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With budgets stretched and food inflation lingering, many dining concepts assume that value – specifically, a compelling price-per-food-item ratio – is the key to driving traffic in 2025. And this approach may work: chains like Chili's have shown that an array of deals – such as the 3 For Me and the Triple Dipper Deal – has helped the casual dining brand significantly outpace the wider dining category for more than a year.
But looking at recent QSR traffic trends suggests a more nuanced story. At both McDonald’s and Burger King, the strongest visit lifts in recent months came from experiential promotions and culturally resonant LTOs – not from discounts.
McDonald’s reintroduced its Extra Value Meals on September 8, 2025 – but despite substantial promotional support, the rollout produced only a modest uptick in visits that week. And while traffic improved slightly in the weeks that followed, analyzing recent foot traffic trends highlights that the real inflection points came from experiential activations.
The return of Monopoly, which gave registered app users the chance to win prizes ranging from free food to high-value rewards, sustained elevated visits for weeks through gamification. Boo Buckets sparked a Halloween-season surge driven by nostalgia and collectability and drove a 10.8% increase in weekly visits compared to the January to August weekly visit average. And The Grinch Meal generated the strongest spike of the entire period by tapping into holiday IP and playful packaging. This data highlights that while consumers may appreciate affordability, moments that feel fun, shareable, and culturally relevant may sometimes be more effective at bringing them through the door.
Burger King’s recent performance shows a similar pattern. The rollout of the limited-time Monster Menu generated a stronger visit lift than either Treat Week or Perks Week, both of which focused on giveaways and discounts. The debut of the chain’s nearly $20 Advent Calendar also outperformed Treat Week and Perks Week, underscoring how novelty and excitement may have a greater impact than price-based incentives.
And the strongest surge came with the debut of the SpongeBob Menu, which produced the strongest spike of the entire period and pushed weekly visits well above the January to August average. By pairing a beloved character franchise with themed packaging, kids’ meal tie-ins, and a sense of occasion, Burger King tapped into the same emotional drivers fueling McDonald’s biggest wins.
While price sensitivity will likely continue to influence dining decisions in 2026, recent QSR data underscores an important point: Consumers may be watching their wallets, but price alone doesn’t determine where they choose to eat. Chili’s success shows that a compelling value platform can be a powerful differentiator in full-service dining, where the experience is already baked into the visit. But the same strategy doesn’t automatically translate to the QSR landscape, where affordability is expected and price-based promotions quickly blur together.
Consumers still care about value – but value now spans both price and experience. For full-service restaurants, this means leaning harder into the affordability side of that equation. With ambiance, service, and hospitality already part of the offering, emphasizing everyday value or reliable deal structures may help guests justify dining out more often.
For QSR brands, the calculus is different, and price alone may not be enough to unlock meaningful incremental traffic. Instead, traffic data shows that the strongest results in the QSR space come from experience-driven LTOs, cultural tie-ins, and moments that feel fun, collectible, or social. In other words, fast-food chains may need to focus less on matching grocery-store economics and more on delivering the kind of excitement consumers simply can’t get at home.
As budgets remain tight and expectations continue to evolve, the brands that win won’t be those that chase the lowest price – but those that understand how to deliver the right kind of value for their category: affordability where it matters, and memorable experiences where it counts.
For more data-driven insights, visit placer.ai/anchor.
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.

Black Friday deals may now be spread throughout the month of November – but for the Citadel Outlet’s most passionate shoppers, nothing beats the rush of standing in line with thousands of other eager customers awaiting the chance to be the first to scoop up deals. This year, the mall opened on Thanksgiving night once again – and the foot-traffic data shows that shoppers responded. While most malls in California and across the country saw visits plunge on the holiday, Citadel Outlets experienced a significant surge in traffic, despite being open for only a limited window.
Citadel Outlet as a whole opened Thanksgiving evening at 8pm, with certain stores opening even earlier at 4pm or 6pm. Black Friday sale hours ran until 11pm on Friday, giving these marathon shoppers 27 hours of continuous shopping. People driving northbound on the 5 freeway post-Thanksgiving dinner would have come across lines of cars visible already waiting to get into the Citadel parking lot to get a start on holiday shopping and burn off that turkey by hitting their step count. Once there, exciting experiences awaited, such as a giant Christmas tree and a gingerbread man scavenger hunt.
A quarter of visits to the Citadel on Thursday/Friday actually took place on the Thursday of Thanksgiving itself.
Value seekers came out in abundance, led by Melting Pot Families, Near-Urban Diverse Families, and City Hopefuls per Spatial.ai’s Personalive.
Angelenos were willing to come from afar, with the Citadel shoppers encompassing a whopping 255.5 mile trade area to score their deals on Black Friday alone. They say shopping is a marathon and it appears that for these dedicated customers, nothing beats the thrill of the chase when it comes to saving money.
