The Value Of Customer Data Analysis For Restaurants
The Value Of Customer Data Analysis For Restaurants

The National Restaurant Association held its 2015 Restaurant Innovation Summit from October 27-28, in which Vice President of Customer Relationship Management Helen Baptist spoke on the value of studying and understanding collected data and statistics gathered on customers.


To prove her point, she spoke of an example of a study that was done on a sports bar chain that had an inaccurate customer profile. According to their initial analysis, their largest clientele was male, aged between 18 and 45, single, frequented Twitter and Instagram, listened to sports radio and made an average of $60,000 a year. This guided the kind of music they would play in the restaurant (specifically top 40, hip-hop, and country music), amongst many other aspects of the bar.


Upon analyzing customer data, they found that the average customer was actually married, aged between 35 and 60 and was making around $100,000 a year, which is nearly double what they had originally estimated. The data also showed that their average customer did not frequent Twitter or Instagram as much as LinkedIn and E-Clubs.


In response to their findings, they were able to rebrand themselves and cater more to families rather than singles. That meant changing their music from Top 40 and hip-hop to more classic rock. They started to play all sports in general instead of specific ones because data showed that this was more family oriented. Had they not collected the necessary data, the bar would’ve likely alienated their customers and gone out of business within a matter of years.


The technology is not quite there yet, however, because there is not one unifying aggregation system that reaches across the entire restaurant industry. Consequently, organizing whatever information that is gathered poses somewhat of a challenge. That’s where Fishbowl comes in, a company that offers comprehensive data analytics solutions for the restaurant industry.


The key to attracting repeat customers is earning their trust, which is best achieved by breaking down the seller-customer barrier. This is best accomplished by personalizing your interactions with potential buyers. Understanding your customers interests, budgets, backgrounds, and physical locations can all help you mold and adapt the way in which you communicate with them.


Data analysis is not just used by major big box stores, but by all food industry businesses, regardless of size or scale. It is quickly becoming the norm, meaning that those who do not take advantage will be promptly left in the dust while their competitors adapt.