Sunday, July 17, 2016

Modeling the Market Survey Data to Plan, Develop and Optimize Restaurant Menus

Chapter 1 (from the Book)

Why Demographic Analysis is so Critically Important in Planning Locations and Menus 

While the vast majority of large restaurant chains employ qualified market researchers and quantitative analysts, working with in-house Chefs and testers to plan, develop, and optimize menus, most non-chain and smaller restaurant chains are generally financially constrained from taking that robust research route, and instead rely, at best, on focus groups and internal customer surveys to tweak their menus.

Most focus groups are far less consequential than statistically significant market surveys, while internal customer surveys require sophisticated data tabulation and mining, often packing them to collect dusts. For example, a mere 30 responses a day over a 60-day period will require the help of a data analyst and statistical software to tabulate, analyze, and model the data. If the menus are seasonal, the data collection must be repeated across seasons, necessitating even more sophistication.

Many successful non-chain restaurants located in busy tourist areas or demographically cross-sectional neighborhoods suddenly face disappointment when they try to duplicate that successful “central” format in other parts of the city with vastly different demographics.

John Doe is a very successful restaurateur owning and operating a sit-down lunch and dinner restaurant in a touristy city center. He and his banker agree that the success of this restaurant should be duplicated in other parts of the city, so John decides to open two more – one in the vibrant eastside across from a large State College campus and another in the thriving westside in close proximity to a wealthy retirement community. He has seen success and hence believes in his proven format, including holding his current menu constant for the new locations.

Suddenly, a bolt from the blue.

His Chief Chef is leaving. Due to family reasons, he has decided to return to the west coast. John Doe is nonetheless adamant that he will not abandon his expansion plans. He contacts his banker friend, who suggests ChefQuant Consulting Services. While he is not too thrilled about the suggestion, considering he knows his business inside and out, he reluctantly stops by their office and meets ChefQuant to start the dialogue.  Knowing John is looking to fill the vacancy, ChefQuant invites Priya, a recent graduate at the top of her class from the local culinary school. Before the interview, ChefQuant explains to John that Priya belongs to a new generation who is not only culinary trained but is also data smart, although she lacks the experience of heading a restaurant yet. John is shocked (he was looking for a well-known Chef with at least ten years of culinary and management experience).

John returns to office and speaks to his banker friend who encourages him to take ChefQuant’s advice very seriously. Under a bit of pressure and a feeling of despair, John decides to hire Priya as his Head Chef. While Priya will be working out of the central location, she will be running the two new locations with resident Assistant Chefs and monitoring their operations via live video feeds.

Priya comes on board in a week and starts working with the departing Chef.

A week later, ChefQuant holds his first business meeting with John and Priya. Right at the outset, John makes it adamantly clear that he would not change a thing when it comes to his successful menu and even the interior décor for his new locations.  While ChefQuant did not have any specific survey data for John’s new locations, he puts forth the following citywide survey summary (median) broken down by age groups, politely emphasizing that the eastside location will primarily cater to the Gen-Y (college students) while the westside location will attract mostly Baby Boomers and Seniors 70+.

(Click on the image to enlarge)

The summary shows these two groups’ tastes and preferences are quite different from the overall medians that his central location is perhaps relying on. ChefQuant therefore emphasizes to John that the existing menu has to be meaningfully tweaked in line with the actual survey data and the resulting analyses, with the possibility of several menu items being adjusted, changed or even swapped.

John looks at Priya and wants her suggestion. She says, “Given the divergence in the data, I totally agree with ChefQuant. In fact, once the actual east and west survey data and analyses come in, I suspect they will show even more polarized results than what I see in this citywide summary, potentially prompting significant changes to our central menu. The Gen-Y’s taste for salt and sweet is noticeably higher than the overall medians, though they don’t care for bitter at all. Conversely, BBs and Seniors prefer lower salt and sugar, but are unafraid of bitter.  For example, the appetizer sampler for the west may require a swap like roasted Chinese Bitter Melon with tangy garlic sauce while the east may enjoy a salty and spicy Indian Samosas with sweet Middle Eastern date sauce.”

Priya continues, “By the way, I have been tabulating the recent internal customer surveys for this location in order to understand if there is any disconnect between what we offer and what our customers are truly interested in. I am seeing certain gaps I need to gradually fill in. The culinary business is not all-art anymore. It now requires a good dose of science. For example, this simple correlations matrix tells me how to couple a main ingredient with a complementary sauce.”

John then concludes the meeting by sharing an episode from his college days, “I was a good student, majoring in business. I was so confident of myself that in the final semester I proudly signed up for a class called Applied Finance. To make the long story short, after the third class I had to drop out like a wet cat. The class was nothing but complicated math and the freaking professor was from the Math Dept. I was wondering if I’m looping back into a similar situation, again?”

They will meet in a month after ChefQuant’s marketing team collects and analyzes the targeted survey data.

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