It used to be that all restaurants needed to attract customers was a catchy jingle, a memorable mascot, and a signature menu item. While a strong brand identity is still important, it’s not enough in 2021. Today’s customers want to do business with companies that understand them as individuals.
According to Accenture, 91% of customers are more likely to frequent businesses that personalize their experience. That can be by recognizing them as a returning customer or providing offers and recommendations based on previous purchases.
Personalization is the key to cross-selling and providing excellent customer experiences, and with 87% of restaurant customers planning to continue with mobile and online ordering even after the pandemic, the need for personalization isn’t going away. To offer the personalized service today’s customers expect, restaurants must adopt technology that illuminates individual customer preferences.
The pandemic accelerated many trends in the direct-to-consumer space, including mobile ordering. This shift in ordering provided restaurants with massive amounts of information about their customers’ preferences.
Even before the social-distancing-inspired growth in mobile ordering, restaurants used loyalty programs to recognize their frequent customers. But the pandemic caused more than just loyalty members to use digital options for their takeout. Recent data from Bottle Rocket shows that mobile orders make up 60% of all digital restaurant orders. With the rise in mobile ordering, restaurants now have enough data to build personalization into their customer experiences, fueling the growth strategy for the modern restaurants.
Marketing teams can easily identify when each customer is likely to visit the restaurant, which location (or locations) they frequent, and the menu items they order most often. With this individualized data, restaurants can offer relevant cross-promotional opportunities for their own brand or a complementary brand within their ecosystem.
Say the multi-brand restaurant company Inspire Brands has a customer who frequently enjoys frozen desserts at two of their chains: two scoops at Baskin-Robbins and the occasional Sonic Blast at lunch. This customer might also like a reminder that the mint chocolate shake is available for a limited time at another Inspire Brands’ chain, Arby’s.
Personalization also means meeting (and exceeding) customer expectations with real-time information. According to Deloitte, 52% of restaurant-goers want information from the restaurant that reflects up-to-the-minute changes to help them make decisions. An example might be a recommendation to send the order to a different store a few miles away that has a shorter wait time.
While the past year has been difficult in many ways, the growth in mobile ordering provides restaurants with a foundation for building valuable and personalized experiences for their customers.
Sending the same “come in for a free cookie” push notification to all your app users likely won’t result in an engagement boost. Customers today demand hyper-personalization. To get to this level of tailoring, you’ll need to take a hard look at your current personalization efforts to know where you need to step it up.
Everyone gets the same experience, no matter what city they are in or their previous order history. There is nothing that differentiates one offer from another.
This is the most common level of personalization. Groups of people get unique experiences. Factors that drive personalization could be geography, the time of day, or membership in a loyalty program. Segmentation typically uses a single data point to identify users.
Example: Every customer in Minnesota gets a coupon for a free hot chocolate, while Georgia customers get a free sweet tea.
At this level, restaurant marketing teams start to employ several layers of data, so every user gets a unique experience. Messaging could take into account previous orders, as well as location, localized popular menu items, time of day, and time since their last visit. The chances of two users getting the exact same offer are low.
Example: Temperatures are below freezing where you are in Ohio. Here’s a coupon for the hot drink you’ve ordered three times in the past month.
As the name implies, this level adds an extra layer to a personalized experience by including real-time information or predictive analytics. Not only does each person get a completely individualized experience, but that person also gets a different experience depending on the time of day, where they happen to be, or the actions they are likely to take based on past behavior.
Example: Your GPS-enabled app recognizes that you are leaving the soccer field during the local youth soccer season. Here is a coupon for the kid’s meal you previously ordered so you can feed your hungry athlete.
Unsure which level of personalization your restaurant uses? Here are some questions to ask to see where your current strategy fits in:
A successful personalization strategy starts with a customer-focused and adaptable culture. From there, you’ll need clean, non-siloed data and a clear testing strategy to continually fine-tune your strategy.
Before you can even think about implementing a personalization strategy, you need to make sure you have an agile, customer-centric culture in place.
A strong focus on the customer is also key. To tailor your services, your organization needs to obsessively collect and pull insights from customer data. If your company takes a generalized view of its audience, you’ll likely struggle to deliver the individualized service people expect today.
Chick-fil-A has a long history of customer-first innovation, especially around its digital tools. The company even developed mobile GPS functionality, so stores know when order-ahead customers were on their way. The staff could time when the order was made to ensure the food wasn’t cold when the customer arrived. With an agile and customer-focused culture, Chick-fil-A was able to create a hyper-personalized customer experience.
Bad data is the scourge of personalization. Without correct information, your company risks sending unhelpful recommendations to customers and losing their trust.
Keep your data clean and usable by building a tech stack that includes:
A good personalization strategy looks seamless to the customer. But without clean data and tools to take advantage of it, restaurants can miss opportunities for growth, or worse, turn off customers completely.
Launching new initiatives can be risky, especially if you are just starting to move up the personalization ladder. You can minimize the risks by establishing a process for testing the programs regularly and with narrow segments. Start with one geographic area, for example, or hone in on a particular customer attribute around a specific menu item. Review engagement metrics, such as coupon redemption or visit frequency, on a schedule. Compare them to the campaign goals over time.
When you find something meets or exceeds your goals, look to expand it. Expand your geographic segmentation to a different area with a different offer, for example, to see if the results still hold. For personalization strategies that don’t work, dig in to see if there are things you can tweak, such as the offer or the customer attribute.
By defining specific cohorts in your analytics tool, you can identify user behavior patterns that can be used for testing personalization efforts and measuring outcomes compared to other user groups. Adjusting these cohorts throughout your testing process can help you find the most effective personalization strategies for your customers.
With more people taking advantage of the mobile ordering options because of COVID-19 and beyond, restaurants have an opportunity to use the influx of data to provide the hyper-personalized experiences that create loyal customers. With personalized marketing and customer service, restaurants make it easy for their valued customers to return again and again. These repeat buyers trust the brands to deliver recommendations and offers that fit their needs.