Category: Industry Trends

Restaurant peak season staffing is one of those problems that looks like a headcount problem from a distance and a systems problem up close.

Every summer, operators face the same math: more covers, more dayparts, more pressure — and the same constrained pool of available labor to cover it. The instinct is to hire more people. Sometimes that’s right. But the operators who consistently perform well during their busiest months aren’t just the ones who staff up the fastest. They’re the ones who think harder about where their people are deployed, how their systems absorb front-of-house pressure, and how they build a staffing model that doesn’t require everything to go right in order to hold together.

Here’s what that looks like in practice.

The Labor Market Doesn’t Get Easier in Summer

According to the National Restaurant Association’s 27th annual Eating and Drinking Place Summer Employment Forecast, restaurants are projected to add 490,000 seasonal jobs this summer, making the industry the second-largest source of seasonal employment in the country, behind only construction. But the conditions operators are hiring into haven’t gotten friendlier. 

The NRA’s 2025 State of the Restaurant Industry report found that 77% of operators say recruiting and retaining employees is still a leading challenge, and that pressure doesn’t ease when summer volume ramps up. The truth is, it compounds. Corporate sets the headcount budget and scheduling guardrails. Regional operators own the execution problem when those budgets don’t stretch to match what summer actually demands. 

The result is a familiar tension: more covers moving through locations that are already running lean, managed by a mix of returning staff and seasonal hires who are still finding their footing. The question at the end of the day is how to structure the operation so that it performs regardless of the challenges.

Seasonal Hires Belong in the Right Roles, Not Just Available Ones

Here’s a staffing mistake that plays out every summer across multi-unit operations: a new seasonal hire gets put on the register because that’s where the immediate coverage gap is. They’re slower, they make more errors, and every fumbled order adds to the line behind them.

The instinct is understandable. You have a body, and you have a gap—you fill it. But new hires have the highest error rates and the steepest learning curves, and the register during a summer lunch rush is one of the highest-stakes, highest-visibility roles in the building. Putting inexperienced staff there doesn’t solve the throughput problem. It compounds it.

The smarter deployment is to assign seasonal and newer hires to roles where the risk of error is lowest and the need for execution speed is highest: food running, bussing, expo support, lobby management. These roles contribute directly to throughput and guest experience without putting new team members in positions where a slow transaction or a misheard order backs up the entire front of house.

That redeployment logic only works, though, if your experienced staff aren’t pinned to the counter. Which is where the technology question becomes a staffing question.

Kiosks Change the Labor Equation at the Counter

When kiosks are handling a significant share of order intake, the staffing equation at the front of house shifts. Counter staff don’t disappear—they just move. And where they move is the decision that separates operators who get real leverage from their kiosk investment from those who just have kiosks in their lobby.

According to Restaurant Dive’s coverage of major QSR kiosk deployments, restaurants that feature kiosks redeploy labor so employees can focus on preparing food, reducing the need for front counter staff to take orders. The value isn’t just labor reduction, it’s labor reallocation toward the roles that actually move throughput during a rush.

Bite’s partnership with Urbane Cafe is a practical example of what this looks like at scale. Through their kiosk deployment, Urbane Cafe has been able to shift team members away from order-taking and toward the guest-facing hospitality roles that define the brand experience. It’s a reallocation in practice that makes a real-world difference in the guest experience and their bottom line. 

There’s a compounding benefit during summer specifically: Bite kiosks deliver 99% order accuracy regardless of volume. During the weeks when your most experienced staff are stretched thin and newer hires are filling gaps, that consistency matters. 

Cross-Train Before You Need To

One of the clearest operational levers for peak season isn’t hiring, it’s preparation. With 77% of operators citing recruiting and retaining as a leading challenge, per the NRA’s 2025 State of the Restaurant Industry report, most operations are heading into summer already running below their ideal staffing depth. Cross-training is the primary way to build flexibility into a team that may not be at full strength when volume peaks.

For multi-unit operators, the timing of cross-training matters as much as the practice itself. Cross-training done in May, before summer volume ramps up, builds the flexibility your locations need in July. Cross-training attempted during a peak rush is training under duress. It’s slower, less effective, and more likely to create the errors you were trying to prevent.

The practical implication looks like this. Identify your highest-risk coverage gaps by location before peak season and run cross-training against those specific gaps. Which roles go sideways first when volume spikes? Which team members are closest to being capable in those roles with a bit of preparation? Those are the investments that pay off when it matters.

Schedule Against Data, Not Last Year’s Anecdotal Memory

Operators who build their peak season staffing plans around a general sense of “summer is busy” rather than actual daypart-level data are solving the wrong problem. Summer volume isn’t uniform. It’s specific. Tourist-heavy locations see patterns that commuter corridors don’t. Weekend dinner service in June looks different from weekday lunch in August. The locations that struggle during peak season are often the ones scheduled for average expectations rather than the actual demand their specific location and daypart combination generates.

Transaction data by location, day of week, and daypart is the most actionable staffing tool that most operators aren’t fully using. Where does ticket time consistently fall apart? Which locations are running thin coverage during their highest-volume windows? Which dayparts are generating more orders than the current staffing model can absorb cleanly?

Bite’s Sales and Analytics Dashboard surfaces exactly this data—location-level and daypart-level transaction visibility that gives corporate and regional teams the information to schedule more precisely against actual demand. The goal isn’t to staff for the average week. It’s to staff for the hard weeks without blowing the labor budget on the easy ones.

Build for the Hard Weeks, Not the Best-Case Scenario

Peak season staffing plans that only work when everything goes right aren’t plans—they’re optimistic projections. Someone calls out. A seasonal hire doesn’t show. A location gets hit with an unexpected volume spike on a Tuesday. The operations that hold together under those conditions aren’t the ones with the most people on the schedule. They’re the ones with the most flexibility built into the model.

That flexibility comes from a few places: cross-trained staff who can cover multiple roles without a full retraining cycle, kiosk coverage that doesn’t depend on who showed up that morning, and scheduling visibility that surfaces gaps before they become a problem on the floor. It also comes from being honest about where your single points of failure are—the roles, the locations, and the dayparts where one staffing problem tumbles into a guest experience problem.

Peak season tests every part of your operation—staffing most of all. The operators who perform consistently during their busiest months have figured out that it’s not really a headcount problem. It’s a deployment, technology, and planning problem. Get those three things right, and the headcount you have goes a lot further.

Peak season fills seats. But filling seats doesn’t automatically mean better margins. For multi-unit operators trying to maximize restaurant revenue during peak season, that gap is where the real work happens.

The operators who grow revenue during their busiest months have figured out something important: volume creates opportunity, but only if your systems are built to capture it. More covers moving through your locations generate more chances to grow the check, introduce a premium add-on, and push a high-margin item. Miss those moments consistently across hundreds of orders, across dozens of locations and you’ve left meaningful revenue on the table during the period you could least afford to.

Here’s how the best operators close that gap.

High Volume Is When the Human Upsell Breaks Down

There’s a counterintuitive reality about peak season that most operators recognize but rarely address directly: the busier your locations get, the less reliable your staff-driven upselling becomes.

When a line stretches to the door, and a team member is focused on moving guests through as fast as possible, suggestive selling is the first thing that goes. It’s not a training failure—it’s physics. A cashier managing a lunch rush doesn’t have the bandwidth to work through a thoughtful upsell opportunity for every order. They take the order, process the payment, and move on. It’s the right call for throughput. It’s a quiet revenue leak at scale.

This is precisely why peak season is the highest-leverage moment for kiosk upselling. The kiosk doesn’t experience a lunch rush the same way a team member does. It surfaces the same well-configured upsell prompt on the 400th order as it did on the first, consistently, without fatigue, and without skipping steps when the lobby fills up. That consistency is where the revenue case for kiosk technology is most concrete.

What Kiosk Upselling Actually Does to the Check

The check lift data on kiosk ordering is well established at this point. Industry operators report average check increases from kiosks ranging from 15 to 30 percent, depending on whether the kiosk experience is optimized for speed of service or upselling, according to QSR Magazine’s coverage of operator deployment data. 

The act is straightforward. Kiosks surface add-on prompts at the moment of highest purchase intent—after the main item is selected, and before the order is confirmed. They don’t rely on a team member remembering to mention the side, the upgrade, or the seasonal add-on. They do it every time, for every order, based on what the guest has already selected.

Yum Brands CFO Christopher Turner said in a 2023 earnings call: “Kiosks not only drive a higher check compared to our traditional front counter, but also drive higher margins through operational efficiencies and generate new opportunities to leverage customer data and create personalized ordering experiences.” 

Restaurant Dive’s coverage of that call is worth reading in full for the broader context on where major chains are placing their bets. 

Bite operators consistently see 20%+ average check lift across their kiosk deployments—a figure that reflects both upsell attachment and the broader effect of guests spending more time with the menu when they’re in control of the ordering experience.

The Upsell Logic Has to Be Built for Performance, Not Just Presence

Not all kiosk upselling is equal. A kiosk that surfaces a random add-on, or promotes items without regard for contribution margin or prep time, isn’t capturing revenue—it just adds noise to the ordering experience.