Ultimately, Citadel Outlets’ Black Friday performance suggests that immersive experiences, extended hours, and a strong value proposition can still transform holiday shopping into a destination-worthy event.
For more data-driven retail insights, visit placer.ai/anchor.
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.

This year’s Candle Day once again drew eager shoppers to Bath & Body Works in search of deeply discounted candles. The in-store portion of the annual sale ran from December 5th through December 7th, 2025, during which traffic increased 266.8% compared to the chain's January to November daily average – a larger boost than that generated by the sale in both 2023 and 2024. This impressive visit surge suggests that shoppers are still willing to invest in affordable, emotionally resonant, or tradition-linked discretionary goods, provided the perceived value is high.
The sale also drove a noticeable spike in morning traffic, with roughly one-fifth of visits occurring before noon during Candle Day – up from the typical 17.1%.
Candle Day's strong showing highlights how brand appeal and strong value can still generate strong consumer interest – even as household budgets remain under pressure.
By pairing compelling pricing with strong brand identity and holiday timing, Bath & Body Works has succeeded in turning a discretionary product into a seasonal ritual that reliably drives engagement. Much like Starbucks’ Pumpkin Spice Latte phenomenon – where limited availability and emotional resonance generate recurring traffic spikes – Candle Day leverages anticipation, tradition, and value to prompt purchases that might otherwise be deprioritized.
For more data-driven insights, visit placer.ai/anchor.
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.

As the 2025 holiday season kicks off, Starbucks and Dunkin’ continue to see strong consumer engagement, with both brands outperforming their 2024 traffic levels and capitalizing on early seasonal launches.
Both Starbucks and Dunkin’ outperformed their 2024 traffic levels in Q3 2025. Starbucks visits rose 0.7% year-over-year in Q3, following slight declines in Q1 (-1.0%) and Q2 (-0.2%). Dunkin’ showed a similar trajectory – rebounding from a 1.8% drop in Q1 to a 1.7% increase in both Q2 and Q3.
These gains suggest that both brands have successfully reignited customer visits heading into the critical holiday season, when limited-time drinks and seasonal marketing tend to drive engagement.
The weekly data highlights the impact of seasonal offerings in the coffee space. Starbucks’ Bearista launch – on the same day as the holiday menu rollout – proved to be a major traffic driver, propelling visits up 11.9% year-over-year during the week of its launch. And the strong visit trends continued the following week with a 6.2% YoY increase, helped by an impressive “Red Cup Day” performance and highlighting Starbucks' capacity for generating demand with limited-time offerings.
Meanwhile, Dunkin’s Wicked collab – announced along with its holiday menu rollout – also generated traffic boosts, with visits up 3.5% to 3.6% YoY during the two weeks following the launch.
As competition in the coffee category intensifies, both brands’ early-season success highlights the growing importance of timing and tradition in driving visit growth.
For more data-driven consumer insights, visit placer.ai/anchor.
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.
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November 2025 marked the strongest November office attendance since 2019, with average daily visits on working days reaching a five-year high – although regional patterns diverged.
Office visits in November 2025 were 36.3% lower than in November 2019 – marking an improvement over November 2024 but falling slightly behind November 2023.
But monthly totals don’t always reflect true office activity, since the number of working days can vary from year to year. November 2025 began on a Saturday, giving the month five full weekends and the fewest working days of any November from 2019 to 2025. When we shift from looking at total visits to examining average visits per working day compared to November 2019–2024, a different picture emerges: office attendance on working days reached its highest level in five years.
As in recent months, Miami continues to lead the office recovery, pulling ahead of other major markets – including New York City. Many firms relocated to or expanded in Miami in recent years, contributing to the growth of the professional-services sector and boosting demand for office space and in-person work.
Meanwhile, New York City – which had led the nationwide office recovery in July – has been falling increasingly behind Miami. One possible factor is the city’s white collar workforce's reliance on long, transit-heavy commutes: as temperatures drop and weather worsens, many NYC commuters reduce their in-office days, while Miami’s more car-dependent workforce is less affected by seasonal conditions.
Meanwhile, San Francisco is posting some of the strongest year-over-year gains in office visits nationwide. Despite suffering some of the steepest office occupancy declines during the pandemic, the city is now mounting one of the most robust recoveries – perhaps helped by the recent AI boom which has attracted new tech talent to San Francisco.
Other cities with a strong tech scene – including Denver, Chicago, and Boston, have also posted solid YoY gains – although these markets continue to trail the nationwide average when comparing current office visit rates to pre-pandemic.
By contrast, Houston and Washington, D.C. showed YoY declines. Houston's office traffic may be impacted by the slower energy markets, while Washington, D.C. office trends were likely dampened by the government shutdown, which ended on November 12. (Although Placer.ai’s Washington, D.C. office index does not track government buildings, much of the private sector in the city is closely tied to federal agencies, so paused meetings and reduced client activity during the shutdown likely impacted in-office attendance across the board.)
