The Strategic Context
Pricing has become a boardroom imperative. Input costs, tariffs, and inflation have elevated pricing from tactical execution to strategic priority. Consumers remain hyper-aware through daily purchases and constant media coverage, making value perception critical.
What the Data Reveals
In a familiar industry, Morning Consult Intelligence tracking demonstrates how promotional strategies influence consumption patterns and competitive dynamics. Our drill-down analysis reveals how small price increases can trigger significant effects. When tailored to your brand position and your current and target customers, pricing becomes a key strategic lever.
Why the Right Data Are Critical
Pricing delivers the highest profit leverage of any business decision, and market disruption creates windows to capture new segments and occasions. However, customer movement is asymmetrical. You must understand which competitors you attract customers from and who threatens your base. Success requires fast, certain information to make confident decisions under pressure.
The Path Forward
Morning Consult's analytics provide the speed and certainty executives need for high-stakes pricing decisions. Our choice modeling and competitive simulations quantify preferences, predict responses, and stress-test scenarios before implementation.
Consumer sensitivity to inflation, the high-profile discussion of tariffs, and increased political sensitivity have made pricing a central business issue in 2026.
This isn’t new. Concerns about cost of living played a meaningful role in the 2024 elections as well as the New York City mayoral election, and affordability has increasingly become a term of art in politics. Expect this narrative to continue. As Mark Zandi of Moody’s noted, "Consumer price inflation is near 3 percent, well above the Fed's inflation target, and everything points to even higher inflation dead-ahead. It didn't have to be this way." [1]
Tariffs have raised the profile of pricing even further. Increases have already affected overall U.S. price levels and, if they remain in place, are likely to continue working their way through the system. Even if the impact of tariffs proves to be more of a one-time shift rather than an ongoing source of inflation, the tariff narrative has raised the visibility of price changes. [2,3]
Executives are constantly making decisions within ongoing narratives like these, but it is never easy. In this case, both consumers and policy makers pose important challenges. The primary economic problem, however, is predicting consumer response to price changes.
The prediction problem comes at two levels. First, your industry matters. Price surprise and price sensitivity vary substantially across categories.[4] Where there is an effect, it can be significant. For example, LendingTree found that 80 percent of Americans now consider fast food a luxury.[5] CEOs, CFOs, and strategists especially need to understand these drivers.
Second, brand position and strength affect consumer response. This is core to answering the tactical pricing question: Given what consumers will spend on the category, how do we capture a greater share of that category spend? This is especially crucial to CMOs.
The final challenge is communication. Executives face a dilemma: attributing price increases to rising costs may improve consumer understanding, but it can also be a lightning ride for political scrutiny.
Overall, pricing has moved from a tactical execution issue to a strategic imperative. Our purpose here is to show how a few focused and rapidly executable tools can support clear insights and confident management decisions.
Pricing decisions serve multiple, often conflicting objectives. Market entry requires aggressive pricing to overcome incumbency advantages. Share growth demands prices that attract marginal customers without triggering competitive retaliation. Profitability optimization pulls toward higher prices and margin expansion. Brand positioning uses price to signal quality or value. Each objective implies a different price.
Behavioral economics adds further layers. Consumers exhibit reference-dependent preferences, sometimes anchoring to historical prices and competitor offerings rather than evaluating absolute value. What consumers consider a “good value” one day, can be prohibitively expensive the next. Additionally, threshold effects can produce discontinuous demand responses: $4.99 may generate substantially different purchase behavior than $5.29, despite the modest absolute difference.[6]
Consequently, traditional pricing approaches - cost-plus markup, competitive matching, value-based estimation - provide frameworks but rarely definitive answers.
While pricing has always been hard, and is becoming still more challenging, Morning Consult has powerful tools to help executives navigate.
Understanding the current state of consumer demand
Some tools help us understand how consumer decisions are being made. These provide context for what your strategy and tactics need to accomplish. Two stand out.
