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U.S. consumer activity looked relatively stable in the first half of 2025, with year-over-year (YoY) retail and dining traffic (shown in the chart below) staying mostly positive or flat through May – aside from February, when extreme cold and leap year comparisons drove declines.
But momentum shifted in June, when both categories slipped into negative territory, and the softness persisted in July before worsening in August. The late-summer weakness suggests that what began as a temporary cooling may now be evolving into a broader consumer slowdown.
Looking at state-level data reveals that the pullback is not isolated to a few regions. Western states such as Idaho and Utah – where H1 2025 dining traffic rose 2.1% and 2.4% YoY, respectively – flattened out, with visits in July and August down 0.2% and 0.1%, respectively. And states that had already experienced flat visits or dining softness in H1 2025 saw their visit gaps grow further: YoY dining traffic in New York State declined from -1.2% to -2.3%, while California saw its visits swing from +0.3% in H1 2025 to -2.0% in July and August 2025. Only in Vermont and Rhode Island did YoY dining visits actually increase over the summer.
Statewide retail traffic trends also point to broad-based declines in consumer activity, as visits to retail chains nationwide fell compared to July-August 2024 – even in regions such as the Pacific Northwest and the Southwest that had experienced high consumer resilience in H1 2025. Vermont, joined this time by Delaware, once again stood out as an outlier.
A key driver of the slowdown is the widening gap between higher- and lower-income households. While wealthier consumers have continued to prop up overall spending, middle- and lower-income groups are scaling back. Even among high earners, international summer travel may have drawn dollars away from U.S. retail and dining, softening domestic foot traffic during the analyzed period. This dynamic highlights the risks of relying too heavily on affluent households to sustain consumer activity.
Tariffs have added another layer of complexity. Earlier in the year, many consumers rushed to make purchases ahead of anticipated price hikes. Now, the lingering financial impact of those spring splurges may still be weighing on budgets.
Looking ahead to the holiday season, discretionary fatigue looms large. Spending is expected to slow, led by a sharper cutback from Gen Z. Budget-conscious households may already be tightening their belts in preparation for holiday expenses, further dampening retail and dining performance.
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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With summer just behind us, we dove into the data to see how office visitation fared in August 2025. Did July’s impressive recovery momentum hold, or did seasonal factors slow the pace?
Visits to the Placer.ai Nationwide Office Building Index registered a 34.3% decline in August 2025 compared to the same period in 2019 – a wider gap than that seen in August 2023, and an even more notable retreat from July's encouraging 21.8% deficit.
However, this apparent setback is largely due to calendar differences: August 2025 had only 21 working days, compared to 22 in both August 2024 and 2019, and 23 in August 2023. When normalized for average visits per workday, August 2025 actually outperformed August 2023.
Seasonal dynamics also likely played a crucial role. August represents peak vacation season, and just as employees often embrace remote work on Fridays to extend weekends, they likely embrace similar flexibility during the peak summer travel season. Organizations may also relax in-office requirements when substantial portions of their workforce are taking time off.
So rather than signaling a genuine return-to-office (RTO) reversal, August's softer performance likely reflects the intersection of compressed work calendars and seasonal vacation patterns, with the underlying recovery trajectory remaining fundamentally intact.
The August effect impacted major markets nationwide, including New York and Miami – both of which achieved full recovery in July yet posted year-over-six-year gaps in excess of 10.0% last month. But while gaps widened across most markets, San Francisco once again avoided last place, ranking ahead of Chicago in post-pandemic office recovery metrics. Despite still facing below-average office attendance relative to 2019 levels, the Bay Area market’s renewed momentum – bolstered by increased AI-sector leasing activity – continues drawing employees back to offices even amid summer distractions.
San Francisco also ranked among August's year-over-year (YoY) office visit recovery leaders, providing further evidence of the city’s robust recovery momentum. But it was Chicago that claimed the top spot with a 12.5% year-over-year (YoY) gain – encouraging progress for the Windy City, though it remains to be seen whether this signals the beginning of a lasting turnaround.
