The Cost of Outdated Pricing Strategies


by Justin Massa, CEO and Co-founder of Food Genius |

Note: This series appeared originally from QSR Magazine in 3 parts.

Operators are leaving dollars on the table by committing to cost-plus and value-based pricing.

Part 1

Recently, I went on a road trip across the Midwest, and on that trip I consumed more than my fair share of fast food. As I darted between Burger Kings and Taco Bells, I began to notice some of the menus’ nuances: the way LTO items were prominently displayed, design elements like typeface or color, and, most interestingly, the wide variety of prices. For instance, why is Burger King’s large french fry worthy of a  $2.39 price tag while McDonalds’ large french fry sells for a cool $2.19? Why does Taco Bell sell a large fountain soda for $1.89 while the Burger King right down the street sells a large fountain soda for 10 cents less?

These small discrepancies in price are as common as apple pie in the foodservice industry, and are often the result of one or two tactics: a cost-plus pricing approach or a value-based approach. Today, cost-plus and value-based pricing are practically tired terms. Both strategies have been around for quite a while and have developed their fair share of shortcomings as the world around them has updated and innovated. One more notable and recent shortcoming of both these models is that neither have a way to take into account the massive amount of “big data” about consumer behavior and foodservice costs that is now available to the industry. Though tried and true, these models are far from sophisticated and are likely causing operators to leave large amounts of money on the table.

To understand the potential benefits of data-enhanced pricing strategies, let’s first look to an e-commerce leader that has already put similar strategies in place: Amazon.

A Business Insider article recently pointed out a few shocking statistics: That Amazon had changed the price of a wireless Internet router eight times in one day and that evidently Amazon alters prices more than 2.5 million times daily. Now if Amazon’s decision-makers were implementing either a cost-plus or value-based approach to pricing, there would be no need for this kind of scrupulous adjusting. But they aren’t. Rather, they have built systems that leverage massive amounts of data to understand more about purchase behavior than any decision maker ever could.

Elements like time of day, region, past individual consumer behavior, past aggregate consumer behavior, and so on are taken into consideration in a split second and affect what the consumer sees and how that product is priced. Obviously, Amazon’s algorithms are an extreme example of a data-enhanced pricing strategy, but it’s important to realize just how sophisticated some pricing strategies have become. Meanwhile, the food industry still depends on strategies that have been around before the invention of the computer.

The good news is that much can be borrowed from Amazon’s strategy and applied to the foodservice industry. In fact, many newer foodservice concepts are already primed to implement more sophisticated strategies. With roots in Silicon Valley and technology in their DNA, food industry start-ups like Sprig and Plated, which deliver healthy pre-made meals to busy diners, are bound to incorporate big-data insights when considering pricing (if they don’t do so already), making them all the more capable of being restaurant replacers and Millennials’ new food provider of choice. This means that, in addition to the typical brick-and-mortar competitor down the street, restaurant operators now have to worry about these start-ups, who have the technological prowess to optimize their prices instantaneously based off data that is no different than the data that is available to every restaurant operator around the country. That’s the other good news. What these technology-inclined companies are doing is not out of reach for any operator, it just requires a few lessons on the nuances of data as it applies to the food industry. That’s where I come in.

Over the next series of articles, we will be exploring a variety of alternative pricing strategies that leverage recently available data and new technology. To make things more interesting, each new approach and its key takeaways will be discussed within the context of a hypothetical restaurant that our team has, developed replete with its own menu items and pricing that is derived from a cost-plus pricing strategy. We will use this restaurant and its menu both as a way to make clear how to implement these strategies and as a vehicle for discussing their real world benefits upon implementation. Menu item pricing will be based off of food costs provided to us from Reinhart Foodservice’s powerful new suite of tools, TRACS Direct. By the end of this series, operators will be ready to implement more effective pricing strategies that allow them to determine quality inputs, analyze the data, optimize prices based off that data, and then do it all over again with a different set of inputs.

In the meantime, let us know what you think we should name our hypothetical restaurant on Twitter using the #menudata. We’ll pick back up in a few weeks with the introduction of our restaurant, its menu, and the first new pricing approach. Until then, class dismissed.

Part 2

Welcome back, class. Last we left off, we were discussing the shortcomings of a cost-plus approach to menu pricing and teasing more sophisticated strategies that have the potential to benefit operators in myriad ways. Now we are back to contextualize our case for more modern strategies through a hypothetical restaurant that we decided to name Millie’s. Think of Millie’s as a fast-casual concept, a sort of hybrid of leading fast-casual and quick-service chains like Five Guys, Wingstop, and Panera Bread. It is located on the north side of Chicago in a neighborhood with a median income of $50,000.