These patterns highlight the growing influence of local dynamics in shaping the future of office work, with Miami’s momentum, San Francisco’s tech revival, and the strength of other innovation hubs revealing how regional conditions drive in-office activity.
For more data-driven insights, visit placer.ai/anchor.
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.

Dave’s Hot Chicken and Dutch Bros represent two stages of competitive maturity in the dining industry. Dave’s, the rookie powerhouse, is still in its breakout phase – driven by speed, excitement, and growth at any cost. Dutch Bros, on the other hand, is the seasoned veteran entering a more disciplined period of its career, focused on refinement, endurance, and strategic precision.
A snapshot of nationwide foot traffic data clearly shows the difference between the two brands. Between January and October 2025, Dave’s Hot Chicken recorded a remarkable 59.3% increase in total visits, driven by an aggressive pace of new openings. And the average number of visits to each individual store also rose 4.8%, signaling robust and growing demand.
Dutch Bros, meanwhile, experienced a more measured 13.1% growth in total visits, with visits per location holding steady at 0.2%. This stability suggests that while new units continue to perform, many established markets are reaching maturity – a hallmark of a seasoned brand transitioning from rapid expansion to optimization.
The contrast between the two brands becomes even more striking when analyzing major markets. While Dutch Bros’ visit growth reflects slower gains tied to market maturity, Dave’s is posting explosive per-location surges in major DMAs like Chicago (+18.4%), Orlando (+15.5%), and Houston (+15.0%). It’s the classic rookie hot streak – fast, fearless, and full of momentum.
Dutch Bros is now a massive operation with 1,080 locations in 24 states as of September 2025. Though much of the company's early growth was achieved through a franchise system, Dutch Bros stopped selling franchises to operators who didn’t grow up in the company in 2008 – and stopped franchising completely in 2017 to maintain consistency and preserve its distinctive brand and culture.
Today, only about 30% of Dutch Bros locations are franchise-operated. And as illustrated by the map below, while new stores are fueling growth, older markets – particularly in the Pacific Northwest – are reaching maturity. Dutch Bros is no longer just sprinting to open new stores; it’s managing endurance and refining its playbook – optimizing store placement, leveraging data analytics, and deepening engagement through its digital rewards program. This maturity mirrors what Starbucks went through two decades ago: fewer easy wins, but a much higher floor for long-term performance.
Then there’s Dave’s Hot Chicken – fast, fearless, and still in its hyper-growth phase. From a parking-lot pop-up in 2017 to around 300 locations today, Dave’s is scaling at a speed rarely seen in food service.
Like Dutch Bros in its early days, Dave’s still embraces a franchise-first approach. Backed by Roark Capital and celebrity investors including Drake, the brand is leveraging multi-unit operators to plant flags nationwide and abroad. The company aims to open 150 new locations a year and recently signed an 180-unit European deal with Azzurri Group – proof that the rookie’s winning streak is turning into a global phenomenon.
And the map below highlights how Dave’s Hot Chicken is playing offense with no signs of slowing down. The brand’s franchise-first model allows for rapid scaling with lower capital risk, while Roark Capital’s involvement brings big-league operational infrastructure. But like any breakout player, the challenge will be endurance – ensuring franchisees maintain consistency and profitability as the system races toward 1,000+ units.
For operators and investors, the Dutch Bros/Dave’s contrast is a roadmap to growth sequencing. Early-stage brands can learn from Dave’s: Invest in buzz, speed, and market saturation while consumer curiosity is high. Maturing chains, on the other hand, can look to Dutch Bros as proof that disciplined growth, data-led decisions, and cultural integrity are what sustain relevance once expansion slows.
For more data-driven insights, visit placer.ai/anchor
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.

1. Expanded grocery supply is increasing overall category engagement. New locations and deeper food assortments across formats are bringing shoppers into the category more often, rather than fragmenting demand.
2. Grocery visit growth is being driven by low- and middle-income households. Elevated food costs are leading to more frequent, budget-conscious trips, reinforcing grocery’s role as a non-discretionary category.
3. Short, frequent trips are a major driver of brick-and-mortar traffic growth. Fill-in shopping, deal-seeking, and omnichannel behaviors are pushing visit frequency higher, even as trip duration declines.
4. Scale is accelerating consolidation among large grocery chains. Larger retailers are using their size to invest in value, assortment, private label, and execution, allowing them to capture longer and more engaged shopping trips.
5. Both large and small grocers have viable paths to growth. Large chains are winning by competing for the full grocery list, while smaller banners can grow by specializing, owning specific missions, or offering compelling value that earns them a place in shoppers’ routines.
While much of the retail conversation going into 2026 focused on discretionary spending pressure, digital substitution, and higher-income consumers as the primary drivers of growth, grocery foot traffic tells a different story.