Category entry point analysis maps the triggers that determine whether consumers are in-market for your category or brand at all. This is a fundamental issue at any time but takes on new importance when household budgets become materially tighter. For example, a QSR meal turns into a higher end casual meal or vice-versa, or dining out may shift to more in-home occasions.[7]
Revealed-Preference Analysis tracks actual behavior: purchases, trade-downs, deferrals. Through surveys and other data, people tell us what happened, and some of the why. Insights are grounded in demonstrated choices.[8]
Deciding what to do about it
The ultimate business question is never “What is the world like?” It is inevitably “What should we do?” How can pricing and other tactical levels be modified to gain an edge?
Again, two tools stand out.
Gabor-Granger Pricing varies price systematically and measures purchase intent, to map out demand. This brings us closer to predicting what will happen. It estimates own-price effects within a simplified world that focuses on your product or service, abstracting away from others’ offers and competitive response. This is incredibly fast and powerful in existing markets with well understood products.
Understanding "what is" is important,
but pricing tools take this to the next level of decision intelligence,
guiding executives on "what to do."
Conjoint Analysis is more comprehensive. It decomposes products into attributes. Utility estimates enable share simulation. Set competitor prices, and the model predicts shares, revenue, and profits. Because it lends itself to simulating multiple scenarios within a specific competitive context, conjoint provides a means to see how consumers respond to your offers, whom you might attract customers from, or lose them to, and how your brand and position affect your pricing power.
We’ll focus here on the ways the conjoint based pricing tools provide insights in a particular setting.
Morning Consult MCI data shows acute pressure and significant change in the 2025 restaurant industry.
Major chains responded with divergent strategies.[9] Some raised menu prices cautiously, while others introduced value platforms. Several repositioned their offerings. The variation reflects different views and uncertainty about elasticity, substitution patterns, and competitive response.
The number and variety of these offers is evident from Morning Consult’s MCI data, from which we can estimate relative changes in consumption in a category. While these are not comprehensive, we see a proliferation of offers in QSR, and, after some time, substantial growth in consumption quarter to quarter. We also see initiatives by near-competitor fast casual restaurants, such as Chili’s and Applebee’s.
One key factor for executives to consider is what fits their own positioning, and whether and how competitors will adapt.
"While competitors can certainly price below our 3 for Me offer, it is very difficult for them to replicate the total value proposition given the amount of time and investment we have put into improving the experience." - Kevin Hochman, CEO, Brinker International
Another factor to consider is: where will it end? In the offers mapped out in the figure, we eventually see a settling into a new normal, with platforming of the value concept (e.g. McDonald’s McValue), versus a sequence of limited time offers.
Competitive intensity makes restaurants an instructive case study. That there are so many moving parts makes it extremely valuable to have clear and accurate analytical tools to evaluate options.
Category: The category’s characteristics stress-test pricing frameworks: high purchase frequency provides rapid market feedback, visible pricing reduces consumer information asymmetries, and distinct occasions create segmentation opportunities.
Competitors: The competitive landscape featured distinct positioning strategies. For example, here we will look at two QSR brands and a fast casual chain. Quick Service A and B operated at similar price points for core offerings. Fast Casual offered premium items at roughly twice those levels. Note: we lightly disguised the specific brands both because they are generally representative of their sub-categories, and our analyses here illustrate generally applicable points, not purely brand-specific recommendations.
Tactics: In the few last years, many QSR and Casual brands launched pricing initiatives, as seen in the timeline above. Quick Service chains initiated several new bundled offerings, including combination meals pairing burgers with sides and beverages at promotional price points. Some Fast Casual braunds implemented an aggressive promotional strategy, narrowing the price gap with QSR competitors.[10]
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Three Stylized Offers, 2024-2025 |
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QSR-A |
QSR-B |
Fast Casual |
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Choose one of two sandwiches, plus 4-piece chicken nuggets, small fries, and small soft drink |
Choose one of three sandwiches, plus 4-piece chicken nuggets, small fries, and small soft drink |
Customers select an appetizer, an entree, and a non-alcoholic beverage for a single price |
Models: Morning Consult conducted a study in mid-2025 modeling competitive dynamics among three stylized restaurant brands: two quick service restaurants (QSR) and one fast casual chain.
Properly specified choice models enable executives to evaluate strategic alternatives before committing resources, reducing both execution risk and time-to-decision. While we did not work with the companies on these specific offers, the model provided a basis for us to predict outcomes and test against market observations.
