Hey Restaurants! How Many Customers Do You Know By Name?

There are many fields where customer-facing businesses know the name of every single customer they serve. Clinics, auto repair services, utility companies — these are some commonly used customer services where virtually every customer identity is known to the service provider. Then there is the restaurant industry, where on average, service providers know the names of less than a third of their customers.

Even best-in-class Starbucks knows only half of its customers by name. Does it matter? If you have strong business, good prices, and loyal customers, why do you need to know anything more?

You need to know as much as possible because your business is going to change. Your customers are going to age, some are going to move away, their tastes are going to change, and the way they purchase and consume meals will also change. Without data about your customers, it’s hard to change with them. It’s difficult to understand what they like and what they want. It’s hard to grow your restaurant without data about who is eating your food, engaging in your service, and why.

Customer Data is Driving the Restaurant Business

A new white paper from Datavail explores the use of Business Intelligence (BI) in the restaurant industry. Entitled Big Hot Customer Data: Increasing Restaurant Revenue Through Customer Segmentation, it examines the way data combined with Business Intelligence and analytics practices yield tasty insights into restaurant customer behavior.

Some of the ways restaurants are using big, hot customer data include:

Menu Mix Decisions
Menu items are being selected based on analysis of sales and trends. New menu items are being designed based on customer feedback data. Menu items are also being suggested through analysis of customer psychographics and demographics vs. simply location and demographics.

Procurement & Demand Planning
The timing and quantity of orders is increasingly being re-designed to optimize food quality and maximize location revenues. This results in more discounts taken, more just-in-time inventory, and less food waste.

Staff Scheduling
BI systems are analyzing customer traffic patterns, including time of visit, time waiting for order, and time on-premises to schedule employees. Balancing customer satisfaction against costs of additional staff, analyzing data can determine when a rush is an unusual event or likely to recur.

Marketing Spend
This is probably the most important change resulting from big, hot customer data. Customers are segmented into behavior patterns and marketing messages are customized for individuals to maximize engagement. Analytics eliminates the wasted mass-market single-offer spends and replaces it with segment messaging to small groups and even individuals.

Collecting Restaurant Customer Data

Most restaurants are already collecting a myriad of customer data they are not using. Payment card swipes provide first names and last names. From there, complete profiles can be built up for customers by harvesting some of these other internal data points:

  • How did the customer first contact you for this sale?
  • Did someone else direct the customer to you? If yes, who?
  • How did the customer arrive at your location?
  • What exactly did the customer order?
  • How was the meal paid for?
  • Was any discount applied? From what source?

The Big Hot Customer Data white paper goes on to list dozens of data points you could be collecting about your customer, including their behavior post-visit. Did they review you or rate you online? Did you send a thank you message or offer within 24 hours?

According to data collected by Polaris Marketing Research, satisfied customers tell on average three people about their experience at your restaurant and dissatisfied customers tell on average 18 people. Big, hot customer data can help you take action to influence those numbers before it’s too late.

Augmenting Restaurant Customer Data with Business Data

In order for restaurants to tap the ability to segment and market to individual customers, they need as much data as possible integrated into one system. Your restaurant has phone records, supply invoices, payroll information, bank records, website traffic data, email archives, mobile phone data, social media data, and probably many reports provided by third-party vendors. All of this data could already be sitting around waiting for someone to heat it up.

The integration of data from throughout the organization into a single data warehouse is one of the biggest problems for organizations to tackle. Every department, functional area or outlet may be keeping its own set of books and uniting them may be impossible due to incompatible software, methodology or terminology. However, data integration is necessary to realize the benefits of customer analytics.

Datavail worked with a national fast casual dining chain that was opening more than 20 outlets a year at its peak. Then traffic stalled, revenue stalled, and profits declined sharply. They contacted Datavail because of the company’s track record of building customer personas for major restaurant chains. One of the first problems identified: the chain knew only 6% of their customers by name, and they were using mass media to push a discount message that was not working.

After an assessment and approval for a Customer Analytic Map, Datavail integrated the chain’s data and began intense customer profile creation, tracking, customer segmentation, and restaurant analytics. This resulted in learning customer names and building customer profiles for 30% of the chains customers. That data was used to customize marketing messages, resulting in three times the revenue generated for each dollar spent marketing.

Building Customer Profiles with Data Discovery

So far, we have only discussed data that the restaurant possesses — data about its customers and its operations. This data can be easily and dramatically augmented using data discovery methods or third-party providers. By combing the Internet and social networks, it’s possible to build a large dossier on a customer from just a name. When BI systems are integrated with content marketing systems, a lot of customer information can be added automatically through the organization’s own marketing efforts.

“The first goal is to identify your customers. You want to unanonymize the entire population of unknown customers. The goal of most restaurants is to go from 95% unknowns to 70% unknowns. You should know at least 30% of your customers by name, age and occupation.” — Evan Eakin and Dominic Yacovella, Big Hot Customer Data: Increasing Restaurant Revenue Through Customer Segmentation

If your customer data acquisition and analysis is not so hot,contact Datavail todayabout 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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Senior Vice President of Strategic Client Services
Dominic is the SVP, Strategic Client Services for Datavail, a national leader in the BI, Analytics, and data professional services arena over the last 15+ years. Dominic’s analytical capabilities include experience across many divergent industries like Restaurant/Hospitality, Manufacturing, E-Commerce, Financial Services, and Big Box Retail. Dominic has led BI, Analytics, and Information Technology teams organizationally for some of the major leaders in these respective industries within North America, and his expertise is seen across technologies like the Microsoft BI stack as well as the Tableau visualization platform. Dominic has an Economics degree from Villanova University and an MBA from NSU. He has also been awarded a certificate from the highly-acclaimed Georgetown Executive Leadership program and has held his Six Sigma Green Belt certification for the last decade.

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