Rather than being diluted by new formats or eroded by e-commerce, brick-and-mortar grocery engagement is expanding. Visits are rising even as grocery supply spreads across wholesale clubs, discount and dollar stores, and mass merchants. At the same time, growth is being powered not by affluent trade areas, but by low- and middle-income households navigating higher food costs through more frequent, targeted trips. Shoppers are showing up more often and increasingly splitting their trips across retailers based on value, availability, and mission – pushing grocers to compete for portions of the grocery list instead of the full weekly basket.
The data also suggests that the largest grocery chains are capturing a disproportionate share of rising grocery demand – but the multi-trip nature of grocery shopping in 2026 means that smaller banners can still drive traffic growth. By strengthening their value proposition, specializing in specific products, or owning specific shopping missions, these smaller chains can complement, rather than compete with, larger one-stop destinations.
Ultimately, AI-based location analytics point to a clear set of grocery growth drivers in 2026: expanded supply that increases overall engagement, more frequent and mission-driven trips, and continued traffic concentration among large chains alongside new opportunities for smaller banners.
One driver of grocery growth in recent years is simply the expansion of grocery supply across multiple retail formats. Wholesale clubs are constantly opening new locations and discount and dollar stores are investing more heavily in their food selection, giving consumers a wider choice of where to shop for groceries. And rather than fragmenting demand, this broader availability appears to have increased overall grocery engagement – benefiting both dedicated grocery stores and grocery-adjacent channels.
Grocery stores continue to capture nearly half of all visits across grocery stores, wholesale clubs, discount and dollar stores, and mass merchants. That share has remained remarkably stable thanks to consistent year-over-year traffic growth – so even as grocery supply increases across categories, dedicated grocery stores remain the primary destination for food shopping.
Meanwhile, mass merchants have seen a decline in relative visit share as expanding grocery assortments at discount and dollar stores and the growing store fleets of wholesale clubs give consumers more alternatives for one-stop shopping.
While much of the broader retail conversation heading into 2026 centers on higher-income consumers carrying growth, the trend looks different in the grocery space. Recent visit trends show that grocery growth has increasingly shifted toward lower- and middle-income trade areas, underscoring the distinct dynamics of non-discretionary retail.
For lower- and middle-income shoppers, elevated food costs appear to be translating into more frequent grocery trips as consumers manage budgets through smaller baskets, deal-seeking, and shopping across retailers. In contrast, higher-income households – often cited as a key growth engine for discretionary retail – are contributing less to grocery visit growth, likely reflecting more stable shopping patterns or a greater ability to consolidate trips or shift spend online.
This means that, in 2026, grocery growth is not being propped up by high-income consumers. Instead, it is being fueled by necessity-driven shopping behavior in lower- and middle-income communities – reinforcing grocery’s role as an essential category and suggesting that similar dynamics may be at play across other non-discretionary retail segments.
Another factor driving grocery growth is the rise in short grocery visits in recent years. Between 2022 and 2025, the biggest year-over-year visit gains in the grocery space went to visits under 30 minutes, with sub-15 minute visits seeing particularly big boosts. As of 2025, visits under 15 minutes made up over 40% of grocery visits nationwide – up from 37.9% of visits in 2022.
This shift toward shorter visits – especially those under 15 minutes – is driven in part by the continued expansion of omnichannel grocery shopping, as many consumers complete larger stock-up orders online and rely on in-store trips for order collection or quick, fill-in needs. At the same time, the rise in short visits paired with consistent YoY growth in grocery traffic points to additional, behavior-driven forces at play – consumers' growing willingness to shop around at different grocery stores in search of the best deal or just-right product.
Value-conscious shoppers – particularly consumers from low- and middle-income households, which have driven much of recent grocery growth – seem to be increasingly shopping across multiple retailers to secure the best prices. This behavior often involves making targeted trips to different stores in search of the strongest deals, a pattern that is contributing to the rise in shorter, more frequent grocery visits. At the same time, other grocery shoppers are making quick trips to pick up a single ingredient or specialty item – perhaps reflecting the increasingly sophisticated home cooks and social media-driven ingredient crazes. In both these cases, speed is secondary to getting the best value or the right product.
So while some shorter visits reflect a growing emphasis on efficiency – as shoppers use in-store trips to complement primarily online grocery shopping – others appear driven by a preference for value or product selection over speed. Despite their differences, all of these behaviors have one thing in common – they're all contributing to continued growth in brick-and-mortar grocery visits. Grocers who invest in providing efficient in-store experiences are particularly well-positioned to benefit from these trends.
As early as 2022, the top 15 most-visited grocery chains already accounted for roughly half of all grocery visits nationwide. And by outpacing the industry average in terms of visit growth, these chains have continued to capture a growing share of grocery foot traffic.