Market results roughly validate our predictions, as we show later. For example, industry reporting confirmed that a fast casual chain of the type we modeled increased traffic by approximately 10 to 15 percent, in part using a promotion like the one we modeled.
The conjoint analysis generated individual-level utility estimates for each respondent across all brands and price points, enabling construction of full demand curves. The curves reveal not just overall price sensitivity but the shape of demand response across the price spectrum.
Preference shares represent relative preference, not literal market share. In particular, they model preference assuming equal distribution and availability. Still, they indicate directionally how market share would move in response to price changes. An X percent increase in preference share typically approximates an X percent directional market share change, though the actual level of sales depends on distribution, awareness, and operational factors of each competitor.
Quick Service A (lower elasticity, less substitutable, slightly premium) exhibits moderate own-price elasticity, with demand declining steadily, but not rapidly, as bundle prices rise. The roughly symmetric responses around any starting point indicate neither strong premium nor strong discount positioning. If anything, results suggest a slight premium position vs its closest competitor.
Quick Service B (higher elasticity, more substitutable, more promotion-sensitive) slopes more steeply, reflecting greater price sensitivity. This reflects value positioning: Quick Service B gains more revenue from price cuts than it loses from equivalent increases, at least around current market prices.
Fast Casual displays the most inelastic demand when compared to A and B. At baseline 11.49, Fast Casual commands roughly 35 percent preference share. A promotional price of 9.99 can increase preference shares to nearly 40 percent - a substantial gain but proportionally smaller than QSR responses to comparable percentage changes. Premium pricing at 12.99 reduces share only to approximately 30 percent. This shows the distinct position of fast casual: when a patron wants to sit and eat more slowly, a small price increase will not drive them to QSR, and a small increase will not drive them away.
Our discussion here is focused on what demand tells us about strategic options. Obviously cost plays a key role as well. In practice we can and do model contribution margins to probe plans more fully, but our intent here is to focus on price, because consumers’ response, which lies outside the company’s
direct view - unlike labor, food, real estate, and advertising costs - is the issue for which executives need the most external insight.
Costs are visible to executives. It is demand, and consumer response,
where external insights have the greatest potential contribution.
Figure 5.1: Preference Share as a function of price for Quick Service A, Quick Service B, and Fast Casual.
Demand insights in brief: Quick Service A and Quick Service B exhibit highly elastic cross-price effects: when one changes price, share flows rapidly to the other. Fast Casual shows muted cross-price effects with QSR brands, reflecting category separation. These patterns inform strategy: QSR brands must anticipate immediate competitive response, while Fast Casual operates with greater pricing autonomy.
The conjoint simulation enables systematic analysis of unilateral price changes and their competitive consequences.
Strategic Group Dynamics
The competitive structure reveals distinct strategic groups. In simulation, customers switch between QSR A and QSR B based on promotional offers and relative value. A distinct substitution frontier exists between QSR and fast casual however, such that consumers trade between categories based on occasion and budget.
This aligns with classic concepts of strategic groups within industries, where rivalry intensity varies based on competitive positioning and customer segments.
Three scenarios illustrate these points. Each represents plausible strategic moves from baseline positions.
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Scenario |
Action Taken |
Key Outcome |
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Quick Service A – Price Reduction |
Quick Service A reduces price to 5.29, matching Quick Service B. |
Quick Service A increases its attractiveness by about 22 percent, gaining substantially more share and drawing over 90 percent of these gains from B. Most shifts are with the head-to-head competition. |
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Quick Service B – Price Reduction |
Quick Service B reduces price to 4.79, opening a gap below Quick Service A. |
Quick Service B increases its attractiveness by around 10 percent; approximately 67 percent of new patrons come from A and about 33 percent from Fast Casual. |
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Fast Casual – Promotional Pricing |
Fast Casual reduces price to 9.99, narrowing the premium over QSR. |
Fast Casual improves its attractiveness by roughly 15 percent and draws new customers nearly evenly from QSR A and QSR B. Fast Casual stands distinct from QSR as a group, and draws from the group broadly, not one particular player. |
Scenario 1: Quick Service A Price Reduction
Baseline: Quick Service A at 5.79, Quick Service B at 5.29, Fast Casual at 11.49
Action: Quick Service A reduces price to 5.29, matching Quick Service B
Result: Quick Service A gains 5.8 percentage points of preference share, rising from 26.1 percent to 31.9 percent; we would expect around a 22-23% (32/26) improvement in sales (of this meal offer), all else equal.