The configuration of the upsell sequence matters enormously. During peak season, when kitchen bandwidth is constrained and ticket time is a variable you can’t afford to ignore, the items you’re promoting at the kiosk need to pass two tests: they need to be high-margin, and they need to be fast. A summer LTO that takes four minutes to prep should not be the featured upsell during the lunch rush. A high-attachment add-on with a strong contribution margin that comes off the line in under a minute should be.

This is the problem Bite Lift is built to solve. Rather than static upsell rules configured once and left alone, Bite Lift uses AI to match the right add-on to the right order at the right moment. It’s the difference between an upsell sequence that was smart at setup and one that stays smart as your menu, your traffic patterns, and your guest behavior evolve across the season.

For multi-unit operators, the additional value is consistency. Upsell logic configured at the brand level performs the same way at every location.

Use Your Peak Season Data Before the Season Ends

Peak season generates more transaction volume than any other period, which means it also generates more data. Operators who aren’t actively mining that data mid-season are missing a competitive window that closes when traffic normalizes in the fall.

The most actionable analysis is straightforward: pull your item-level sales mix, your upsell attachment rates, and your daypart performance by location. Look for the gaps. Which items are being promoted but underperforming on attachment? Which locations are seeing strong check lift and which aren’t—and what’s different about each? Which dayparts are converting on upsell prompts and which are seeing guests skip past them?

Bite’s Sales and Analytics Dashboard surfaces this data at the org and location level, giving corporate and regional teams the visibility to make configuration adjustments mid-season rather than waiting for a post-mortem. The operators who come out of summer with better margins aren’t the ones who reviewed the data in September. They’re the ones who acted on it in July.

Peak season is the highest-leverage moment to close the gap between traffic and revenue. The volume is already there, but are the systems configured to capture it on every order, at every location, across every daypart? If you’re ready to see what that looks like in practice, request a demo, and we’ll show you how Bite operators are doing it.

Summer doesn’t sneak up on restaurants. Operators know the volume is coming weeks in advance. They staff up, prep more, and push harder. And yet every year, the same thing happens: lines back up, ticket times stretch, and guests who might have become regulars walk out the door before they ever place an order.

The problem usually isn’t the kitchen. It’s everything upstream of it. Ordering infrastructure that was built for a normal Tuesday. Staff positioned where they’ve always been, not where peak volume actually needs them. Systems that work fine at moderate volume and quietly break down when covers spike.

Multi-unit operators who consistently outperform during peak season aren’t just working harder. They’re running tighter systems. Here’s what that looks like in practice.

1. Walk Your Locations Before the Rush Does

The best pre-season investment costs nothing but time. Walk each of your locations during a simulated high-volume period, ideally when traffic is already elevated, and map what you see. Where do guests naturally slow down after entering? Where does the line form when the lobby gets full? Where does the ordering process visibly stall?

This matters especially for locations with kiosks. A kiosk that sits to the side of the natural guest flow gets ignored. One positioned at the point where guests decelerate after entering captures orders before a counter queue ever forms. Placement relative to entry traffic patterns has a direct impact on adoption—and adoption is what drives throughput at scale.

While you’re walking, evaluate signage and queue management too. These are consistently underdone. Guests who don’t know where to go don’t wait patiently while they figure it out, they get frustrated, they leave, or they create congestion that slows down everyone behind them.

2. Let Kiosks Handle Order Intake at Volume

Counter service has a structural limitation: it’s sequential. One guest orders, then the next. During a summer lunch rush, that constraint compounds fast.

Kiosks break the sequential bottleneck by letting multiple guests order simultaneously. The throughput math is straightforward: Four guests ordering in parallel move through the system faster than four guests waiting in line. That difference is manageable at low volume and significant when covers spike.

The industry has taken note. Shake Shack’s kiosks are now the brand’s largest and most profitable ordering channel, with kiosk checks running meaningfully higher than other in-store ordering channels—a result the chain attributed to smarter upsell sequencing through the kiosk experience. According to reporting from Restaurant Dive, a majority of QSR and fast casual guests now prefer kiosks over counter ordering when lines exceed four people—a figure that has grown significantly year over year.

For multi-unit operators still evaluating kiosk ordering ROI, peak season is the clearest test case available. The volume is real. The staff constraint is real. The question is whether your ordering infrastructure can keep pace with both.

3. Align Your Menu for Speed Before You Need To

A menu that performs well at moderate volume can become a throughput liability when summer traffic hits. Complex modifier flows, items with long prep dependencies, and poorly organized category structures all slow down the order process at the kiosk, at the counter, and in the kitchen. The effects multiply when every station is running at capacity.

Before peak season, run a practical audit. Which items drive the longest ticket times? Which modifications generate the most kitchen confusion or order errors? If you’re running summer LTOs, have those items been stress-tested at volume, or only at normal traffic levels?

On the kiosk side, this translates to deliberate merchandising decisions: which items are promoted in featured slots, how modifier screens are sequenced, and whether your default selections reduce friction or add to it. Small adjustments to item placement and modifier flow can meaningfully reduce average order duration without any changes to the menu itself. Bite’s Sales and Analytics Dashboard gives operators the item-level data to make those calls with confidence rather than gut feel.

4. Redeploy Your Team Toward Execution

When kiosks are handling a significant share of order intake, the labor freed from the counter doesn’t disappear; it shifts. The operators who get the most out of that shift are intentional about where the capacity goes.

The highest-value redeployment during peak season is toward execution: food prep, expo, and guest experience. These are the roles where speed and accuracy have the most direct impact on throughput and satisfaction, and they’re also the roles that get stretched thinnest when volume spikes. A team member who would otherwise be managing a register queue can instead focus on keeping the kitchen moving, which is where the actual bottleneck usually lives.

QSR operators increasingly view kiosk deployment as a way to improve labor flexibility, not reduce headcount. It’s a framing that holds especially during summer, when you may be onboarding seasonal staff with limited experience. Limiting new hires’ exposure to high-stakes, high-error roles at the counter while kiosks handle ordering is a meaningful risk management decision, not just a staffing one.

5. Build a Daypart Strategy Around Your Actual Peak Windows

Not all summer volume looks the same. Tourist-adjacent locations see different traffic patterns than commuter corridors. Dinner daypart extends significantly in summer, particularly near outdoor venues, retail districts, and recreation areas. Weekend volume profiles can look almost nothing like weekday ones.

Treating “summer” as a single operational condition misses the specificity that matters. Pull your transaction data by daypart, day of week, and location. Find where throughput consistently degrades—not just which locations are busy, but when and why the system slows down at each one.

Peak season rewards preparation. Operators who treat summer as a systems problem—not just a staffing problem—come out of it with better margins, better guest scores, and an operational playbook that holds up well beyond Labor Day.

If you’re evaluating how kiosk technology can support throughput and consistency across your locations, request a demo to see what Bite makes possible.

At a brand with 10, 20, or 50 locations, the spring menu season looks a little different than it does at the unit level. You’re not designing the menu—corporate is. What you’re doing is something harder: executing someone else’s vision profitably, consistently, across a portfolio of locations with different volume profiles, different staffing realities, and different guest mixes.

That’s the tension most regional franchise operators don’t talk about openly. The spring LTO comes down from brand. The contribution margin target is yours to hit. The upsell strategy—if there is one—is often under-defined. And the data that would tell you whether any of it is working tends to live in systems that don’t talk to each other cleanly.

The pressure on either side of that tension is real. 82% of operators reported higher average food costs in 2025, with the NRA’s data showing food costs running more than 35% above pre-pandemic levels. At the same time, 95% of operators say consumers are more value-conscious than they used to be—making price sensitivity a ceiling that’s increasingly difficult to push through, even with a seasonal LTO.

Spring feels exciting. For a regional operator managing margin across dozens of units, it also carries real risk if it isn’t approached analytically.

Here’s the argument: seasonal menu transitions are among the highest-leverage moments in a franchise operator’s calendar. Done well, they drive traffic, improve per-guest profitability, and generate location-level data that informs smarter decisions across the rest of the year. Done wrong, they create execution inconsistency across your portfolio—some units running the LTO well, others burying it—and burn operational bandwidth on items that never earn their place.

Most regional operators treat spring menu planning as an implementation exercise. The ones who outperform treat it as an engineering problem.

The Menu Engineering Framework, Applied at Scale

The menu engineering framework isn’t new—it was developed by Michael Kasavana and Donald Smith at Michigan State—but it’s underused at the regional franchise level, where operators often have access to more data than their single-unit counterparts but less freedom to act on it unilaterally.

Understanding the framework is still essential, because it shapes how you evaluate brand-mandated items against your actual portfolio performance—and how you make the case internally when something isn’t working.

The four quadrants:

Stars: high popularity, high contribution margin. Protect these. They’re the items your locations can’t afford to deprioritize in favor of a new seasonal push.

Plow Horses: high popularity, low profitability margin. These sell well and feel like wins. They often aren’t. At scale, Plow Horses that dominate the mix quietly suppress your average contribution margin per transaction across every unit.