This widening gap suggests that scale is increasingly enabling grocers to reinvest in the factors that attract and retain shoppers. Larger chains are better positioned to invest in broader and more differentiated product selection, stronger private-label programs that deliver quality at accessible price points, competitive pricing, and operational excellence across stores and omnichannel touchpoints. These capabilities allow top chains to serve a wide range of shopping missions – from quick, convenience-driven trips to more intentional visits in search of the right product or ingredient.
Consolidation at the top of the grocery category is reinforcing a virtuous cycle: scale enables better value, selection, and experience, which in turn draws more shoppers into stores and supports continued grocery traffic growth.
In 2025, the top 15 most-visited grocery chains accounted for a disproportionate share of visits lasting 15 minutes or more, while smaller grocers captured a larger share of the shortest trips. As shown above, larger grocery chains, which tend to attract longer visits, grew faster than the industry overall – but short visits, which skew more heavily toward smaller chains, accounted for a greater share of total traffic growth. Together, these patterns show that both long, destination trips and short, targeted visits are driving grocery traffic growth and creating viable paths forward for retailers of all sizes.
Larger chains are more likely to serve as destinations for fuller shopping missions, competing for the entire grocery list – or a significant share of it. But smaller banners can grow too by competing for more short visits. By specializing in a specific product category, owning a clearly defined shopping mission, or delivering a compelling value proposition, smaller grocers can earn a place in shoppers’ routines and become a deliberate stop within a broader grocery journey.
As grocery moves deeper into 2026, growth is being driven by the cumulative effect of how consumers are navigating food shopping today. Expanded supply has increased overall engagement, higher food costs are driving more frequent and targeted trips, and shoppers are increasingly willing to split their grocery list across retailers based on value, availability, and mission.
Looking ahead, this suggests that grocery growth will remain resilient, but unevenly distributed. Retailers that clearly understand which trips they are best positioned to win – and invest accordingly – will be best placed to capture that growth. Large chains are likely to continue benefiting from scale, consolidation, and their ability to serve full shopping missions, while smaller banners can grow by earning a defined role within shoppers’ broader grocery journeys. In 2026, success in grocery will be less about winning every trip and more about consistently winning the right ones.

To optimize office utilization and surrounding activity in 2026, stakeholders should:
1. Plan for continued, but slower, office recovery. Attendance continues to rise and has reached a post-pandemic high, but moderating growth suggests the return-to-office may progress at a more gradual and incremental pace than in prior years.
2. Account for growing seasonality in office staffing, local retail operations, and municipal services. As office visitation becomes increasingly concentrated in late spring and summer, offices, downtown retailers, and cities may need to plan for more predictable peaks and troughs by adjusting hours, staffing levels, and local services accordingly, rather than relying on annual averages.
3. Align leasing strategies with seasonal demand. Stronger attendance in Q2 and Q3 suggests these quarters are best suited for leasing activity, while softer Q1 and Q4 periods may be better used for renovations, repositioning, and targeted activation efforts designed to draw workers in.
4. Design hybrid policies around midweek anchor days. With Tuesdays and Wednesdays consistently driving the highest office attendance, employers can maximize collaboration and space utilization by concentrating meetings, programming, and in-office expectations midweek.
5. Reduce early-week commute friction to support attendance. Monday office attendance appears closely correlated with commute ease, suggesting that reliable and efficient transportation may be an important factor in early-week office recovery.
6. Prioritize proximity in leasing and development decisions. Visits from employees traveling less than five miles to work have increased steadily since 2019, reinforcing the value of centrally located offices and housing near employment hubs.
2025 was the year of the return-to-office (RTO) mandate. Employers across industries – from Amazon to JPMorgan Chase – instituted full-time on-site requirements and sought to rein in remote work. But the year also underscored the limits of policy. As employee pushback and enforcement challenges mounted, many organizations turned to quieter tactics such as “hybrid creep” to gradually expand in-office expectations without triggering outright resistance.
For employers seeking to boost attendance, as well as office owners, retailers, and cities looking to maximize today’s visitation patterns, understanding what actually drives employee behavior has become more critical than ever. This reports dives into the data to examine office visitation patterns in 2025 – and explore how structural factors such as weather, commute convenience, and workplace proximity have emerged as key differentiators shaping how and when, and how often workers come into the office.
National office visits rose 5.6% year over year in 2025, bringing attendance to just 31.7% below pre-pandemic levels and marking the highest point since COVID disrupted workplace routines. At the same time, the pace of growth slowed compared to 2024, signaling a possible transition into a steadier phase of recovery.
With new return-to-office mandates expected in 2026, and the balance of power quietly shifting towards employers, additional gains remain likely. But the trajectory suggested by the data points toward gradual progress rather than a return to the more rapid rebounds seen in 2023 or 2024.
