information such as activity and message engagement to populate the “next best offer” to deliver a unique customer journey.

Proximity Personalization

One of the greatest values of advanced CDPs is that they provide the tools to connect the physical and digital worlds. One way that CDPs can do this is by enabling marketers to use a customer’s proximity to stores for campaigns, offers, and messaging.

For example, when a customer who hasn’t made a purchase in the past seven days enters a pre-defined geo-fence of one of your restaurant locations, send the person a push notification to invite him to stop in; or when a customer with a dwell time greater than 10 minutes enters a pre-defined geo-fence of one of your competitor’s restaurants, tag the customer profile with the name of that competing restaurant to be used for later segmentation, reporting and campaign targeting.

To stand out from competitors in today’s omnichannel world, it’s imperative that QSRs deliver a unique, tailormade experience for each and every customer. Advanced CDPs offer brands the tools they need to unify their data, create a two-way relationship with customers to drive incremental high-value behaviors and increase the speed with which they engage with customers because quick service is nice, but real-time is better.