Puzzles: low popularity, high profitability margin. These are the items that need your merchandising attention most—and in a kiosk or digital ordering environment, they’re the items most likely to be overlooked without active intervention.

Dogs: low popularity, low profitability margin. At the regional level, the ability to retire these may sit with brand—but the data case for doing so is yours to build.

The two metrics that drive the analysis:

• Profitability/Contribution margin: selling price minus food cost per item. According to NRA data, food and beverage costs for limited-service operators ran a median of 32.4% of sales in 2024—useful context, but food cost percentage can obscure what actually matters at volume. A $14 item with $4 in food cost contributes $10 to margin. A $9 item at 28% food cost contributes $6.48. Across 40 locations doing hundreds of transactions a day, that gap is not theoretical.
  
• Popularity index: an item’s share of total sales in its category, tracked per location. At the regional level, this matters not just in aggregate but as a consistency signal—wide variance in popularity index across locations often points to an execution or merchandising problem, not a product problem.

The spring relevance: every brand-mandated seasonal item should be run through this framework at the regional level before rollout—not to override brand decisions, but to inform how you price, position, and sell them across your portfolio.

The Spring Opportunity (And the Trap)

Spring is one of two annual windows—along with fall—when guests actively expect menus to change. That expectation is a genuine asset, and it operates at the brand level as much as the unit level. Guests who follow the brand are primed for something new. The regional operator’s job is to convert that priming into actual margin.

What the spring window makes possible at the regional level:

• Phasing out underperforming items without guest friction—seasonal transitions give cover for removal that mid-year changes don’t
• Introducing brand-designed LTOs with a local execution strategy that the brand hasn’t fully specified (more on that in Section 4)
• Using the novelty of seasonal items to test upsell prompts and price attachment behavior across your portfolio—data that becomes proprietary insight for your group

Spring ingredients—asparagus, strawberries, lemon, peas, fresh herbs, lighter proteins—carry strong perceived value with guests. When sourced in season, they tend to support favorable margins relative to their perceived quality. That’s the brand’s sourcing call, but the margin benefit is yours to protect or lose in execution.

The trap at the regional level looks different from what it does for independent operators.

It’s not usually a failure to design the right items. It’s a failure to execute them consistently across locations. Three patterns show up repeatedly in regional franchise portfolios:

Inconsistent rollout across units. Some locations merchandise the spring LTO aggressively; others treat it like a footnote. The result is wide performance variance that makes it nearly impossible to evaluate whether the item itself works. You can’t improve what you can’t measure cleanly.

Treating the brand’s LTO strategy as the complete strategy. Brand provides the item, the pricing, and the promotional materials. What brand often doesn’t provide is a location-level upsell plan, a merchandising sequence for kiosk and digital ordering, or a defined evaluation framework. Filling those gaps is the regional operator’s leverage point.

Pricing drift at the unit level. In multi-unit portfolios, it’s common for individual locations to apply discounts, modify modifiers, or run local promotions that quietly erode the contribution margin of a brand-designed LTO. At 10 units, this is manageable. At 50 units, it becomes a significant margin leak if it isn’t actively monitored.

Start with Your Portfolio Data, Not the Brand Playbook

The instinct at the regional level is often to wait for brand guidance before doing any planning. That’s an understandable instinct—and it leaves significant value on the table.

The data audit that should happen before any spring rollout begins is entirely within your control, and it shapes how you execute regardless of what brand provides.

The right questions to ask across your portfolio before spring planning begins:

• Which locations have the highest average contribution margin per transaction, and what’s driving the difference? Understanding your top performers’ item mix tells you something about what to replicate in merchandising and upsell strategy.
• Where do your current Stars and Plow Horses sit across locations? An item that performs as a Star at your top-volume units may be a Plowhorse at lower-volume locations. And that distinction changes how you merchandise it.
• Which items consistently appear in multi-item orders? Attachment behavior varies by location and daypart, and that variation is information. A spring LTO that pairs naturally with a high-attachment item is a better upsell target than one that stands alone.
• Are there daypart gaps that a spring item could address? A lighter spring offering that drives lunch traffic is more valuable to your portfolio than one that spikes on weekend dinner and fades by mid-week.

The kiosk advantage for regional operators:

At 10–50 units, kiosk and digital ordering data are among the most valuable assets you have—and it’s often underused. Unlike verbal ordering data, kiosk data is structured, consistent, and captures behavior that aggregated POS data misses: what was browsed versus purchased, which add-ons were accepted at which locations, and how item placement on the screen affected sales mix across your portfolio.

This is the data foundation for informed spring planning. It’s also the input layer that Bite Lift uses to surface the right upsell at the right moment—not as a static prompt, but as a dynamic recommendation tuned to the guest, the item, and your margin priorities.

Building Your Execution Strategy Around Brand LTOs

The LTO environment across the industry right now is more competitive than it’s ever been. According to Technomic Ignite Menu data, LTO launches rose 19% year over year as of late 2025, with the full year tracking 10% above 2024. Technomic tracked 17,790 restaurant LTO launches in 2020; by 2024, that figure had grown to 36,830—more than double in five years. And 55% of consumers now say a restaurant’s LTO offerings factor into where they choose to eat, up from 50% in 2022.

For a regional franchisee, those numbers mean two things simultaneously: brand’s instinct to run seasonal LTOs is strategically correct, and the execution gap between operators who merchandise them well and operators who don’t is growing more consequential.

Where regional operators build their edge:

Operational preparation before launch, not after. Brand announces the spring LTO. The question to answer before it hits your locations: Does this item extend prep workflow in ways that create throughput risk at peak hours? If so, which locations are most exposed, and what’s the mitigation plan? The operators who ask these questions before launch are the ones who don’t spend six weeks watching a good item underperform because of a fixable execution problem.

A location-level merchandising plan. Research from Kerry found that 88% of consumers rated point-of-sale promotions as one of the three most influential purchase drivers for LTOs—making in-the-moment presentation a primary driver of LTO performance, not a secondary one. Brand may provide creative assets—the question is whether those assets are being deployed at every location, in every relevant touchpoint, with the same consistency. In a 50-unit portfolio, the answer is seldom yes without active oversight.

Pre-defined evaluation criteria. Before a spring LTO launches across your portfolio, define the benchmarks: What sales volume justifies the operational complexity? At what contribution margin does the item earn a permanent recommendation to brand? What upsell attachment rate indicates the item has real cross-sell potential? Setting these benchmarks before launch transforms the LTO from a brand mandate you’re executing into a business experiment you’re running—with findings that have value beyond the season.

Monitoring for margin drift. Across 10–50 locations, discount application, modifier behavior, and local promotional decisions can quietly erode the profitability/contribution margin of a brand-designed item. Building a monitoring cadence into your spring rollout—not just for sales volume but for actual contribution margin by location—is the difference between knowing your LTO is working and assuming it is.

How AI Upselling Changes the Seasonal Execution Equation

The structural challenge for regional operators running a spring menu isn’t getting guests to the restaurant. It’s getting guests who are already there—already at the kiosk, already in the app—to engage with a new item they didn’t come in planning to order.

Human upselling is inconsistent at scale. A motivated team member at your best location might mention the spring special on 70% of interactions. Across 50 locations with varying staff tenure, training compliance, and peak-hour pressure, that number drops significantly and unpredictably. Traditional kiosk upsell prompts are an improvement—they’re consistent, but they’re static. They present the same prompt to every guest at the same moment, regardless of order history, item affinity, or which items in your portfolio need merchandising support most.

AI-driven upsell via kiosks changes the equation for regional operators in three concrete ways:

Targeting by guest behavior, not just by prompt position. A guest whose order history shows affinity for lighter proteins is a different upsell target for a spring salad than a guest whose history is built around burgers and loaded fries. Bite Lift surfaces seasonal items to guests who are most likely to convert, rather than presenting the same prompt to every guest and measuring the average.

Weighted toward your margin priorities. The items that need active merchandising support are almost always Puzzles—high contribution margin, lower organic popularity. A well-configured AI upsell system via kiosk can be weighted to push those items harder across your portfolio, turning underperforming high-margin SKUs into active contributors. This is the kind of portfolio-level margin management that’s difficult to achieve through staff training alone.

Consistent across every location, every shift. For a regional operator, consistency of execution is the variable that determines whether portfolio-level analysis means anything. If your top five locations are executing the spring upsell strategy well and your bottom ten aren’t, your aggregate data is noise. Bite Lift delivers the same quality of upsell execution at every kiosk, across every unit, on every shift—which means the data you get back is actually actionable.

The Post-Season Data Harvest

This is the step most regional operators skip—and where the compounding value of disciplined execution either gets captured or evaporates.

The spring menu is not just a revenue event for your portfolio. It’s a research event. Every LTO and seasonal item generates location-level data about guest preference, price sensitivity, attachment behavior, and operational throughput that has direct implications for fall planning—and for the case you make to brand about what worked, what didn’t, and what should change.

Before retiring spring items, capture across your portfolio:

• Final contribution margin versus projected, by location. Did margin drift occur? Where, and why? This is the data that identifies which locations need operational or training attention before the next seasonal rollout.
  