Before COVID, “I couldn’t come in, it was raining” would have sounded like a flimsy excuse to most bosses. But today, weather, travel, and individual scheduling are widely accepted reasons to stay home, reflecting a broader assumption that face time should flex around convenience.
This shift is visible in the growing seasonality of office visitation, which has intensified even as overall attendance continues to rise. In 2019, office life followed a relatively steady year-round cadence, with only modest quarterly variation after adjusting for the number of working days. In recent years, however, greater seasonality has emerged. Since 2024, Q1 and Q4 have consistently underperformed while Q2 and Q3 have posted meaningfully stronger attendance – a pattern that became even more pronounced in 2025. Winter weather disruptions, extended holiday travel, and the growing normalization of “workations” appear to be pulling some visits out of the colder, holiday-heavy months and concentrating them into late spring and summer.
For employers, office owners, downtown retailers, and city planners, this emerging seasonality matters. Staffing, operating budgets, and programming decisions increasingly need to account for predictable soft quarters and peak periods, making quarterly planning a more useful lens than annual averages. Leasing activity may also convert best in Q2 and Q3, when districts feel most active. Slower quarters, meanwhile, may be better suited for renovations, construction, or employer- and city-led programming designed to give workers a reason to show up.
The growing premium placed on convenience is also evident in the persistence of the TGIF workweek – and in the factors shaping its regional variability.
Before COVID, Mondays were typically the busiest day of the week, followed by relatively steady attendance through Thursday and a modest drop-off on Fridays. Today, Tuesdays and Wednesdays have firmly established themselves as the primary anchor days, while Mondays and Fridays see consistently lower activity. And notably, this pattern has remained essentially stable over the past three years – despite minor fluctuations – as workers continue to cluster their in-office time around the days that offer the most perceived value while preserving flexibility at the edges of the week.
At the same time, while the hybrid workweek remains firmly entrenched nationwide, its contours vary significantly across regions – and the data suggests that convenience is once again a key differentiator.
Across major markets, a clear pattern emerges: Cities with higher reliance on public transportation tend to see weaker Monday office attendance, while markets where more workers drive alone show stronger early-week presence. While industry mix and local office culture still matter, the data points to commute hassle as another factor potentially shaping Monday attendance.
New York City, excluded from the chart below as a clear outlier, stands as the exception that proves the rule. Despite nearly half of local employees relying on public transportation (48.7% according to the Census 2024 (ACS)), the city’s extensive and deeply embedded transit system appears to reduce perceived friction. In 2025, Mondays accounted for 18.4% of weekly office visits in the city, even with heavy transit usage.
The contrast highlights an important nuance: Where transit is fast, frequent, and integrated into daily routines, it can support office recovery, offering a potential roadmap for other dense urban markets seeking to rebuild early-week momentum.
Another powerful signal of today’s convenience-first mindset shows up in commute distances. Since 2019, the share of office visits generated by employees traveling less than five miles has steadily increased, largely at the expense of mid-distance commuters traveling 10 to 25 miles.
To be sure, this metric reflects total visits rather than unique visitors, so the shift may be driven by increased visit frequency among workers with shorter, simpler commutes rather than a change in where employees live overall. Still, the pattern is telling: Workers with shorter commutes appear more likely to generate repeat in-person visits, while longer and more complex commutes correspond with fewer trips. Over time, this dynamic could shape office leasing decisions, residential demand near employment centers – whether in urban cores or in nearby suburbs – and the geography of the workforce.
Taken together, the data paints a clear picture of the modern return-to-office landscape. Attendance is rising, but behavior is no longer driven by mandates alone. Instead, workers are making rational, convenience-based decisions about when coming in is worth the effort.
For cities, the implication is straightforward: Ease of access matters. Investments in transit reliability, last-mile connectivity, and housing near employment centers can all play a meaningful role in shaping how consistently people show up. For employers, too, the lesson is that the path back to the office runs through convenience, not just compulsion, as attendance gains are increasingly driven by how effectively organizations reduce friction and increase the perceived value of being on-site.

1. AI is raising the bar for physical retail as shoppers arrive more informed, more intentional, and less tolerant of friction – though the impact varies by category and format.
2. As discovery shifts upstream, stores increasingly serve as confirmation rather than discovery points where shoppers validate decisions through hands-on experience and expert guidance.
3. AI-based tools can improve in-store performance by removing operational friction – shortening trips in efficiency-led formats and supporting deeper engagement in experience-led ones.
4. By embedding expertise directly into frontline workflows, AI helps retailers deliver consistent, high-quality service despite high turnover and limited training windows.
5. AI enables precise, location-specific marketing and execution, allowing retailers of any size to align assortments, staffing, and messaging with real local demand.
6. Retailers can also use AI to manage their store fleets with greater discipline and understand where to expand, where to avoid cannibalization, and where to rightsize based on observed demand rather than static assumptions.
