Menu Optimization

After a brief period of stabilization, inflation and cost pressures have resurged for operators in 2026. To combat rising costs, operators have swapped suppliers and ingredients, cut menu items, and most commonly, raised prices. There was a period when this strategy worked—higher prices boosted 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?"

We now have our answer. Traffic is declining across most segments as consumers push back against years of cumulative price increases. Yet 42% of operators still plan to raise prices in the next year.

Many operators feel they have no choice: they've already swapped suppliers, trimmed portions, cut menu items, and reduced labor.

With costs rising and other levers exhausted, price increases feel like the only option left. But these necessity-driven hikes are being layered on top of sustained increases that have fundamentally reset consumer price expectations and exhausted their tolerance. The pricing lever that carried operators through the post-pandemic era has reached its limit.

As operators plot their next move, the twin challenge looms of protecting margins without alienating price-fatigued customers and capturing new transactions in an increasingly competitive marketplace. 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 or an unpopular but high-margin item, operators must understand their current and potential customers’ preferences, their likelihood of purchasing a menu item and each item’s role as a traffic drivers. This can be done by surveying consumers and conducting an online simulated ordering scenario using discrete choice-based analysis such as maximum difference scaling (MaxDiff) or conjoint analysis. This research method reveals critical insights that POS data alone cannot capture. If an item has been marked for deletion because it represents only 2% of sales and carries low margins, the essential question is whether that 2% comes from a unique customer base who would be lost entirely. Would those customers buy something else? Would they defect to 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 that menu can increase or decrease the incremental nature of that reach. When streamlining menus, operators may find that removing items may have a minimal impact on the overall reach (and revenue) of the menu because consumer simply order something else rather than forgo a visit. Conversely, an operator may find that cutting an unprofitable but popular item carries significant risk if it has a hidden fanbase, generates a social buzz or serves as a traffic driver that pulls customers through the door. In these cases, operators need to understand whether existing menu items can serve as adequate replacements or if a new item should be introduced 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 underperforming items. 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 critical next question operators should ask is whether the new menu item has the potential to cannibalize a current, more profitable menu item. Once cannibalization risk is determined, the operator must evaluate food and labor costs, operational complexity and pricing power. Can the new item command a premium? Does it require specialized ingredients or prep that strain efficiency? A menu addition only makes strategic sense if it expands reach, protects margins, and fits within operational realities.

Looking ahead, as operators face relentless cost pressures and the reality that price increases reached their limit with consumers, it will be critical to consider whether you can safely trim or expand the menu in ways that create incremental revenue or profit opportunities. Ensuring you’ve got the right menu to navigate cost challenges and keep your customers happy will be key to weathering a stormy 2026.

Top Chart: 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. 

Bottom Chart: 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.