• Upsell attachment rate by location and daypart. Wide variance here is an execution signal. Locations with strong attachment rates are doing something replicable. Locations with weak attachment rates need a different intervention.
  
• Multi-item order frequency for seasonal items. Which spring items appeared most often alongside other items? Strong pair performance is a signal for future bundling strategy and kiosk menu architecture.
  
• Any items that generated repeat guest requests after retirement. This is among the strongest signals you can bring to brand when making the case for a permanent addition or a returning LTO next spring.

Regional operators who build this feedback loop systematically such as using spring data to inform fall design, fall data to inform the following spring, create a compounding advantage over operators who treat each season as a fresh start. Over a two- to three-year horizon, the margin gap between those two operating approaches becomes significant.

Menu Engineering Is a System, Not a Season

For a regional franchise operator running 10 to 50 locations, the spring menu season is never just about the items. It’s about execution consistency, contribution margin management across a portfolio, and turning brand-level decisions into location-level performance.

The operators who outperform in Q2 are the ones who start with a data audit instead of a brand briefing, define their evaluation criteria before launch instead of after, and close the execution gap at the kiosk with tools that don’t depend on staff consistency to deliver results.

The tools to do this at the regional scale already exist. The question is whether you’re using them.

How the restaurant industry’s workforce evolved from pandemic chaos to a new normal — and what operators need to know to compete for talent in today’s market

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Key Data Points

Employment & Recovery

• 42,000 jobs (0.3%) above February 2020 levels as of February 2026 — National Restaurant Association
• QSR and fast-casual restaurants added 79,000 jobs (2%) above pre-pandemic levels — Escoffier
• 18 states plus D.C. remain below pre-pandemic restaurant employment — National Restaurant Association
• Industry added net 128,800 jobs during 12 months ending February 2026 — National Restaurant Association

Wages & Compensation

• Average hourly wages jumped from $13.36 (April 2020) to $19.93 (December 2025) — Restaurant Dive
• Leisure and hospitality sector wages increased 3.8% year-over-year to $22.70 (April 2025) — OysterLink
• Waiters and servers earn average base wage of $17.56 per hour before tips — OysterLink
• Base wages now make up 43% of restaurant worker pay, up from 35% in January 2020 — ADP Research Institute
• Median hourly wage for waiters/waitresses ($15.36) vs. all-profession median ($23.11) — Kezner Consulting

Labor Shortage & Staffing

• 70% of operators report job openings difficult to fill; 45% don’t have enough employees — NetSuite/National Restaurant Association
• 986,000 job openings in restaurants and accommodations sector (October 2025) — National Restaurant Association
• Restaurant unemployment ranged between 5.5% and 6.8% in recent months — Restaurant Dive
• Turnover rates at 73.9% annually — Toast

Technology Impact

• Urbane Cafe: 22% higher check average on kiosk orders and 5.6% lift in total sales — Bite Case Study

2026 Projections

• Industry projected to add more than 100,000 jobs in 2026, reaching 15.8 million employees — National Restaurant Association

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The restaurant labor market has undergone seismic shifts over the past five years. From the devastating pandemic job losses that saw over 3.7 million restaurant workers unemployed in early 2020, to the scramble for talent during the recovery, to where we stand today, restaurant operators have weathered a transformation that fundamentally changed how the industry approaches staffing.

As we navigate 2026, one thing is clear: we’ve reached a “new normal” that looks distinctly different from the pre-pandemic world. The question for operators is no longer “how do we get back to normal?” but rather “how do we thrive in this transformed landscape?”

Let’s examine what’s actually changed, what’s remained stubbornly the same, and what strategies are working for operators who are winning the war for talent.

The Numbers Tell a Complex Story

Employment Has Recovered… Sort Of

The headline news sounds positive: as of February 2026, restaurant employment stands at 42,000 jobs above February 2020 levels, representing a 0.3% gain. While this marks a recovery from the pandemic’s devastating job losses, the modest gains and month-to-month volatility—January saw the industry at 105,000 jobs above pre-pandemic levels before winter weather impacted February—reveal an industry still finding its footing.

But dig deeper, and the picture becomes more nuanced.

Full-service restaurants—the traditional sit-down establishments that were hardest hit during the pandemic—are still struggling to return to pre-pandemic staffing levels. While quick-service and fast-casual restaurants have added 79,000 jobs (2%) above pre-pandemic levels, full-service dining continues to lag behind.

The geographic distribution tells another story entirely. Eighteen states plus Washington D.C. remain below pre-pandemic restaurant employment, led by West Virginia (-6%), Maine (-5%), and New Mexico (-5%). Meanwhile, mountain states like Idaho (+20%), Utah (+14%), and Nevada (+13%) have surged well past their 2020 employment levels.

What This Means for Operators: The recovery isn’t uniform. Your experience depends heavily on your restaurant concept (QSR vs. full-service) and your location. If you’re in a lagging market, you’re competing for an even smaller pool of available workers.

Wages: The Gains Are Real, But Slowing

Perhaps the most significant change in the restaurant labor market is compensation. The numbers are striking:

• Average hourly wages for production and nonsupervisory restaurant workers jumped from $13.36 in April 2020 to $19.68—a nearly 50% nominal increase
• Average hourly earnings in the leisure and hospitality sector increased 3.8% year-over-year, from $21.87 in April 2024 to $22.70 in April 2025
• Waiters and servers now earn an average base wage of $17.56 per hour before tips, with tips making up approximately 69% of their hourly earnings.

The wage surge of 2021-2022, when restaurants saw year-over-year wage growth of 10-15%, has cooled considerably. Wage growth has moderated to more sustainable levels, but the gains made during those years have stuck.

Interestingly, base wages now make up 43% of restaurant worker pay, up from 35% in January 2020, as minimum wage increases and changing tipping behaviors reshape compensation structures.

What’s Changed: Restaurants can no longer compete for talent with pre-pandemic wages. The $15/hour floor that was once debated is now baseline in most markets, with many operators paying $18-20/hour or more.

What Hasn’t Changed: The fundamental wage gap between restaurants and other industries persists. The median hourly wage for waiters and waitresses ($15.36), including tips, is significantly lower than the all-profession median of $23.11, making it difficult to attract talent away from other sectors.

The Labor Shortage: Still Here, But Evolving

Job Openings vs. Available Workers

Despite employment gains, the labor shortage hasn’t disappeared—it’s just evolved. Seventy percent of restaurant operators report having job openings that are difficult to fill, while 45% say they don’t have enough employees to support existing customer demand, according to the National Restaurant Association.

The challenge is structural: there are consistently more job openings than available workers to fill them. While the gap has narrowed from pandemic highs, demand for workers remains elevated. As of October 2025, there were 986,000 job openings in the combined restaurants and accommodations sector, roughly unchanged from earlier months despite ongoing hiring challenges. The industry added a net 128,800 jobs during the 12 months ending February 2026, yet demand for workers continues to outpace supply.

The Turnover Challenge Remains

If there’s one metric that hasn’t fundamentally improved, it’s turnover. The restaurant industry continues to experience some of the highest turnover rates across all sectors.

While turnover rates have decreased from the peak of 2020 to around 73.9% annually, this remains extraordinarily high. To put it bluntly: roughly three out of every four employees will leave within a year.

The financial impact is devastating. Every departing employee costs money in recruitment, training, and lost productivity. With tight margins already squeezed by food costs and rent, high turnover is one expense operators can’t afford but can’t seem to escape.

What’s Changed: The “Great Resignation” has shifted to what experts call the “Great Stay”—workers are staying in their jobs longer, but not necessarily in the restaurant industry.

What Hasn’t Changed: Restaurant work is still fast-paced, physically demanding, and often involves irregular hours. These fundamental aspects of the job contribute to burnout and drive turnover, regardless of economic conditions.

Why Workers Still Aren’t Returning

The pandemic fundamentally reset worker expectations. Many who left restaurant jobs during COVID discovered:

1. Better Work-Life Balance Exists Elsewhere

Other industries like retail and delivery services offer more predictable hours and often better benefits. A gig economy driver can set their own schedule; a retail worker knows they’ll be off by 9 PM. Restaurant work, with its split shifts, weekend requirements, and unpredictable schedules, struggles to compete.

2. Rising Costs of Living Require Higher, More Stable Pay

While wages have increased, inflation has eaten into those gains. Real wages—adjusted for inflation—have increased only modestly since 2018. Workers need not just higher pay, but also predictable pay. The tip-dependent model, while potentially lucrative for some, introduces income volatility that many workers can no longer afford.

3. Health and Safety Concerns Linger

Though COVID restrictions have eased, health and safety concerns continue to influence job choices. Workers in customer-facing roles remain exposed to illness, and some simply aren’t willing to take that risk for restaurant wages.

4. The Job Itself Hasn’t Changed

Perhaps most fundamentally, restaurant work is still restaurant work. It’s physically demanding, often stressful, and involves dealing with difficult customers. No amount of wage increases changes the fundamental nature of the job—and for workers who found alternatives during the pandemic, there’s simply no compelling reason to return.

