Restaurant chains tap big data for growth, customer engagement
Restaurant big data has a myriad of uses that gives marketers the upper hand
Big data is making a significant impact on decisions made in the restaurant industry. A saturation of restaurants, combined with less loyalty from Gen Y and Z, and the ubiquity of foodservice in the retail and omnichannel environment are contributing to an industry that is highly competitive. It’s an environment in which apparent customer traffic growth for one restaurant is only achieved at the expense of another, and one in which customer and transaction data analysis has become more valuable.
But how can all this data be tracked? Mounds of data are pouring in from point of sale systems, mobile app platforms, email campaigns, social media channels, review sites, in addition to real-world experiences and feedback, to name just a few.
Use of big data grows
New Gen Apps, an international IT solutions provider with offices in Mumbai and New York, has identified several uses of big data analysis for foodservice and food retailers. There are several high-impact uses: to analyze data to customize the guest experience, to create offers and marketing campaigns with a higher value proposition, to understand social sentiment and to learn from such feedback using text data analysis, and to create predictive analysis to create better food delivery experiences for customers.
Predictive analysis can also improve the drive-thru experience, enhancing preparation for large orders, based on previous drive-thru lane traffic patterns. Data analysis that can be used to customize a mobile ordering experience, for example, can be personal and automated so that customers’ next most desirable item is offered to them automatically on a future mobile app transaction. This type of interaction is done through a market-basket analysis and can be part of recurring programming.
One of the most common uses of data analysis has been social sentiment analysis. Natural language processing, for example, is a common tool applied to this type of data collection and review. Multi-unit operators can learn much from social sentiment, and the analysis can be scaled to fit the size of the restaurant chain. In today’s world, customers are easily able to review a restaurant and be a critic. For restaurants, the popularity of review sites and the large presence of feedback tools within search engines and aggregator websites makes the task of analyzing data quite daunting.
“Forget the dread of a famous restaurant critic’s piece hitting the newsstands. Restaurant brands now must treat every diner as a restaurant critic. When you wow them, they’ll light up the social landscape with praise.”NetBase Social Intelligence Restaurants 2018 Report
“Forget the dread of a famous restaurant critic’s piece hitting the newsstands. Restaurant brands now must treat every diner as a restaurant critic. When you wow them, they’ll light up the social landscape
with praise,” notes a Social Intelligence Restaurants 2018 report from NetBase, a social analytics technology provider. While some vocal restaurant owners have felt outrage and scorn at the types of comments they are seeing on review sites, and this reaction has prompted many a news headline, other savvy managers are extracting that information to operate better restaurants.
Big data to analyze consumer sentiment
NetBase notes that this type of online information is freely available and can be used as a tool to give customers exactly what they want and culling widely available feedback and sentiment. Additionally, it can also be used for benchmarking and evaluating competitor performance.
Sentiment analysis can also be used to more easily make big changes to a restaurant operation. A NetBase Social Intelligence Report: Restaurant Brands 2017 used sentiments to rank select restaurant chains in several categories that mattered to each: hospitality, cleanliness, order accuracy, selection, quality and value.
Not surprisingly, Panera Bread lead the list of several notable restaurant chains, based on average scores. NetBase suggests Panera Bread’s use of big data analytics loomed large in key decisions around its commitment to clean-label products, preservative-free ingredients and hormone-free foods. It posits that the changes by Panera Bread were made specifically for Panera Bread’s audience and have added to the brand’s value over time, leading to its acquisition by JAB Holding Co. in 2017.
Brand messaging and marketing
Big data analytics can also improve the types of marketing campaigns that chains can deploy. Multi-unit restaurant marketing has become more science than art as data sets can provide a glimpse into an audience and how to best communicate with it. “The most important things big data analytics allow us to do is understand our audience better and provide insights so we can craft better creative (marketing campaigns)” says James Ward, co-owner and chief creative officer of Saturday Brand Communications, based in Charlotte, N.C. “So in short, we’re using the data to more effectively uncover the humanity and human truth we can either message against or use to determine deployment methods.”
Using big data, marketing teams can weigh their options carefully, and this can play a key role in testing campaigns and messaging and can help provide direction. Ward says, “Big data lets us tap into behavioral data and combine (it) with machine learning to perform highly efficient testing. It means we can explore and/or test multiple directions in messaging simultaneously throughout the life of a single campaign.” A/B (split marketing) testing is more scrupulously analyzed, and its success in resonating with an audience can be more predictable.
Many marketing programs have lost money and did not produce a discernible return on investment, notes the Social Intelligence Restaurants 2018 report from NetBase, because intra-campaign progress could not be easily performed. “But that’s no longer a concern if you have the right tools in your arsenal,” says the report. “Track campaigns in real time and adjust as needed to ensure success—even if it’s not how you pictured it.” NetBase spotlights a campaign in which Chick-fil-A used social analytics to launch a campaign with a chicken sandwich covered in honey. Using this information, the quick-service chain was able to launch a successful breakfast campaign with similar images—honey literally oozing and dripping over a biscuit. That recommendation from marketing agency Moxie led to a 46 percent brand awareness boost.
“We’re using data sets and machine learning to empower our creative, which is always king,” says Saturday Brand’s Ward. “The data gives us the ability to prove that the insight or hypothesis that we think will resonate best with our audience actually does so.” NetBase emphasizes that all tools must work together cohesively so that restaurant operators are not overwhelmed. The company recommends investing in tools that offer everything “currently on the social analytics menu,” including sentiment analysis, image analysis, customer experience analysis, and integration with other business tools.
Author credit: Rick Zambrano
Photo credit: Panera Bread