Take-away: The share gain comes entirely from Quick Service B. Fast Casual remains unchanged. This demonstrates tight competitive coupling within QSR: consumers view QSA and QSB as close substitutes, switching based on relative prices. The casual dining category operates independently, largely unaffected by QSR price competition within this near-normal range.
Scenario 2: Quick Service B Price Reduction
Baseline: Quick Service A at 5.79, Quick Service B at 5.29, Fast Casual at 11.49
Action: Quick Service B reduces price to 4.79, opening $1 gap below Quick Service A
Result: Quick Service B gains 4.0 percentage points, rising from 39.1 percent to 43.0 percent
Take-away: The gain sources shift: 66.8 percent comes from Quick Service A, while 33.2 percent comes from Fast Casual. This asymmetry reveals important strategic information. Quick Service B, already positioned as a value leader at baseline, appears to gain more from Fast Casual when deepening its discount.
The pattern suggests that aggressive value pricing attracts not just QSR switchers but also casual dining customers trading down for affordability, and possibly simply customers who are interested in deals and discounts. The much lower priced QSR option with B at 4.79 has shifted the equilibrium, maybe identifying a new consumer niche.
Scenario 3: Fast Casual Promotional Pricing
Baseline: Quick Service A at 5.79, Quick Service B at 5.29, Fast Casual at 11.49
Action: Fast Casual reduces price to 9.99, narrowing premium over QSR to approximately 4.50
Result: Fast Casual gains 5.1 percentage points, rising from 34.8 percent to 39.9 percent
Fast Casual draws customers relatively evenly from both QSR brands: 42.6 percent from Quick Service A, 57.4 percent from Quick Service B.
Take-away: The symmetric cannibalization confirms Fast Casual's positioning as distinct from either specific QSR competitor. The promotional price makes Fast Casual accessible to price-conscious QSR customers in general, drawing from both.
The scenarios demonstrate a fundamental principle: in tightly competitive markets, pricing decisions create predictable share transfers. Executives equipped with these estimates can evaluate pricing alternatives ex-ante, comparing volume gains against margin compression before implementing strategies.
Anticipating competitive reaction matters as much as estimating own-price elasticity. Isolated demand curves miss the strategic interdependence that determines actual outcomes. Conjoint allows us to simulate effects in a market context.
Here we focus in more detail on the question of what happens when mid-tier firms like fast casual restaurants price aggressively. Can a company win by discounting to become more accessible at the low end?
Benefits (might) come from several sources, including retaining current customers (occasions) who might otherwise trade down under budget pressure, as well as picking up entirely new customers and occasions not previously served.
In late 2024, a fast casual chain did just this, introducing a discounted offering and a reduction from baseline, marketed with messaging directly comparing value to fast-food alternatives.
The conjoint model succinctly predicted preference share would increase from approximately 35 percent to 40 percent, suggesting a 14 percent relative increase in realized market share, all else equal. Indeed, one fast casual chain reported same-store sales growth of 31 percent in fiscal Q2 2025, driven by traffic increases near 20 percent. Later in the year, the chain saw a 13% traffic increase. [11,12]
The 31 percent actual vs. 14 percent predicted outperformance reflects marketing factors beyond pure price elasticity: marketing effectiveness, operational improvements enabling capacity to handle increased traffic, and social media amplification through viral content.
Media coverage of the promotion emphasized its strategic importance. As reported by Restaurant Business Online, the CEO attributed success to "a consistent focus on core menu value, rather than a reliance on temporary LTOs or promotions to drive traffic."[13] The value platform became sustained positioning rather than short-term tactical discount.