What’s Actually Working: Strategies from Successful Operators

While the challenges are real, some operators are finding success. Here’s what’s working:

1. Technology as a Labor Multiplier

Smart operators aren’t just trying to fill positions—they’re reducing the number of positions they need to fill in the first place.

Kiosk ordering systems reduce the need for order-takers, allowing restaurants to maintain throughput with fewer front-of-house staff. This isn’t about eliminating jobs; it’s about reallocating labor to higher-value activities.

Urbane Cafe, a 43-location fast casual chain, reallocated labor at the front of house after implementing kiosks. Locations that previously relied on two cashiers now operate efficiently with one team member serving as a cashier, kiosk ambassador, and guest experience facilitator. 

“We used to have two cashiers. Now we really only have one,” says Caprice Kindgren, Director of Marketing at Urbane Cafe. “It’s not like we’re giving worse guest service because there’s a kiosk—you just make sure you’re still welcoming guests.” 

The result? A 22% higher check average on kiosk orders and a 5.6% lift in total sales across 16 locations.

Mobile ordering, QR code menus, and contactless payment all serve the same purpose: doing more with the staff you have.

2. Flexible Scheduling and Quality of Life

The operators winning the talent war are those who recognize that competitive wages are table stakes—the real differentiator is quality of life.

Flexible scheduling options that accommodate workers’ needs—whether that’s childcare, school, or other commitments—make restaurant jobs more attractive. Some operators are experimenting with guaranteed minimum hours to provide income stability, while others offer shift-swapping apps that give workers more control.

3. Career Development and Growth Opportunities

Workers, especially younger ones, want to know there’s a path forward. Operators who invest in training programs, create clear advancement paths, and support professional development are seeing better retention.

The key is making these opportunities visible and accessible from day one. Don’t wait six months to tell a new hire they could be a manager—show them the path during orientation.

4. Benefits That Actually Matter

Health insurance, paid time off, and retirement plans were once rare in restaurants. They’re becoming standard among operators who want to compete for talent.

But benefits need to match worker needs. For part-time workers, access to earned wage access (getting paid for shifts already worked before payday) can be more valuable than a 401(k). For parents, childcare assistance or flexible scheduling trumps many traditional benefits.

5. Streamlining the Hiring Process

In a competitive labor market, speed matters. Technology-enabled hiring that streamlines applications and onboarding can be the difference between securing a good candidate and losing them to a competitor who moves faster.

Operators are using SMS-based recruitment, virtual interviews, and streamlined onboarding to reduce time-to-hire from weeks to days.

The Road Ahead: What to Expect in 2026

As we move through 2026, several trends are likely to shape the restaurant labor market:

The Industry Will Stabilize, Not Return

Don’t expect a return to pre-pandemic labor dynamics. The industry is projected to add more than 100,000 jobs in 2026, reaching 15.8 million employees, but the fundamental challenges around wages, turnover, and competition for workers will persist.

Regional Divergence Will Continue

Labor markets will remain highly local. Some states are seeing robust growth while others lag, and this pattern will likely continue. Operators need to understand their local market conditions rather than relying on national trends.

Technology Adoption Will Accelerate

Labor shortages are accelerating technology adoption across the industry. From AI-powered scheduling to robotic kitchen assistants to kiosk ordering, operators are increasingly turning to technology not as a nice-to-have but as a necessity.

The question isn’t whether to adopt labor-saving technology, but which technologies and when.

The War for Talent Will Remain Intense

With low unemployment rates and workers having more options than ever, restaurants will continue competing not just with each other but with every other employer in their market.

The operators who succeed will be those who recognize this reality and adapt accordingly—through better compensation, better work environments, better scheduling, and better use of technology to make their employees more productive.

The Bottom Line

The state of restaurant labor in 2026 is a study in contrasts. Employment has recovered, but not evenly. Wages have increased significantly, yet staffing challenges persist. Workers have more options, but restaurants still need to fill positions.

What’s become abundantly clear is that there’s no going back to 2019. The pandemic permanently reset the labor market, and successful operators are those who’ve accepted this new reality and adapted their strategies accordingly.

The path forward requires a multi-faceted approach:

• Competitive wages and meaningful benefits to attract talent
• Technology to multiply the productivity of the staff you have
• Flexible scheduling and quality-of-life improvements to retain workers
• Efficient hiring processes to move quickly when good candidates appear
• Career development opportunities to build long-term loyalty

The restaurant labor shortage of 2020-2022 may have evolved into something more manageable, but make no mistake: the fundamental challenge of attracting and retaining talent in a competitive market isn’t going away. The operators who will thrive in 2026 and beyond are those who treat labor strategy not as a cost to minimize, but as a competitive advantage to maximize.

Walk into a modern convenience store today and you might find yourself ordering a made-to-order breakfast sandwich, customizing a fresh salad bowl, or grabbing a craft coffee that rivals your neighborhood café. This isn’t your grandfather’s gas station—it’s the front line of what industry observers are calling “the Foodvenience Revolution.”

As convenience stores transform into modern retail powerhouses, they’re no longer simply located near gas pumps—they’re embedded in the rhythm of daily life. From fresh breakfast sandwiches to hot lunch options and locally inspired snack assortments, c-stores are stepping into territory once dominated exclusively by quick-service restaurants.

The stakes are high. With transaction counts inside stores flat at best, according to NACS Research, operators must maximize revenue per visit while navigating labor shortages, rising operational costs, and intensifying competition from traditional restaurants fighting back with aggressive value propositions.

But this challenge also represents an unprecedented opportunity. As QSR prices climb and consumers become more value-conscious, convenience stores are uniquely positioned to capture market share through strategic investments in foodservice, technology, and customer experience. Here are the defining trends reshaping the convenience retail landscape in 2026.

C-Stores Now Own Breakfast, Challenging Traditional QSRs

Perhaps the most transformative shift in convenience retail is the aggressive repositioning of c-stores as legitimate breakfast destinations. C-stores are stepping up their breakfast games, with major chains debuting breakfast lineups that could easily be mistaken for fast-casual restaurant offerings.

7-Eleven’s recent breakfast launch exemplifies this evolution: pearl sugar-studded Belgian waffle breakfast sandwiches, Waffle Tots for $1, and El Gran Tocino Breakfast Tacos demonstrate the sophistication level c-stores are achieving. At breakfast, consumers typically want speed, predictability, and value—attributes that play directly to convenience stores’ core strengths.

The demand is substantial and growing. Research shows that 66% of customers wish they could get made-to-order food from a convenience store, with Gen Z showing a particularly strong appetite for this option at 72%. The global breakfast food market’s growth from $210 billion in 2026 to $255 billion by 2030 creates a massive opportunity for operators who can execute well.

The Technology Enabler

Self-service kiosks serve as the critical technology enabling breakfast program scalability. These systems manage morning rush complexity while maintaining the speed customers demand, allowing limited staff to focus on food preparation and quality control rather than order-taking. For operators, kiosks solve the dual challenge of labor efficiency and order accuracy during peak periods.

“In convenience stores, reliability is the top priority. Many locations operate 24/7 and experience sustained, high-traffic usage, which places significant wear on hardware,” explains Jared Epstein, Account Executive at Frank Mayer. “We’re seeing strong demand for both self-checkout and self-order kiosks as C-stores expand foodservice offerings. In many cases, they’re starting to resemble QSR environments – something that’s obvious when you look at brands like Wawa, where speed, consistency, and uptime are critical.”

Extended breakfast hours allow c-stores to capture late-morning and “second breakfast” occasions that traditional restaurants often miss, with some locations serving breakfast items well into the afternoon—a flexibility impossible for labor-constrained QSRs with fixed daypart transitions.

AI-Driven Operations Transform Back-of-House Efficiency

After showing initial hesitancy with artificial intelligence, convenience retailers are now embracing c-store-specific AI technologies rather than generic solutions that could work across any industry. The focus is on practical applications that directly impact profitability and operational efficiency.

Computer Vision for Waste Reduction

Stinker Stores’ February 2025 implementation of AI-powered camera vision to monitor roller grills represents the new generation of foodservice optimization. The system records which items sell and when, using that data to create actionable plans that improve sales while reducing waste—a critical capability given the slim margins in prepared food programs.

“AI is at the top of the list, especially the evolving data infrastructure and governance requirements that come with deploying AI platforms effectively,” notes Tom Colbert, VP of IT at Kwik Trip, in discussing what retail technology trends to watch in 2026.

Predictive Analytics for Inventory Management

Leading c-stores are using predictive analytics and store-level retail data to determine which fresh offerings to prepare each morning, implement dynamic pricing to optimize margin while reducing waste, and maintain real-time inventory visibility to ensure product availability. This operational intelligence transforms fresh food programs from money-losing gambles into profitable differentiators.

Customer Tracking and Experience Optimization

Some operators are implementing AI-driven customer tracking systems that monitor movement patterns throughout the store. “There are systems using AI that allow store operators to track customer movements in the store and locate the most traveled paths throughout the store,” explains Mike Gilligan, president of Gilligan’s Retail. “With this information, we can tailor our product offering depending on where the customer shops.”