7. AI is not a universal lever in physical retail; its value depends on the store format, and in discovery-driven models it should support operations behind the scenes rather than reshape the customer experience.
Physical retail has faced repeated claims of obsolescence, from the rise of e-commerce to the shock of COVID. Each time, analysts predicted a structural decline in brick-and-mortar. And each time, physical retail adapted.
AI has triggered a similar round of predictions. Much of the current discussion frames retail’s future as a binary outcome: either stores become heavily automated, or e-commerce becomes so optimized that physical locations lose relevance altogether.
But past disruptions point in a different direction. E-commerce changed how physical retail operated by raising expectations for omnichannel integration, speed, and clarity of purpose. Retailers that adjusted store formats, merchandising, and operations accordingly went on to drive sustained growth.
AI likely represents another inflection point for physical retail. As shoppers arrive with more information, clearer intent, and even less tolerance for friction than in the age of "old-fashioned" e-commerce, physical stores will remain – but the standards they are held to continue to rise.
This report presents four ways retailers are using AI to get – and stay – ahead as physical retail adapts to this next wave of disruption.
E-commerce moved discovery earlier in the shopping journey. Instead of beginning the process in-store, many shoppers now arrive at brick-and-mortar locations after having deeply researched products, comparing options, and narrowing choices online – entering the store to validate rather than initiate their purchasing decision.
AI-powered shopping accelerates this pattern. Conversational assistants, recommendation engines, and AI-driven discovery across search and social reduce the time and effort required to evaluate options – and this shift is changing consumers' expectations around the in-store experience.
Apple shows what it looks like when a physical store is built for well-informed shoppers. Given the prevalence of AI-powered search and assistants in high-consideration categories like consumer electronics, Apple customers likely arrive at the Apple Store with more preferences already shaped by AI-assisted research than other retail categories.
Apple Stores were designed for this kind of customer long before AI became widespread. The layout puts working products directly in customers’ hands, merchandising emphasizes live use over promotional signage, and associates are trained to answer detailed technical questions rather than walk shoppers through basic options.
That alignment is showing up in store behavior. Even as AI-powered shopping expands, Apple Stores continue to see rising foot traffic and longer visits thanks to the store's specific and curated role in the customer journey – a place where customers confirm decisions through hands-on experience and expert guidance.
Some applications of AI extend trends that e-commerce has already introduced. Others address operational challenges that previously required manual coordination or tradeoffs.
AI can reduce friction and make store visits more predictable by improving staffing allocation, reducing checkout delays, optimizing inventory placement, and managing traffic flow. These changes reduce friction without altering the visible customer experience.
Sam's Club offers a clear, recent example of AI solving a specific in-store bottleneck. For years, customers completed checkout only to face a second line at the exit, where an employee manually scanned paper receipts and spot-checked carts.
In early 2024, Sam’s Club introduced computer vision-powered exit gates, allowing customers to exit the store without stopping as AI algorithms instantly captured images of the items in their carts and matched them against digital purchase data. Employees previously tasked with receipt checks could now shift their focus to member assistance and in-store support.
The impact was measurable. Sam’s Club reported that customers now exit stores 23% faster than under manual receipt checks, a result confirmed by a sustained nationwide decline in average dwell time. During the same period, in-store traffic increased 3.3% year-over-year – demonstrating how removing friction with AI can deliver tangible gains.
AI optimizes stores for different outcomes. At Sam’s Club, it shortens visits by removing friction from task-driven trips. At Apple, upstream research leads to longer visits focused on testing, questions, and decision validation. In both cases, AI aligns store execution with shopper intent – prioritizing speed and throughput in efficiency-led formats and deeper engagement in experience-led ones.
Beyond shaping store roles and streamlining operations, AI can also address a long-standing challenge in physical retail: delivering consistent, high-quality expertise on the sales floor despite high turnover and seasonal staffing. In the past, retailers relied on heavy training investments that often failed to pay off. AI can now embed that expertise directly into frontline workflows, allowing associates to deliver confident, informed service regardless of tenure and strengthening the in-store experience at scale.
In May 2025, Lowe’s rolled out a major in-store AI enhancement called Mylow Companion, an AI-powered assistant that equips frontline staff with real-time, expert support on product details, home improvement projects, inventory, and customer questions.
Mylow Companion is embedded directly into associates’ handheld devices, delivering instant guidance through natural, conversational interactions, including voice-to-text. This enables even newly hired employees to provide confident, expert-level advice from day one, while helping experienced associates upsell and cross-sell more effectively. The tool complements Mylow, a customer-facing AI advisor launched the same year to help shoppers plan projects and discover the right products, leading to increased customer satisfaction.