While same-store sales increased, this reflects both traffic gains and favorable menu shifts. The promotional item likely attracted customers who then ordered higher-margin appetizers and beverages. This sustained performance suggests the promotional price has expanded the customer base.
Another question that comes up in today's environment is, when common pressures such as supply chain or labor costs affect everyone, how will consumers react as almost all brands reprice?[14]
Specifically, it makes sense to ask whether parallel price increases preserve competitive position. Intuition suggests that if all competitors raise prices proportionally, relative sales shares might remain stable while all brands improve margins. However, the conjoint analysis demonstrates this intuition might be incorrect in the near term, if price increases in the short term can better match certain brands with premium positioning.
We will circle back to some caveats and interpretations, but for the moment, let’s play out the model analysis.
Scenario: Consider a scenario where all three brands implement price increases as you might see when general costs rise: Quick Service A from 5.79 to 6.29 (+0.50, 8.6 percent), Quick Service B from 5.29 to 5.79 (+0.50, 9.5 percent), and Fast Casual from 11.49 to 12.49 (+1.00, 8.7 percent). The percentage increases are similar, and the absolute dollar gaps between brands remain fairly close.
Share Outcomes:
The competitive positions shift substantially. Overall, A wins.
Quick Service A rises in preference. Quick Service B loses its leading attractiveness despite maintaining the lowest price among all three brands. Fast Casual loses share despite its price increase being only proportionally equivalent to QSR increases.
Quick Service A benefits because the parallel increase makes it relatively more attractive compared to Fast Casual. Simultaneously, Quick Service A maintains its 0.50 gap with Quick Service B, so it loses minimal share to its direct QSR competitor.
The demand curve analysis earlier in section 5 revealed Quick Service B's customers respond more elastically to price changes than Quick Service A's customers. When Quick Service B raises price, it loses customers to Quick Service A at a higher rate than Quick Service A loses customers when A moves its prices up. The roughly parallel shifts bring the implications home. Even though we assume everyone stays in-market, the new pricing leads to different (relative) value-to-price rations, and A wins in this game across the three competitors.
In the short run at least, premium brands may do better
when everyone is shifting prices upward.
There are caveats to this particular conclusion, which is a bit of an off-label use of the conjoint model to develop an insight.
The model assumes a stable set of consumer preferences and choice options, and prices stated in a consistent unit of value. In contrast, if consumer prices are changing across categories and real discretionary income falls, especially for (e.g.) QSR buyers, some may leave the category.[15] Conversely, in a true, very broad based monetary inflation where all prices and incomes are moving in parallel, real relative prices across our three competitors may be in effect unchanged.
Reality is some mix of these factors. On the firm side, some industries indeed see more pressure on labor and input costs, leading to correlated real-dollar changes in costs and likely prices.[16] On the consumer side, we believe consumers are trying to sort out what price changes are long term vs short term, how their usual brand compares to what another brand may be doing, as well as their own household budgets. They will sort these out over time, but on any day, their reactions are likely sticky to past perceptions and preferences. In that way, we expect to see the kind of near-term shifts predicted by the conjoint model, at least in direction.[17]
In this, the conjoint results provide a hypothesis to investigate, and (maybe) a little (near-term) comfort for the strongest brands.
Pricing has become central to executive decision-making because external forces - tariffs, political scrutiny, consumer financial strain - have raised price visibility to consumers and compressed the margin for error.
The inherent difficulty of pricing stems from multiple goals: margin versus volume, short-term revenue versus long-term brand equity, competitive positioning versus absolute profitability. Traditional frameworks - cost-plus, competitive matching, value-based estimation - provide structure but rarely definitive answers because they fail to model the strategic interdependence that characterizes competitive markets.
Morning Consult's toolkit addresses these challenges through complementary methodologies. Gabor-Granger pricing suits rapid tests. Behavioral tracking validates stated preferences against actual choices. Conjoint analysis and competitive simulation model the full strategic environment, estimating not just own-price effects but complete competitive response structure.
The quick service and fast casual case study demonstrates how these tools, conjoint in particular, provide both strategic insights and tools to predict outcomes. This is a strong foundation for executive decisions.