Retail Media Networks Are The New Revenue Frontier

Retail media networks represent perhaps the most significant untapped revenue opportunity for convenience retailers in 2026. RMNs are projected to generate $89 billion by 2026, up from $46 billion in 2023, yet convenience stores have lagged behind other retail segments in developing these high-margin advertising businesses.

The C-Store Advantage for Retail Media

Convenience stores present unique characteristics that make them excellent candidates for highly effective RMNs, particularly in physical stores. C-store sales are driven by impulse, immediate-consumption purchases where shoppers are looking for inspiration during the shopping trip. This creates prime opportunities for point-of-decision advertising.

Several major chains have launched successful retail media programs:

• 7-Eleven’s Gulp Media Network focuses on “immediate consumption purchase occasions” with coast-to-coast reach
• Casey’s expanded partnership with GSTV adds video content to fuel dispensers at 2,900 stores across 19 states
• Love’s Travel Stops launched its retail media platform serving ads on fuel pumps and in-store digital screens across 660+ locations
• Wiegel’s Milk Crate Retail Media Network offers ad inventory across apps, websites, video, and social media
• EG America’s retail media network, using digital screens and loyalty data, has delivered “meaningful sales lift” for CPG partners

Early results validate the model. Products advertised through c-store retail media see average sales lifts of 5-9% during campaigns, with one 7-Eleven Slurpee promotion raising unit sales by 11% during activation.

The Infrastructure Investment

“I expect launches in 2026 to more than double what we saw in 2025,” predicts Matt Riezman, partner at NexChapter. “What’s particularly interesting is how this is forcing c-store retailers to professionalize their marketing operations almost overnight. They’re hiring talent from consumer packaged goods and traditional retail, building out ad tech stacks and fundamentally rethinking their relationships with suppliers.”

Dover Fueling Solutions’ launch of 4Court Media represents the next evolution, allowing c-store chains to integrate their own promotional content alongside national ads on fuel dispenser screens. The company’s research shows retailers plan to significantly increase investment in promotion and advertising technology (36%) and digital signage (34%) over the next two years.

Third Place Positioning with Premium Environments

Convenience stores are becoming more than places to shop—they’re becoming places to stay. An increasing number of retailers are introducing café-style seating, curated product assortments, and enhanced store designs that make the environment feel more intentional and community-driven.

The European Model Comes to America

Retailers such as Shell Café and Rusty Lantern are setting the pace with formats that look and feel more like boutique cafes than traditional gas stations. Rutter’s 1747 store features multiple screens, sports tickers, and a full bar, exemplifying how c-stores may fill the growing need for third places in 2026.

This strategy particularly resonates with younger shoppers who see retail spaces as extensions of their lifestyle. They want environments that reflect their values and offer more than transactional utility. The investment in ambiance, comfortable seating, premium WiFi, and work-friendly environments positions c-stores as community gathering spaces beyond fuel stops.

The Business Model Evolution

This “third place” strategy allows c-stores to capture different dayparts and occasions:

• Morning coffee meetings
• Remote workers seeking afternoon workspaces
• Evening social gatherings
• Study sessions for students

Each represents an occasion that traditional convenience stores rarely captured. The investment in environment and amenities is justified by higher average transaction values and increased visit frequency from customers who view the location as a destination rather than just a pit stop.

EV Charging Infrastructure Reshapes Store Design and Economics

The proliferation of electric vehicle charging stations is fundamentally changing convenience store customer behavior, facility design, and revenue models. Extended dwell times of 20-30 minutes during charging sessions create both challenges and opportunities for operators.

From Quick Stop to Destination Visit

Traditional c-store visits average 3-5 minutes. EV charging extends this to 20-30 minutes, requiring completely different facility design and service models. Leading operators are responding with:

• Premium food offerings designed specifically for charging customers with time to enjoy a meal
• Digital ordering integration, allowing customers to place orders from their vehicles for pickup
• Comfortable seating areas with power outlets, WiFi, and work-friendly environments
• Entertainment options, including gaming areas, premium coffee bars, and retail boutiques

The key insight is designing the experience around the customer’s need state during the charging period rather than optimizing for speed-of-service. This fundamentally different approach requires new facility layouts, staffing models, and product mix strategies.

The Revenue Opportunity

While fuel margins provide baseline profitability, the real opportunity with EV charging comes from maximizing in-store purchases during extended dwell times. Operators who successfully convert charging customers into foodservice customers can achieve significantly higher per-visit revenue than traditional fuel transactions.

Self-Checkout and Cashierless Technology Scale Rapidly

Self-checkout transactions are expected to make up nearly 40% of all retail transactions globally by 2026, driven by consumer demand for speed and control. But c-stores are pushing beyond traditional self-checkout toward fully cashierless shopping experiences.

Just Walk Out Technology Goes Mainstream

Reitan Convenience Estonia’s R-Kiosk locations exemplify where the technology is headed. Customers enter using a bank card or mobile app, grab what they need, and walk out—no checkout lines, no waiting. Behind the scenes, AI-powered sensors and cameras track product movements in real time, automatically updating each shopper’s virtual cart.

“Innovation touches every part of the retail experience, even if customers only see a fraction of what’s happening behind the scenes,” says Tiia Ilves, CEO of Reitan Convenience Estonia. “Technology helps us create a more intuitive shopping journey. But it also means keeping both staff and customers informed and comfortable with these new tools.”

Smart Shelves and Inventory Intelligence

According to McKinsey research, retailers using smart shelf technology can reduce out-of-stock rates by up to 30% and cut manual inventory checks by nearly 40%. In stores where customers expect to grab what they need and go immediately, these improvements directly impact revenue.

Smart shelves automatically flag when items are running low or misplaced, helping staff keep shelves filled without constant manual checks—particularly critical for fast-moving essentials like bottled drinks, snacks, and ready-to-eat meals. Some retailers are tapping into behavioral data captured by shelf sensors to understand what draws attention, what gets picked up and put back, and using these insights to optimize product placement and pricing strategies.

Age Verification Automation

As self-checkout expands, age verification for restricted items becomes critical. Advanced systems can flag suspicious IDs, maintain audit trails for regulatory compliance, and integrate with existing POS and inventory platforms. Biometric and ID scanning reduce both labor requirements and compliance risk.

Labor Optimization Through Strategic Technology Investment

Finding and retaining good employees remains one of the biggest operational challenges in the convenience space, with labor costs rising, turnover remaining high, and customers expecting consistent service regardless of staffing levels.

The Foodservice Hiring Challenge

As c-stores invest heavily in foodservice to compete with QSRs, they face a critical challenge: “Training somebody just to do the register—which I’m not really a proponent of—is relatively easy. Training someone to work in a QSR is a lot harder,” notes retail consultant Jeff Keune.

The focus on foodservice quality forces operators to change hiring and training practices. Although seeking more food-qualified workers narrows the talent pool, it can improve retention by attracting employees seeking skills development and career progression rather than just temporary work.

Technology as Labor Multiplier

Rather than replacing workers, successful c-store technology deployments multiply worker effectiveness. Solutions that integrate into existing operations without requiring additional headcount, extensive training, or new point-of-sale systems drive revenue growth without increasing operating costs.

Examples include:

• AI-powered scheduling systems that optimize shift coverage based on predicted demand
• Automated inventory tracking that reduces time spent on manual counts
• Self-service kiosks that allow staff to focus on food preparation and customer service
• Computer vision systems that monitor equipment performance and flag maintenance needs

The Cultural Imperative

Keune emphasizes that QSRs often have stronger employee cultures than convenience retailers because restaurants prioritize employees over growth initiatives or product launches. “Make sure that [employees] are set up for success, because that’s the key, as much as anything else,” he advises. “Set up for success and then recognize and compensate for jobs well done.”

Technomic’s 2026 Foodservice Trends Forecast predicts labor challenges will intensify as policy, economic, lifestyle, and demographic factors conspire to reduce the available pool. U.S. labor participation among 16-19 year-olds has declined from 53% in 1994 to 37% in 2024, with forecasts showing a further drop to 35% by 2034.

Digital Visibility and Personalized Promotions Drive Traffic

Today’s customers plan every stop on their phones—checking prices, looking for deals, and comparing locations before they ever get in the car. Retailers that meet customers in these digital moments are winning transactions competitors never see.

The Shift to Intentional Shopping

One of the biggest changes in consumer behavior is the shift from impulse-driven convenience store visits to intentional, planned trips. Customers are shopping strategically, making deliberate choices about where to spend money based on value perception, available promotions, and overall offering quality. This means a store’s digital visibility and value communication matter more than location alone. 

Loyalty Programs as Revenue Drivers

Loyalty members visit more frequently and spend more per visit, while providing valuable customer data that enables targeted marketing. Digital loyalty programs allow operators to:

• Track purchase history and preferences at the individual level
• Deliver personalized promotions based on buying patterns
• Test and optimize promotional strategies in real-time
• Measure campaign effectiveness with precision
• Build direct communication channels with customers

Retail Media Integration

The most sophisticated operators are integrating loyalty data with retail media networks, creating closed-loop attribution that demonstrates promotional ROI to CPG brand partners. This data-driven approach transforms convenience stores from simple product distributors into strategic marketing partners capable of driving measurable results for suppliers.