While AI alone cannot solve demand challenges—especially amid macroeconomic pressure on large-ticket discretionary spending—early signals suggest it may still play a meaningful role. Location analytics indicate narrowing year-over-year visit gaps at Lowe’s post-deployment, pointing to a potentially improved in-store experience. And Home Depot’s recent announcement of agentic AI tools developed with Google Cloud suggests that these technologies are becoming table stakes in this category.
As more retailers roll out similar capabilities, those that moved earlier are better positioned to help set the bar – and benefit as the market adapts.
Beyond improving the in-store experience, AI also gives retailers a powerful way to drive foot traffic through precision marketing. By processing large volumes of behavioral, location, and timing data, AI can help retailers decide who to reach, when to engage them, where to activate, and what message or assortment will resonate – shifting marketing from broad seasonal pushes to campaigns grounded in local demand.
Target offers an early example of this approach before AI became widespread. Stores near college campuses have long tailored assortments and messaging around the academic calendar, especially during the back-to-school season. In August, these locations emphasize dorm essentials, compact storage, bedding, tech accessories, and affordable décor – supported by campaigns aimed at students and parents preparing for move-in. That localized approach has been effective in driving in-store traffic to Target stores near college campuses, with these venues seeing consistent visit spikes every August and outperforming the national average across multiple back-to-school seasons from 2023 to 2025.
AI makes local execution repeatable at scale. By analyzing visit patterns, past performance, and timing signals across thousands of locations, retailers can decide which products to promote, how to staff stores, and when to run campaigns at each location. Marketing, merchandising, and store operations then act on the same demand signals instead of separate assumptions.
Crucially, AI makes this level of localization accessible to retailers of all sizes. What once required the resources and institutional knowledge of a big-box giant can now be achieved through precision marketing and demand forecasting tools, allowing brands to adapt each store’s messaging, assortment, and execution to the unique rhythms of its community.
Beyond improving performance at individual stores, AI can also give retailers a clearer view of how their entire store fleet is working – and where it should grow, contract, or change. By analyzing foot traffic patterns, trade areas, customer overlap, and visit frequency across locations, AI helps retailers identify which sites are truly reaching their target audiences and which are underperforming relative to local demand.
AI also plays a critical role in smarter expansion. Retailers can use it to identify markets and neighborhoods where demand is growing, customer overlap is low, and incremental visits are likely – reducing the risk of cannibalization when opening new stores. By modeling how shoppers move between existing locations, AI can flag when a proposed site will attract new customers versus simply shifting traffic from nearby stores, grounding expansion decisions in observed behavior rather than demographic proxies or intuition alone.
Equally important, AI helps retailers recognize when expansion no longer makes sense. By tracking total fleet traffic, visit growth, and trade-area saturation, retailers can assess whether new stores are adding net demand or diluting performance. The same signals can identify locations where demand has structurally declined, informing rightsizing decisions and store closures. In this way, AI supports a more disciplined approach to physical retail – one that treats the store fleet as a dynamic system to be optimized over time, rather than a footprint that only grows.
The impact of AI on physical retail will vary significantly by category and format. Not every successful store experience is built around efficiency, prediction, or pre-qualification. Retailers with clearly differentiated offline value don’t necessarily benefit from forcing AI into customer-facing experiences that dilute what makes their stores work.
“Treasure hunt” formats are a clear example. Off-price retailers like TJ Maxx, Marshalls, Ross, and Burlington continue to drive strong traffic by offering unpredictability, scarcity, and discovery that cannot be replicated – or meaningfully enhanced – through AI-driven search or recommendation. The appeal lies precisely in not knowing what you’ll find. For these retailers, heavy investment in AI-led personalization or pre-shopping guidance risks undermining the core experience rather than improving it.
Similar dynamics apply in other categories. Independent boutiques, vintage stores, resale shops, and certain specialty retailers succeed by offering curation, serendipity, and human taste rather than optimization. In these cases, AI may still play a role behind the scenes – supporting inventory planning, pricing, or site selection – but it should not reshape the customer-facing experience. AI is most valuable when it reinforces a retailer’s existing value proposition. Formats built around discovery, surprise, or experiential browsing should protect those strengths, even as other parts of the retail landscape move toward greater efficiency and intent-driven shopping.
AI is forcing physical retail to evolve with intention. By creating a supportive environment for customers who arrive with made-up minds, removing friction inside the store, offering the best in-store services, and orchestrating demand with greater precision, retailers are adapting to the new world standards set by AI. All five strategies focus on aligning stores with shopper intent – what customers want, how the store supports it, and when the interaction happens.
The retailers that win in this next era won’t be the ones that use AI to simply automate what already exists. They’ll be the ones that use it to sharpen the role of physical retail – turning stores into places that help shoppers validate decisions, deliver value beyond convenience, and show up at exactly the right moment in a customer’s journey.
In the age of AI, physical retail wins by becoming more intentional – designed around informed shoppers, optimized for the right outcome in each format, and activated at moments when demand is real.
