One Million Meals a Day (or how many calories are in your promotion?)
Recently, lawmakers agreed on who, where, and how a national program would roll out a requirement for restaurants to label the calorie content of their foods. A number of locations–including New York City–already have these regulations. Calorie counts are a great example of a brand new source of data not only being unleashed to the public, but more importantly, influencing their purchasing behavior. A.G. Lafley, the CEO of P&G, called the point of purchase where a consumer makes the buying decision the ‘moment of truth’. More and more, the calorie count will be front and center at this moment of truth. And purchasing behavior maps to profitability, brand loyalty and brand switching, market share, and all the wonderful things that businesses need to be constantly measuring, mining, and acting on to stay competitive and meet their performance expectations.
Consider this thought exercise. There are approximately 300 million (300M) people in the US, so one can assume there are 300M meals eaten a day (the number of babies eating no prepared meals offsets those who eat more than one meal a day, CED). According to NPD, one in five meals are served in restaurants, so 20% of 300M is 60M. Although I can’t source it, somewhere over 50% of restaurant meals in the US are served from chain restaurants. Thus 30M meals a day from chain restaurants. Very soon, these 30M meals, when ordered, will need to be accompanied by a calorie count, if not more information such as fat content. Another study cited by a July 8th article in the Wall St. Journal cited that 1/3rd of Subway customers noticed the nutrition information of their order, although other chains showed much less notice. If we assume 5% of patrons notice the information and are influenced by it, that’s at least 1M meals a day where the consumer is influenced by calorie count. Another validation of these numbers might be the following: McDonalds serves 47M consumers a day worldwide, so let’s assume 20M in the US. If 2.5% of those customers notice the calorie counts, that equals ½ a million customers—assuming one eats only one McDonalds meal a day, there’s half your one million meals out of just one chain. If an average meal costs $6, then the total economic impact of changing preferences may be conservatively estimated at $6M per day, or $2B per year.
Many of today’s sizable data mining businesses and technologies were founded on addressing market pain of less than $2B. This new data phenomenon is real. We can expect to see a growing prevalence not only of consumer data mining solutions, popular ones about on the web and now they’re hitting the phone. But the business opportunity here is selling data mining applications to the chain restaurants. The meal providers should want to know
- If we want to look at price elasticity of meals, wouldn’t we want to look at calorie elasticity?
- We want to see calorie responsiveness geographically, demographically, related to time of day, size of store, and against a number of other independent variables (or dimensional data, if you’re a techie)
All these tie back to promotions and new items. If the restaurant is looking at new item profitability, how to grow a segment of our category, or where to get the most bang out of the promotional buck, maybe calories is where to start. And if we’re talking numbers, with millions of consumers, and hundreds of thousands of stores, take a guess at how much data we’re talking about. Clearly, mining this is not something a business can do with any kind of speed applying statistical functions on little databases like MySQL or Oracle.