The Path Forward: Operational Excellence at Scale

The convenience stores thriving in 2026 share common characteristics that transcend any single trend or technology:

1. Data-Driven Decision Making
Leaders are using predictive analytics, computer vision, and AI-powered systems to make smarter operational decisions. They understand local demand patterns, optimize inventory in real-time, and adjust strategies based on measured results rather than intuition.

2. Customer-Centric Technology
Technology investments are guided by customer needs rather than industry hype. Self-checkout, mobile ordering, and digital loyalty programs are deployed because customers demand them and because they demonstrably improve experience and profitability—not because they’re trendy.

3. Foodservice as Core Strategy
The most successful operators have moved beyond viewing foodservice as a nice-to-have add-on. Foodservice is now a primary draw that generates 27.7% of in-store sales and nearly 40% of gross margin, making it one of the most important profit drivers for the channel.

4. Revenue Diversification
Rather than relying solely on fuel margins, leaders are building multiple revenue streams through foodservice, retail media networks, EV charging, and premium merchandise programs. This diversification provides resilience against volatility in any single category.

5. Operational Discipline
Excellence in execution separates winners from losers. This means maintaining consistent food quality, ensuring equipment uptime, managing labor efficiently, controlling inventory waste, and delivering reliable customer experiences across all dayparts and locations.

The Technology Partner Imperative

For convenience store technology providers, this environment presents a significant opportunity. Solutions that work seamlessly across multiple foodservice formats, adapt to each operator’s unique requirements, deliver measurable ROI through increased check sizes and improved accuracy, and integrate smoothly with existing systems will be essential partners for operators navigating this transformation.

The technology that wins won’t be the flashiest or most futuristic—it will be the solutions that solve real operational problems, work within operators’ existing infrastructure, and deliver results from day one. As c-stores continue blurring the lines with traditional restaurants, the ordering and payment technologies that enable efficient, accurate, and profitable foodservice operations will become increasingly critical.

Key Data Points

Foodservice Revenue Performance:

• Foodservice accounts for 27.7% of in-store c-store sales and 38.6% of in-store gross margin (Restaurant Business)
• Products advertised through retail media networks see 5-9% sales lift during campaigns (C-Store Dive)
• 66% of customers want made-to-order food from convenience stores, with 72% of that demand coming from Gen Z (CStore Decisions)

Consumer Behavior & Technology:

• Self-checkout transactions expected to reach 40% of all retail transactions globally by 2026 (LS Retail)
• Global breakfast food market valued at $210 billion in 2026, growing to $255 billion by 2030 (Tastewise)
• Transaction counts inside c-stores remain flat, driving focus on per-visit revenue optimization (C-Store Dive)

Retail Media Networks:

• Retail media networks projected to generate $89 billion by 2026, up from $46 billion in 2023 (Convenience Store News)
• Dynamic planograms deliver 12-20% category sales uplift (CSP Daily News)
• Retail media ad spending to hit $106 billion globally by 2027 (Gable)

The American foodservice landscape is experiencing a period of unprecedented transformation as technology adoption, labor pressures, and evolving consumer expectations converge to reshape how we eat out. From quick-service restaurants deploying AI-powered drive-thrus to convenience stores positioning themselves as legitimate breakfast destinations, the traditional boundaries between dining segments are blurring faster than ever before.

As we move through 2026, restaurant operators face a market defined by cautious consumers, intense value competition, and the imperative to do more with less. Traffic growth is expected to remain below 1 percent this year, forcing brands to compete for market share rather than rely on overall industry expansion. At the same time, pricing across segments has converged around the critical $10-$12 threshold, creating fierce competition between fast casual, QSR, and even casual dining concepts.

The winners in this environment will be operators who successfully balance technology investment with operational excellence, labor optimization with elevated guest experiences, and value pricing with quality perception. Here’s what’s shaping each major segment in 2026.

Fast Casual Trends

Hybrid Dining Models Blur the Line Between Fast Casual and Full Service

Fast casual restaurants are increasingly adopting elements traditionally associated with full-service dining as they seek to justify premium price points and differentiate from value-focused competitors. This includes table service options with QR code ordering, premium beverage programs featuring craft cocktails and curated wine selections, and extended daypart offerings that allow them to compete with traditional restaurants during breakfast and late-night hours.

However, this evolution comes with challenges. Fast casual traffic slowed from 3.3% growth in December 2024 to just 1.7% in October 2025, with consumers increasingly questioning the value proposition of $15-$20 entrees. Leading brands are responding by emphasizing experience over pure convenience. The most successful concepts are creating “third place” environments with comfortable seating, WiFi access, and work-friendly amenities that justify higher price points through enhanced ambiance rather than just food quality.

AI-Powered Kitchen Operations Optimize Labor

With labor remaining one of the industry’s most persistent challenges, fast casual operators are turning to artificial intelligence to streamline back-of-house operations. Roughly one-third of restaurant operators in 2026 already use AI technologies, while nearly half plan to adopt them in the near term, focusing on predictive inventory management, automated prep scheduling based on demand forecasting, and intelligent kitchen display systems with AI-powered routing.

These investments are paying off. AI automation can trim 15-50% of labor hours in targeted workflows, according to data from successful implementations. The technology allows restaurants to predict demand patterns, optimize staffing levels, and reduce waste—all critical capabilities in an environment where margins are under constant pressure. Kitchen display systems enhanced with AI can now route orders to specific stations based on real-time capacity, crew skill levels, and equipment availability, significantly improving throughput during peak periods.

Sustainability Moves from Marketing to Operations

Environmental initiatives are shifting from customer-facing marketing messages to core operational practices. Fast casual brands, which have historically positioned themselves as more environmentally conscious than traditional QSRs, are now implementing zero-waste kitchen initiatives, renewable energy installations, and sourcing strategies that prioritize local suppliers as standard practice rather than premium positioning.

This operational focus on sustainability serves dual purposes: it reduces costs through waste reduction and energy efficiency while meeting consumer expectations for environmental responsibility. The key difference from previous “green” initiatives is that sustainability is now embedded in operations rather than marketed as a premium feature. Brands are finding that customers increasingly expect sustainable practices as table stakes rather than differentiated benefits worth paying extra for.

Loyalty Programs Become Revenue Centers

Fast casual operators are transforming loyalty programs from customer retention tools into significant revenue drivers. Subscription-style loyalty programs are lowering marketing expenses while increasing visit frequency, with some major chains reporting that loyalty members account for more than half of total sales.

The evolution includes tiered membership structures with exclusive menu access, early access to limited-time offers, and personalized pricing based on individual purchase patterns. Data-driven personalization allows brands to deliver hyper-personalized guest experiences that drive both frequency and average check. The most sophisticated programs use AI to predict when individual customers are most likely to visit and what offers will drive incremental purchases, transforming loyalty from a defensive retention tool to an offensive growth driver.

For instance, the hardware enabling this personalization, such as self-service kiosks, is becoming increasingly sophisticated. 

“When tied to loyalty programs, facial recognition or visual identification can have returning customers opt-in to receive customized menus, preferred item shortcuts, or targeted promotions the moment they approach the kiosk,” notes Jared Epstein, Account Executive at Frank Mayer – Kiosks and Displays.

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QSR Trends

Drive-Thru 2.0: Multi-Channel Order Fulfillment

Quick-service restaurants are fundamentally reimagining the drive-thru as an omnichannel fulfillment center rather than a single-purpose service lane. Drive-thru and delivery channels now account for over 70% of revenue at leading QSR brands, driving massive investments in dedicated mobile order pickup lanes, AI voice ordering systems, and outdoor kiosk ordering with curbside pickup options.

The technology transformation is particularly evident in voice AI adoption. Voice ordering is crossing a critical threshold in 2026, moving from experimental technology to essential infrastructure, with pizza and high-volume takeout categories already seeing 26%+ phone revenue increases. New drive-thru designs feature dual lanes with separate routing for mobile orders versus traditional ordering, cutting transaction times to under 90 seconds while increasing throughput by up to 18% in pilot markets.

Operators are also rethinking store layouts, dedicating just 25% of floor space to seating while investing in walk-up windows and curbside pickup infrastructure that maximizes revenue per square foot without expanding the building footprint.

Premium Menu Stratification

QSR brands are breaking away from traditional value-focused positioning by introducing elevated ingredients, limited-time collaborations with celebrity chefs and brands, and tiered pricing structures featuring “signature” product lines. Burger King’s partnerships with entertainment properties like SpongeBob demonstrate how major chains are using branded collaborations to create buzz and justify premium pricing.

This trend reflects QSRs’ attempt to compete with fast casual concepts on quality while maintaining speed advantages. Chains are developing dual-tier menus with both value-priced basics and premium offerings that allow customers to trade up when they’re willing to spend more. The key is maintaining the operational simplicity and speed that define quick service while incorporating ingredients and preparations traditionally associated with higher-end concepts.