In order to keep the takeaways straightforward and the insights clear, we are going to focus on a few menu items that we think of as variations on standard inclusions across the aforementioned segments and avoid discussing all other specific elements of the restaurant. Those menu items are as follows:

  • Bourbon Glazed Wings (appetizer, serves four)—$10.95
  • Wisconsin Stuffed Cheeseburger (entrée)—$6.95
  • Villa Frizzoni Supreme Pizza (entrée)—$26.95
  • Roasted Vegetables (side)—$4.95
  • French Fries (side)—$2.95

As promised in the last article, the prices of the above items were derived from a cost-plus approach that is based on raw food costs provided by Reinhart Foodservice, and the items themselves were based on recipes accessed through TRACS Direct, Reinhart’s ecommerce solution. We held food cost at 25 percent and rounded to the nearest $0.95. To double check our work, we then compared these prices to those found on Applebee’s menu, which boasts a $10.49 chicken wing appetizer, and Five Guys’ menu, anchored by a cheeseburger with the exact same price tag as Millie’s cheeseburger: $6.95. Now we are going to show you how to tip things in your favor through a new approach we are callingattribute-based pricing.

In its simplest definition, 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. Determining a menu item’s value is something that can only be done through careful observation of data. To crystallize this point, let’s return to Millie’s. By consulting restaurant and menu data, we know that the average price of cheeseburgers among fast-casual and quick-service restaurants within a 10-mile radius of our Chicago location is $9.98. So already we see that there is a $3.03 disparity between a cost-plus-based price and a price that is based off the perceived value of a cheeseburger within Millie’s local competitive set. To be sure, we aren’t saying that an operator could easily increase the price of their burger by $3 without a customer noticing. Rather, we are simply shedding light on the vast difference between pricing of similar items in a close geographic area.

Given the data on average burger prices, an operator of a new restaurant could easily price their cheeseburger at $10 and have that price be aligned with a local consumer’s expectations. Doing so would increase their profit margin on that menu item by upward of 20 percent. By observing the data on an even more granular level, we discover additional insights related to pricing. For instance, we know that there are certain attributes related to a food item that correlate with an increased price. In the case of a cheeseburger on the north side of Chicago, the attributes or terms that are associated with a pricier burger are charred, bacon, beef, lettuce, and tomato. What’s noteworthy is that most cheeseburgers typically include these attributes. Which means, in some cases, the difference between burgers that cost less and burgers that cost more is not the actual elements, but the mere mentioning of those elements on the menu.

Menu items that feature longer descriptions and mention specific attributes garner higher prices, and nowhere is this made clearer than in the case of french fries. At Millie’s, a regular side of french fries costs $2.95, a price that is once again below the neighborhood average of $4.20. Now, let’s tack on a few terms that require very little additional costs and see what happens to the price. The average price for seasoned fries is $4.71, while hand-cut fries sell for $4.63. In both cases, the mere mentioning of the words hand cut and seasoned garners an almost 50-cent increase in the price. The actionable insight here is that if you are seasoning your french fries or hand-cutting them and not making mention of that, you are leaving a significant amount of money on the table every time you send out a side of fries. There’s no food costs associated with the hand-cut methodology, and seasoning certainly doesn’t cost 44 cents per serving. This is where a cost-plus pricing approach glosses over the value that your market has assigned to specific attributes of items.

uniqueAnother easy win associated with attribute-based pricing comes in the form of source labeling. Ever noticed how in every Five Guys there is a white board that features the name of the farm that grew the potatoes? Mentioning a product’s origins is no longer a tactic reserved for trendy, independent operators. Most food items purchased by a restaurant are tethered to a farm (the more local the farm is to the restaurant, the better) and it behooves all operators to mention this reality to consumers. Perhaps prominently displaying their potatoes’ origins is in part why Five Guys can get away with selling a side of regular-sized french fries for $3.19, 26 cents above the cost-plus derived price of Millie’s fries.

But you don’t always have to increase the price of an item because its attributes have a high value in your market. For example, Millie’s sells its wings for $10.95—in line with the average price of wings in its neighborhood. But a quick glance at the data reveals that operators who are charging upward of $11 for their wings are mentioning terms like glazed and dusted. While Millie’s may want to keep an order of wings under $11, it can add to the perceived value of the product by including words whose market value would push the price higher. An order of $10.95 wings sounds expensive; $10.95 bourbon-glazed wings sound delicious and like a good value.

Discerning customers can and will gauge the value of an item from how it is named and described on the menu. Emphasis on unique aspects of dishes, specific mentions of certain attributes, and references to the ingredient origins are all positively correlated with a higher price. But the nuances matter; while referencing a product’s origins seems to lead to a higher price, the same can’t be said for all attributes. Attributes like premium, artisan,charred, and hand cut all have different values depending on how they are combined with other attributes. Attribute-based pricing strategies require you to leverage external data about your competitive landscape as opposed to the purely internal data of a cost-plus approach. It’s more work, but the payoff can be significant.

Don’t just take our word for it; grocery brands and retailers have long taken advantage of the power of their brands and product attributes to push for higher prices of greater perceptions of value. In the freezer aisle of the grocery store, value supreme pizzas use words like deluxe and the works, whereas super-premium supreme pizzas use words like fire roasted and Tuscan style.

That’s all for this week’s lesson. Make sure to keep up with the conversation on Twitter using the hashtag #menudata and check back in a few weeks for our next article, in which we’ll discuss another pricing strategy that builds on attribute-based pricing and is specifically geared toward multi-location operators with units across the country.

Part 3

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.

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Justin Massa, CEO and cofounder of Food Genius, with additional reporting and research by Abigail Covington.

via QSR