The current environment rewards organizations best in price analytics infrastructure. The alternative, relying on competitive signaling, cost-plus rules, or reactive adjustments to quarterly results, produces systematic errors in both direction and magnitude. By construction, these are laggard approaches.
In contrast, executives who build capabilities to model demand, simulate competition, and measure outcomes will navigate pricing complexity more effectively than those who treat pricing as tactical execution rather than strategic discipline.
Methodology Note
Conjoint insights here are based on a sample of 2,271 US consumers in April 2025. Data insights were developed with MC AI-based analytics tools to find key strategic insights and rapidly develop analytic insights, market simulations, simulator tools, and context from trade press, business news, and economic commentary.
Endnotes
[1] Mark Zandi quoted in Fortune, "'It didn't have to be this way': Top economist warns affordability crisis will continue as tariffs and immigration crackdown send inflation higher" (November 23, 2025).
[2] Federal Reserve Bank of St. Louis, 2025, "How Tariffs Are Affecting Prices in 2025," On the Economy (October 17, 2025).
[3] Federal Reserve Bank of Boston and Morning Consult, 2025, “Who Will Pay for Tariffs? Businesses’ Expectations about Costs and Prices.”
[4] Morning Consult, 2025, “Morning Consult Price Surprise Index Rises for Fifth Consecutive Month; Price Sensitivity Increases Across Essentials Like Groceries and Clothing.”
[5] LendingTree survey cited in Mashed, "The Only Recap Of Chili's Major Resurgence You Need" (December 2025).
[6] For a discussion of how context, including economic pressures can affect the consumer decision process in terms of use triggers and points of comparison, see Morning Consult Pro, December 2025, “The Context Advantage: How Economic Reality Shapes Consumer Choice and Reveals Your Best Path To Growth.”
[7] Morning Consult Pro, ibid.
[8] For more detail on Morning Consul's approach to measuring revealed price preferences, see Morning Consult Pro, “A New Framework for Evaluating Supply Chains and Consumer Inflation” (August 2022).
[9] Multiple sources document divergent restaurant pricing strategies in 2024-2025, including: Restaurant Business Online, "Chili's caps an epic comeback with 31% same-store sales growth" (January 29, 2025); CNN Business, "Chili's take on the Big Mac is beating McDonald's at its own game" (August 14, 2024); Restaurant Dive, "How Chili's boosted comparable sales by 31%" (January 30, 2025); TheStreet, "Major restaurant chain's $10.99 burger deals McDonald's, Wendy's blow" (November 2024).
[10] Documentation of bundled offerings includes Restaurant Business Online coverage of McDonald's $5 meal deals and value platforms; CNN coverage of Chili's $10.99 "3 for Me" promotion including Big Smasher burger; multiple outlets covering Burger King value bundles and promotional pricing during 2024-2025.
[11] Restaurant Business Online, "Chili's caps an epic comeback with 31% same-store sales growth" (January 29, 2025).
[12] Restaurant Dive, "Chili's dramatic sales growth continues with 13% traffic jump" (October 29, 2025).
[13] Restaurant Dive, ibid.
[14] Note that the discussion here is how consumers respond to similar changes across companies. The other side of this question, namely how firms anticipate responding to a common cost shock (specifically tariffs) is discussed in Federal Reserve Bank Boston and Morning Consult, Sept 2025, “Who Will Pay for Tariffs? Businesses’ Expectations about Costs and Prices.” The results there suggest that the “firms change prices in rough parallel” hypothesis used here is a good starting point for simulating what consumers may see.
[15] Morning Consult, “The Context Advantage,” op. cit.
[16] Federal reserve Bank of Boston and Morning Consult, op. cit.
[17] This harkens back to Robert Lucas, 1972, J. Economic Theory, “Expectations and the neutrality of money.” The core idea is that at any point in time, consumers have some but not all information. For example, perhaps a price change is transitory, or perhaps it’s permanent; perhaps it’s local to my situation, or perhaps it’s pervasive. In our case, I may see from the menu board that QSR A has increased, but not know for sure about B or Fast Casual. It may take a while for full information to percolate through. In that interim, we hypothesize that behaviors from the earlier demand curves carry over, and (in this example) the stronger brand does better for at least a while.