Editor’s Note: This is the third in a series on pricing strategies within the quick-service restaurant industry. Click here to read part one, and here to read part two.

Hello again QSR readers! Before we dig into another alternative pricing strategy, we want to take a moment to look back at where we’ve been. In case you missed it, in our last article we introduced a hypothetical fast-casual restaurant named Millie’s and used it as a way to showcase the benefits of transitioning from a cost-plus pricing strategy to a more sophisticated, attribute-based pricing strategy. Now, because the next model we are going to discuss builds off of the attribute approach, here’s a reminder of its essential elements.

First and foremost, attribute-based pricing is a strategy that draws from a product’s internal characteristics and external factors to ensure that an item’s price reflects its consumer-perceived value. Inherent to this strategy is an understanding of the monetary value associated with different attributes for a dish. For instance, the average price of a regular side of french fries based off of a cost-plus approach in Chicago is $4.20. But when we add on just a few descriptive words to the term french fries, the price can be increased. As in, the average price of seasoned french fries is $4.71, while hand-cut french fries sell for $4.63. Both prices are more than 40 cents, or 9.5 percent, above the cost-plus derived average price of regular French fries, and there’s no additional food costs associated with the hand-cut methodology. Nor does seasoning a serving of french fries cost 44 cents. The point being, if you are an operator using a cost-plus pricing approach, you are glossing over the value your market has assigned to specific attributes of menu items, the key word being market.

This is where our second pricing strategy comes into play. While we know that different attributes have different values, we still don’t know if and how those values fluctuate across the country. If you are a chain operator in charge of a fleet of restaurants in different states, this is invaluable information. When layered on top of the attribute-based approach, a market-based approach allows a chain restaurant operator to tailor the pricing of his menu items and each of their corresponding attributes to local averages and consumer expectations.

Take, for example, bacon. By analyzing menu data, we know that when put on a burger, bacon in Arizona has an average value of 55 cents, whereas in Iowa, bacon’s value on a burger is 70 cents. Knowing that, there is no reason why chain restaurant operators should price their burgers with bacon in Iowa the same as they price a burger with bacon in Arizona. And yet they do—as made evident by Ruby Tuesday, whose Bacon Cheeseburger costs $9.99 in Glendale, Arizona, which is the exact same price as the Bacon Cheeseburger at the Ruby Tuesday in Urbandale, Iowa, where bacon is more valuable and worthy of a higher price tag.

Ruby Tuesday also gets it right. For instance, the Bacon Cheeseburger at a Ruby Tuesday on the west side of Chicago costs $9.99, while the Bacon Cheeseburger at a Ruby Tuesday in Times Square costs a whopping $15.99. Clearly, Ruby Tuesday understands that food in general has a higher market value in a popular tourist neighborhood like Times Square than it does on the west side of Chicago. But it’s not enough to deploy a market-based approach only in the case of extreme examples. Common sense tells us that we can charge more for food in tourist attractions like Times Square, but it stops short of knowing the market value of bacon as an attribute in the Pacific Northwest versus the Southeast. For that kind of nuance, operators have to team with a quality data provider, and it’s worth it to do so.

In the aforementioned Pacific Northwest, the value of the term artisanal in reference to a sandwich is $6.13. In the Northeast, it’s $6.60. That’s a difference of almost 50 cents, or 8.15 percent. Put in context, that means that, hypothetically, for every sandwich that a typical restaurant sells in Connecticut at $6.13, it’s leaving almost 50 cents on the table. Over the course of a year, it’s realistic to figure the total amount of money left on the table by the same hypothetical restaurant is well into the thousands of dollars. In this situation, it seems as if what you don’t know actually can hurt you. Or, put another way: The more you know, the better. Knowing the national average value of an attribute like artisanal is great data. But if you are a chain operator, knowing where across the country that value fluctuates and by how much is what turns that data into an actionable insight.

By now, we hope we’ve left operators with a holistic understanding of the future of pricing strategies. Attribute- and market-based approaches work in conjunction with one another but are only two out of many examples of how pricing strategies might evolve. What’s certain, though, is that central to each new strategy will be the usage of big data. Data allows decision makers to make smarter and more informed decisions. In foodservice, data-driven insights can be deployed for many reasons. CPG sales teams might use data to determine the best territories for pitching their new products. Operators might use point-of-sales data to get a better understanding of their more popular menu items. Both are great ways to implement big data, but nowhere is the payoff for using data more immediate and profitable than in the case of pricing strategies. To that end, we encourage all operators today to reevaluate how they price items and avoid the costs of using outdated strategies.

Now let's move this conversation over to Twitter. Tweet us @foodgenius using the hashtag #menudata, and we'll debate these strategies with you to your heart's content. Until next time, we encourage all operators today to reevaluate how they price items and avoid the costs of outdated pricing strategies.