Big Data and How it Can Fuel Restaurant Growth
With over 40 years in the restaurant industry, most notedly as CEO of a restaurant chain with over 150 locations, Ward Olgreen, from Marketing Vitals, shares his perspective on the value of big data for industry growth.
Now that restaurants have access to data like never before, how is this changing the decision-making process for operators?
First is marketing. Restaurants can now spend less and get more because they can trace purchase behavior back to specific transactions and marketing events. So, very quickly, they can determine what is working and what is not even during multiple event periods. It used to be the promotion ad was created with money spent on artwork and buy times for the newspaper, radio and TV. Whether it generated business or not—the restaurant was “stuck” for the run of the campaign. Not anymore. Digital promotions can be rapidlychanged after identifying purchase trends and, if a shift is required, it can be done before the original is entrenched in the mind of the consumer.
Second is pricing. Flat “across the board” price increases aren’t effective. Instead, restaurants are now determining price movement for every menu item (by location) based on guest purchase history and behavior.
Thirdly, and what could be most important, is staffing. Scheduling labor using a “best guess” sales model often will lead to either idle employees or frustrated customers. When restaurants have the use of a predictive six-week model, inclusive of product mix, they can anticipate within 3 percent of their needs. Additionally, having analytic tools to judge server quality by success rate versus total sales is significant. No longer will servers win contests purely as a byproduct number of hours worked, quality of section and being assigned the busiest shifts. The winners will be determined by who has the best conversion ratio of guests served allowing even part-time employees to participate and win. This really helps separate the excellent from average workers.
What is your take on the influx of technology flooding the restaurant industry? From kiosks to facial recognition ordering, should brands embrace the trends or be wary of them?
Embrace them and here’s why. Today’s technology, when gathered and analyzed properly, can change the trajectory of profits locally, regionally, and nationally. And, they are mostly cloud-applications and easily integrated with POS systems, which is why a platform should be developed to be compatible with the most commonly used POS systems, so no additional hardware investment is required. Additionally, a month-to-month fee based provider can be low-risk because there is no contract. This type of arrangement is what every serious restaurant operation should seek to insure satisfaction and success in their operating plan.
In that vein, how can a restaurant maintain the customer service and quality experience guests look for, while staying tech-savvy?
Restaurant technology and predictive analytics will never replace great food, courteous servers, and a wonderful dining experience. The purpose for technology is to enhance all of this so the customer will keep coming back and refer others. Technology should help solve the mystery of frequency by determining why people chose your restaurant, why they will return and, just as importantly, why they may not.
How can data help restaurants with their in-house operations, from employee motivation to performance?
For restaurant marketing intelligence to be successful, it is essential to tie in all the data points from transactions, loyalty clubs, email clubs, text messaging, reservation services, payment history, weather, marketing events, and more. Collection needs to have a process for review that will inform and educate restaurant operators. The purpose should always be to make decision-making more obvious for how to improve planning, buying, pricing, and employee schedules.
The iconic fast food phrase, “Do you want fries with that?” is a genuine upsell line but in today’s world it needs a technology counterpart.