Maximize profits while minimizing price hikes

Although inflation is cooling, operators are continuing to grapple with mounting cost pressures from rising food costs, wages, rent and other overhead expenses heading into 2024. With many consumers reaching their limit on price and questioning the overall value of restaurant dining, what else should operators be doing to minimize price hikes while protecting margins? 

By Lori Rakoczy, Associate Principal

Consumers are showing a growing resistance to escalating prices, impacting traffic and customer perceptions. With little room left to raise prices, operators should be examining their menu mix to ensure it’s optimized in a way that balances their costs with the revenue potential of menu items that will maximize their customers’ satisfaction.

Although inflation is cooling, operators are continuing to grapple with mounting cost pressures from rising food costs, wages, rent and other overhead expenses heading into 2024. To combat rising costs, operators have swapped suppliers and ingredients, cut menu items and operating hours, and most commonly, raised prices. Looking ahead, operators are still planning on turning to price hikes to boost margins, likely because they feel they’ve made all the cuts they can possibly make to stay afloat, and consumers have thus far have been largely resilient to price hikes. However, as operators plot their next move, the twin challenge looms of retaining a customer base who have likely swallowed all the price increases they can handle and finding new transactions at the expense of the competition.

Raising prices seemed to be working. Higher prices were boosting sales figures, and consumers showed a willingness to pay those prices, for longer than expected. As prices ticked up, the question on everyone’s mind was, “how much more can prices go up before people stop going to restaurants?”  

With traffic stalling and negative consumer sentiment around price hikes and added service fees, we may finally have the answer we feared was coming.

Further, nearly a quarter (23%) of consumers say if menu prices go up by just $1.00, they would no longer order from that restaurant. This jumps to 34% when viewed in the context of fast-food restaurants.   

With many consumers reaching their limit on price and questioning the overall value of restaurant dining, what else should operators be doing to minimize price hikes while protecting margins? Operators should be asking themselves if they have the optimal menu mix. Specifically:  

  • Does the menu maximize consumer reach and revenue?  
  • Can I streamline the menu without sacrificing sales and profits?  
  • Or, do I need to expand it to find new transactions?
  • Which items can I cut? What are the risks of removing menu items? Will I lose customers?
  • If I add items, how will my sales-mix shift? Will it shift in profitable ways?  
  • How does the cost of executing the menu (e.g., labor, ingredients, etc.) impact profitability?  

An obvious first place to start is by analyzing the POS data and simply cutting out menu items that aren’t top sellers or profitable. But that comes with a risk. Relying on POS data alone means ignoring customer sentiment around the current menu and their expected reaction to changes in the menu—namely, how they would respond if their go-to favorite items are missing the next time they come in the store. While analyzing POS data should certainly be part of strategic menu design, it’s not the only part and, in fact, is just a basic first step in analyzing the opportunity. Layering in a risk assessment of item removal or expansion is crucial to reducing the risk of failure for any major menu move.  

To mitigate the risk of removing an unprofitable, fan-favorite item or, on the opposite end, an unpopular but high-margin item, operators must understand their current and potential customers’ preferences, their likelihood of purchasing a menu item and the role the items play on the menu as traffic drivers. This can be done by surveying consumers and conducting an online simulated ordering scenario using discreet choice-based analysis such as maximum difference scaling (MaxDiff) or conjoint analysis. This research method is akin to finding a needle in a haystack. If an item the POS analysis has marked for deletion because it is not highly profitable and represents only 2% of sales, for example, the question must be answered as to whether that 2% is coming from a unique customer base. If so, it is crucial to understand how this customer would respond. Would they buy something else? Would they leave for a competitor? If so, how big of a hit would you be taking from a traffic loss standpoint?

At the basic level, a simulated ordering scenario analysis, such as MaxDiff or conjoint analysis, will tell operators the number of consumers they can reach with their current menu and how changes to the menu can increase or decrease the incremental nature of that reach. When operators are looking to streamline menus, they may find that removing items may have a minimal impact on the overall reach (and revenue) of the menu because a consumer is likely to just order something else rather than forgo a visit. Or an operator may find that removing an unprofitable but popular item carries the risk of losing customers because it’s an item that generates buzz or has a hidden fanbase and, thus, pulls people into the restaurant. In this case, operators would want to understand whether they have items currently on the menu that serve as adequate replacements or if a new item should be considered in order to extend the reach of the menu without cannibalizing the most profitable items already available.   

Operators can also use this type of choice-based analysis to understand how a new item would perform alongside the current menu or as a replacement for a low-performing item. For example, let’s say the menu optimization analysis shows that a new menu item has a relatively high likelihood of purchase when added to the current menu. Should an operator move forward to market testing and add it to the menu? Maybe. The next question operators should ask is if the new menu item has the potential to cannibalize a current, more profitable menu item. Once this cannibalization risk is determined, the operator must also consider the food and labor costs, and whether they can charge a premium for the new item.  

Looking ahead, for operators whose traffic remains at risk given the nature and level of price hikes over the past year and a half, it will be important to consider whether you can safely trim back or must expand the menu in ways that create incremental revenue or profit opportunities. Ensuring you’ve got the right menu that can navigate cost challenges and keep your customers happy will be key to weathering what could be a stormy 2024.


MaxDiff methodologies enable us to simulate and forecast the impact of implementing different menu-mix scenarios. This particular scenario was one where a client was looking to test which menu item in their innovation pipeline extended the incremental reach of their menu the furthest. Combining this metric with additional contextual insights helps identify whether a new menu item is truly additive to the current menu mix.


This methodology also enables a wholesale search for the most efficient menu within size constraints. For example, let's say we are testing a menu that presently has 12 items on it. We tested those 12 items in addition to another five potential new items to consider. In this instance, it was decided that for operational efficiencies sake that the menu needed to be simplified and the customer desired to reduce this section of the menu to eight items. The simulator can identify which combination of the 17 items can satisfy the most people. By comparing the reach of the original menu to the recommended menu, we can measure the potential risk to customer satisfaction by this planned reduction.

Base: 2,000 consumers 
Q: Now, imagine you are visiting "X" restaurant. Which of the following menu items is the one you would be most likely to purchase and which one would you be least likely to purchase? Even if you do not see your favorite selection in the list of four, still select the one you would be most likely to purchase of the four choices in that set. You will be given an opportunity to select other items you refer more in later rounds of the exercise. 


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