The quick-service restaurant industry is built on the delivery of food—and data. 

The former is obvious, complemented by the physical layout and the queue of customers, standing or seated, waiting, respectively, to place their orders or receive their meals. But the latter is the proverbial secret sauce, the (data) packet of ingredients that, when arranged and made accessible to a business owner, reveals valuable information about the interests, habits, and expectations of consumers.

Translating that material into actionable intelligence, converting the language of the Internet with its collection of so many ones and zeroes into a series of facts, is the essence of data. 

Whether we label that content “Big Data,” which is a media catchall for anything and everything that bears this stamp of importance, the point is this: Deciphering data, finding the details that can enable a quick-serve brand to market with precision and anticipate (and adjust to) rapid changes in the marketplace, was, until very recently, an expensive exercise, the once-exclusive domain of global corporations with teams of scientists and statisticians, all of them gathered to “mine” data that is just as golden to the Golden Arches as it is to the rollout of a new dining concept with locations in Miami, Memphis, Minneapolis, and Mesa.

We are now at a milestone in the history of data where its popularization—its democratization—will result in the affordable interpretation of all this content.

Deciphering data was, until very recently, an expensive exercise, the once-exclusive domain of global corporations with teams of scientists and statisticians.

I write these words from experience because, in my role as founder of Ocoos, I seek to give quick-service companies the freedom to build their own websites, manage real-time traffic, and better appreciate the analytics of the Web in general. 

Regarding that term, the “analytics of the Web,” I beg your pardon because there is too much jargon that clouds the meaning and purpose of most conversations about technology. I prefer a discussion about data, plain and simple, that is clear and actionable; I want a solution, based on analysis, not analytics, that tells a business owner what to do—and when and why to do it—so a brand can succeed, period.

That success can have many forms, determined as much by what you see—the opening of new restaurants and the unveiling of related billboards, banners, and streamers—as by what you do not see: Busy highways and adjacent roadways without a particular restaurant, a strategy of conscious choice—call it action-by-absence, powered by data—where intelligence reveals which spots to avoid, and what marketing slogans to retire, so a brand’s position (and its positioning) is as much a product of literal truth as it is a figure of speech (to consumers).

By explaining the what behind this data, as in what it tells a quick-serve brand about everything from menu items and staffing (including frequency of orders and peak hours of operation) to what customers want and expect (such as farm-fresh produce and loyalty discounts), is invaluable.

The age, job, and income of each consumer—the reduction of this data into specific segments (the variables are as long or short as a company chooses them to be) is the most direct answer, on behalf of each group, to the most crucial question a quick-serve business must ask: What do consumers want?

Access to this data is essential, but affordable access to this data is revolutionary.

It is revolutionary because it makes the quick-serve industry more competitive; it demands a higher degree of attention and care, so businesses can earn the support of new customers and enjoy the rewards of true-to-their-word consumers of passion and pride, the brand ambassadors who infuse every call, post, or tweet with a summons to do: “Go to this new restaurant—now! The food is delicious, and the service is great.”

These things are cause for celebration because, within this ever-growing library of data, there is—finally—not only a means to identify and sort this information, but there is also a fast and effective way to transfer knowledge into measurable results.

Businesses can see what plans work and why and when to maximize these returns. These things, from the most abstract to the most actionable, are part of that larger category known as data.

Now it is ours to use, with accuracy and accountability.

Let us use this information to inspire our deeds, and thus, honor our words about leadership and integrity.

Rahul Razdan is the founder of Ocoos. He has more than 20 of years executive management experience in a variety of roles in sales, R&D, and marketing. He has authored numerous technical papers and is named on 24 issued patents. Razdan holds a PhD in Computer Science from Harvard University. For more information, visit
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