Ghost Kitchens Come In-House

Rather than ceding delivery-only concepts to third-party ghost kitchen operators, QSR brands are launching their own virtual concepts from existing locations. This allows chains to maximize utilization of their kitchen capacity, particularly during off-peak hours, while testing new menu concepts with minimal capital investment.

The strategy includes dual-brand operations in single footprints and daypart-specific brands that optimize kitchen use throughout the day—breakfast concepts that transition to lunch and dinner offerings in the same space. By controlling the virtual brand experience in-house, QSRs maintain quality standards and capture margin that would otherwise go to third-party kitchen operators.

Labor Technology Goes Beyond POS

The highest-impact investments for 2026 will be those that simplify, strengthen, and scale operations, with technology extending far beyond traditional point-of-sale systems. Automated beverage stations and robotic fry cooks are moving from pilot programs to scaled deployment, while employee scheduling AI optimizes shift coverage based on predicted demand patterns.

Cross-training support tools help crew members quickly learn new stations, improving operational flexibility in an environment where 80% annual restaurant turnover makes it impossible to reliably staff all positions. IoT-enabled equipment monitoring tracks fryer oil quality, refrigerator compressor performance, and other indicators that allow predictive maintenance rather than reactive repairs. These technologies collectively reduce labor requirements while improving consistency and reducing downtime.

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C-Store Trends

Breakfast as a Destination Daypart

Perhaps no trend is more transformative for convenience stores than their aggressive positioning as breakfast competitors to traditional QSRs. C-stores are stepping up their breakfast game, with chains like 7-Eleven debuting breakfast lineups featuring pearl sugar-studded Belgian waffle sandwiches, breakfast tacos, and other offerings that could be right at home in fast casual restaurants.

At breakfast, consumers typically want speed, predictability and value—all attributes convenience stores are known for. Full-service restaurant concepts within c-store footprints now feature made-to-order breakfast sandwiches, premium coffee bars that rival specialty cafes, and bakery programs with fresh pastries.

The technology enabler making this possible is self-service kiosks, which manage morning rush complexity while maintaining the speed customers expect from convenience stores. 66% of customers wish they could get made-to-order food from a convenience store, with Gen Z showing particularly strong demand. Extended breakfast hours capture late-morning and “second breakfast” occasions that traditional restaurants often miss, with some locations serving breakfast items well into the afternoon.

For convenience stores, kiosk hardware faces unique operational demands. “In convenience stores, reliability is the top priority. Many locations operate 24/7 and experience sustained, high-traffic usage, which places significant wear on hardware,” explains Epstein. “We’re seeing strong demand for both self-checkout and self-order kiosks as C-stores expand foodservice offerings. In many cases, they’re starting to resemble QSR environments—something that’s obvious when you look at brands like Wawa, where speed, consistency, and uptime are critical.”

Fresh Food Programs Mature Into Core Business

Foodservice is no longer just an add-on; it is a primary draw for modern convenience stores. Retailers are moving beyond grab-and-go prepared foods to offer chef-driven concepts with in-house food preparation capabilities, including bakeries and full kitchens. Foodservice sales made up 27.7% of in-store sales at convenience stores in 2024 and 38.6% of in-store gross margin, making it one of the most important profit drivers for the channel.

Leading c-store operators are developing proprietary menu items that create brand differentiation rather than relying solely on branded food partners. This requires understanding local taste preferences, predicting demand patterns, managing inventory with precision to minimize waste, ensuring food safety compliance, and maintaining quality standards across multiple locations—operational challenges that mirror full-service restaurant operations.

EV Charging Stations Reshape Store Design

The proliferation of electric vehicle charging infrastructure is fundamentally changing convenience store customer behavior and facility design. Extended dwell times of 20-30 minutes during charging sessions require enhanced amenities beyond traditional grab-and-go offerings. Operators are responding with premium food offerings designed specifically for charging customers, digital ordering integration that allows customers to place orders from their vehicles, and comfortable seating areas with WiFi and work-friendly environments.

This shift creates opportunities to increase average transaction values by offering customers more sophisticated food and beverage options during what would otherwise be idle time. The key is designing the experience around the customer’s need state during the charging period rather than the traditional quick-in-and-out convenience store visit.

Third Place Positioning with Indoor Dining

Following the lead of successful European c-store chains, American convenience stores are investing in comfortable seating, premium WiFi, and work-friendly environments that position them as community gathering spaces beyond transactional fuel stops. Coffee shop ambiance competing directly with enterprise coffee chains includes specialty coffee programs, pastry cases, and environments designed for lingering rather than rushing.

This “third place” strategy—creating spaces that serve as social hubs between home and work—allows c-stores to capture different day parts and occasions. Morning coffee meetings, remote workers seeking afternoon workspaces, and evening social gatherings all represent new occasions that traditional convenience stores rarely captured. The investment in environment and amenities is justified by higher average transaction values and increased visit frequency from customers who view the location as a destination rather than just a pit stop.

Age Verification Technology for Alcohol & Tobacco

Regulatory compliance is driving rapid adoption of age verification technology at self-checkout, including biometric and ID scanning systems that automate compliance while reducing liability and theft. As self-checkout expands throughout convenience stores, operators need solutions built for the unique challenges of convenience retail, like age verification for restricted items, alongside lottery ticket management and fuel pump integration.

These systems reduce both labor requirements and compliance risk by automating a process that previously required employee intervention at every transaction involving age-restricted products. Advanced systems can flag suspicious IDs, maintain audit trails for regulatory compliance, and integrate with existing POS and inventory management platforms.

Payment Technology Gets an Upgrade

Payment technology at kiosks is also evolving rapidly. “We’re seeing the emergence of ‘payment-on-glass’ solutions, where the touchscreen itself functions as the payment device, embedding NFC tap-to-pay directly into the display,” notes Epstein. “These technologies have the potential to reduce hardware complexity, speed up transactions, and simplify kiosk layouts.” Biometric payment options, including palm-based authentication similar to implementations at Whole Foods, are also gaining traction as operators seek to reduce friction in the checkout process.

The Convergence: Technology, Value, and the Blurring of Segment Lines

Three common threads connect these trends across all segments: aggressive technology investment, relentless labor optimization, and unwavering focus on elevated customer experiences that justify pricing in a value-focused market.

Self-service technology serves as a critical connector across fast casual, QSR, and convenience stores. 61% of diners now want more kiosks in restaurants, while studies show order sizes increase 15-30% when customers use self-ordering interfaces. This technology simultaneously addresses labor shortages, improves order accuracy, and drives incremental revenue through strategic upselling prompts—making it one of the highest-ROI investments operators can make.

For restaurant technology providers like Bite, this environment presents a significant opportunity. Solutions that work seamlessly across multiple formats—from fast casual to QSR to convenience stores—that adapt to each segment’s unique operational requirements, and that deliver measurable ROI through increased check sizes, improved accuracy, and optimized labor deployment will be essential partners for operators navigating this complex landscape. The technology that wins in 2026 won’t be the flashiest or most futuristic—it will be the solutions that solve real operational problems, integrate smoothly with existing systems, and deliver results from day one.

Key Data Points

Market Size & Growth Projections:

• U.S. QSR Market: Projected to reach $491.65 billion in 2026, growing to $789.65 billion by 2031 at a 9.94% CAGR (Mordor Intelligence)
• Global QSR Market: Expected to reach $1.16 trillion in 2026, expanding to $1.74 trillion by 2031 at 8.41% CAGR (Mordor Intelligence)
• U.S. Fast Casual Market: Projected to reach $115.5 billion by 2026, growing by $84.5 billion through 2029 at 13.7% CAGR (Technavio)
• Global Breakfast Food Market: Valued at $210 billion in 2026, projected to reach $255 billion by 2030 (Tastewise)

Technology Adoption:

• AI Investment: 38.75% of restaurant executives already investing in AI/ML, with nearly 48% planning adoption soon (Modern Restaurant Management)
• Kiosk Preference: 61% of diners want more kiosks in restaurants, up from 36% two years ago; 72% now comfortable using kiosks (EZ-Chow)
• Digital Ordering: Voice AI and self-service kiosks expected to become industry standard in 2026 (QSR Web)
• Restaurant POS Market: Expected to exceed $62.67 billion in 2026, expanding at 9.5% CAGR through 2035 (Restolabs)

Consumer Behavior:

• Traffic Growth: Less than 1% traffic growth anticipated for 2026, making market share capture critical (Restaurant Dive)
• Value Focus: Pricing convergence around $10-$12 creating intense competition across segments (Restaurant Dive)
• Off-Premise Dining: Drive-thru and delivery channels now account for over 70% of revenue at leading QSR brands (Mordor Intelligence)

C-Store Food Service:

• Foodservice Revenue: Made up 27.7% of in-store sales and 38.6% of in-store gross margin at c-stores in 2024 (Restaurant Business)
• Made-to-Order Demand: 66% of customers wish they could get MTO food from a convenience store, with 72% of those being Gen Z (CStore Decisions)