A national quick service restaurant (QSR) wanted to increase and drive the number of incremental trips to their locations. The client needed guidance on who to target, which marketing channel to choose, which messages to send, and most importantly – what time to send it. Our team of data scientists worked with the client to provide insight on which communication tactics would be the most effective.
Quick service restaurants (QSRs) typically see traffic during meal times (breakfast, lunch, and dinner). Because of this, it is difficult for the industry to encourage patrons to visit during non-meal hours. Furthermore, it is also difficult for restaurants to increase their overall spend and stock-up on products, which is a successful tactic other food or beverage companies use. The buy 3, get one free doesn’t work when you just need one meal for lunch.
As a result, the client faced a common QSR issue: three opportunities for people to come in and buy – and that’s it.
Moreover, the client had a data issue. While their CRM included customers’ home addresses, it did not include where customers worked. Many customers travel to QSRs during the workday so it is valuable for the client to know where they worked to effectively market to them.
Lastly, the client had four different marketing messages to present to potential clients: Healthy Salads, Juicy Cheeseburger, Hot Wings, or frosty beer; however, there was no data about which products the customer would likely respond to in the CRM or elsewhere. The client struggled to understand who to target, which channels to use, and which messages to send.
Using a big-data platform, a team of data scientists pulled together receipt-level data, email response, Facebook profiles, 3rd party household data, and CRM. They utilized Facebook API log-in data to detect where people are working.
With this information now in-hand, the data scientists partnered with the client’s Marketing Department to create messages that would entice customers to come to the client’s QSR, focusing on Workday Lunch and Workday Happy Hour. They utilized the following channels:
- SMS (text)
- Social Media
As a result, the cross-functional team derived the optimal day and time a customer should receive a “join us for lunch” email. With the data gathered, they made decisions, such as if a certain customer should be shown a healthy salad or a juicy hamburger.
In the end, the cross-functional team improved open-rates on emails reaching 20%. More importantly, the team created a machine-learning platform that would continue to learn the optimal timing, cadence and message – and tied it back to the actual customers, making it easy to quantify the ROI.
The tools and techniques for delivering the right message to the right customer at the right time and picking a clear channel are critical to changing behavior. Every customer is different. Some enjoy hearing from brands and advertisers daily. Some prefer every other week. Deals motivate some customers and others just need a little reminder. Data science techniques provide a powerful tool to solve these challenges and can be applied to any industry where there is a relationship between a customer and a provider. If you have customers who buy from you and you communicate with them, you can apply these techniques to your business.