Restaurant Sales Flat? Turn Up the Heat!

By | In Big Data, Blog, Business Intelligence | May 12th, 2017

Revenue growth in the restaurant space is flat. Fast-growing segments such as fast-casual and limited-service restaurants (LSRs) are gaining at the expense of established chains and locations. This situation is described in a new white paper from Datavail, entitled Big Hot Customer Data: Increasing Restaurant Revenue Through Customer Segmentation.

“Food industry research firm Technomic predicts flat growth for the restaurant industry for the next 18 months. If you are serious about growth, you have to take market share from competitors. The smart use of big data can give your restaurants an advantage that most in the business are missing.”

Technomic‘s predictions for 2017 are a 3.5% nominal growth rate with 2.7% inflation for an expected growth rate of just 0.8%. No matter how good you are at cost-cutting and operational efficiency, you cannot beat the trends without stimulating revenue growth. The best way to generate restaurant revenues in a time of stagnant growth is by forging a deeper relationship with your customers through proactive customer segmentation and “big data marketing.”

Growing Restaurant Revenues

Restaurant chains on average know the identities of less than 10% of their customers. Right off the top, that means 90% of the data is missing. How easy is it to develop effective marketing messages when more than half of your customers are a mystery?

This is not the customer’s fault. Customers provide boundless information directly and indirectly to restaurants but restaurants choose to overlook customer information because there’s no single 360-degree view. Data for customers can be gathered from the moment of contact to the moment of payment, and everything that happens between and even beyond. The Datavail white paper contains dozens of data points where customers can be tracked, including what was ordered, in what order mode and channel, when it was picked up, who has referred the customer, and what, if any, discounts were used.

Gather this basic customer data in one place – a single database with information from customer research, POS systems, customer relations, website tracking reports, loyalty programs, and other proprietary company data. This data is then enriched with psychographic analysis performed in-house or by third-party vendors. From a simple name and location, profilers can build deep profiles on every customer from publicly-available records.

From Basic Data to Breakthrough Insights

Integration of all this data into a single data source is the first stage of building a restaurant revenue-generating machine. Breaking down all those silos where data is kept by different groups of people in different formats, and getting it into one container is a long process well worth the effort.

Customers can then be mapped to different target market segments based on the criteria you want to cluster – whether they dine alone, as a couple, or as head of a household, for example, or whether they prefer dine-in, pickup, drive-thru, or delivery. Customer profiles are then scored. With this infrastructure in place, you’ll know who to market to if you want to increase revenues in a specific target market, and what message will be most effective for each customer or prospect.

Case Study Proves the Point

The Datavail white paper Big Hot Customer Data: Increasing Restaurant Revenue Through Customer Segmentation includes a case study of a national casual dining chain that hit a wall after years of exceptional growth. When traffic started to flatline and revenues started going the wrong way, the restaurant chains contracted with Datavail to build a better system to guide their marketing efforts.

When Datavail began the operation, the chain knew the identities of only 6% of their diners. A concerted effort to collect data on existing customers and integrate the data already being collected by the chain resulted in the percentage of known diners rising to 30%. When their marketing moved from using broadcast messages to the entire market to using personalized messages based on customer profiles and segmentation, revenue per dollar spent on marketing increased threefold. That’s the kind of acceleration your business development efforts can get with personalized, segmented marketing messages.

If your customer data acquisition and analysis is not so hot,contact Datavail today about heating up restaurant revenues with business analytics or attend our presentation at the upcoming National Restaurant Association show May 20-23 in Chicago, IL. Former VP of Information Technology at Red Robin, Evan Eakin, and former Head of Business Intelligence at PF Chang’s, Dominic Yacovella will be presenting their expertise in using data to build restaurant revenue during their technical session. Learn more here or register for the show here.

Datavail is a specialized IT services company focused on Data Management with solutions in BI/DW, analytics, database administration, custom application development, and enterprise applications. We provide both professional and managed services delivered via our global delivery model, focused on Microsoft, Oracle and other leading technologies.

 

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Executive Advisor to Datavail
Evan Eakin is an Executive Advisor to Datavail in the restaurant vertical who has been expertly navigating organizations through technology transformation for over 20 years. As the former Vice President of IT at Red Robin, he has deep experience with point-of-service businesses and has consulted or led teams in Retail, Retail Services, Hospitality and Ecommerce industries. Prior to starting Green Leaf Business Solutions LLC, a technology consulting services and advisory firm, Evan spent five years as the Vice President of Information Technology for Red Robin International. Evan earned a Bachelor of Science degree in Industrial Engineering from Cal Poly State University, San Luis Obispo.

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