Meanwhile, Boston also exceeded the nationwide year-over-year average of 2.9% with a 3.1% increase, while Washington, D.C. lagged behind with a YoY decline of 3.9%.
As we noted in July, the office recovery path is anything but linear. Months of significant progress are often followed by more sluggish periods – and August 2025 exemplifies how seasonality and calendar differences can obscure underlying trends.
Will September 2025 set a new RTO record as kids return to school and employees refocus?
Follow Placer.ai/anchor to find out.
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

Following modest gains to the Placer.ai Industrial Index in June and July, foot traffic to U.S. manufacturing facilities fell 5.6% year over year in August 2025. So even as order books improved in July, operators seem to have scaled back in-plant activity and nonessential visits to navigate cost and policy uncertainty.
Several national and regional gauges underscore the divergence in August. S&P Global’s Manufacturing PMI jumped to 53.0, its highest since May 2022, as firms built inventory amid worries over prices and supply constraints. Meanwhile, ISM's Production Index fell to 47.8% – 3.6 percentage points lower than July's 51.4% – pointing to weaker factory output, and demand for industrial space has fallen recently for the first time in 15 years. The Philadelphia Fed’s August 2025 Manufacturing Business Outlook Survey also showed a decline in general activity as new orders dipped back into negative territory.
Together, these mixed signals mirror Placer.ai's foot-traffic trends: Underlying demand is stabilizing, but managers remain cautious with on-site labor and vendor engagement, with macro uncertainty continuing to translate into swings in on-the-ground activity. Looking ahead, September will reveal whether greater policy clarity and easing cost pressures can help stabilize factory visits after a turbulent summer.
For more data-driven insights, visit placer.ai/anchor.

The same macroeconomic forces pressuring other retail sectors are fueling demand for auto parts: With the U.S. light vehicle fleet now averaging 12.8 years – up from 11.6 in 2019 – and many households delaying new car purchases, aftermarket maintenance has become more essential than ever. And while discretionary upgrades may be postponed, core failure and replacement parts continue to see robust demand. Though tariff-related uncertainty continues to loom, leading retailers report they have managed the impact effectively so far.
Against this backdrop, we dove into the data to check in with AutoZone, O’Reilly Auto Parts, and Advance Auto Parts. How did they fare in Q2 2025? And what awaits them the rest of the year?
AutoZone, the sector's largest chain, continues to expand while growing its customer base. Over the past six years, AutoZone has steadily increased its store count, leaning into growing demand without diluting location-level traffic. Year over year (YoY) too, the chain saw significant visit growth between March and May 2025 – and while June showed some softening, July and August visits remained essentially flat versus 2024, demonstrating stability during the chain’s busy summer maintenance season.
This robust foot traffic performance aligns with the company's recent financials. In its last reporting period (ending May 10, 2025), AutoZone posted a solid 5.0% year-over-year increase in U.S. comparable sales. Commercial performance was especially strong – Do-It-For-Me (DIFM) sales jumped 10.7%, while DIY sales grew 3.0% YoY. And management emphasized that tariff-related impacts have been minimal so far.
O'Reilly Auto Parts is also executing on an impressive expansion strategy. In Q2 2025, overall visits to O’Reilly climbed 4.6% YoY, with same store visits up 3.0%. Compared to 2019, both total and per-location foot traffic has steadily increased, demonstrating the company’s success in combining aggressive growth with operational efficiency.
And in its last reporting quarter, the company posted a 4.1% increase in comparable store sales, with robust performance across both DIY and professional channels. Total sales revenue reached a record $4.53 billion – a 6.0% increase versus last year. The company also noted a modest pricing lift tied to tariffs but emphasized that overall demand trends remain strong.
Advance Auto Parts, for its part, is restructuring to compete more effectively. During the quarter ending July 12th, 2025, net sales fell 7.7% year-over-year, partly due to planned store closures. Still, signs of stabilization are emerging: Comparable-store sales edged up 0.1%, indicating that core demand remains healthy.
And recent foot traffic provides further evidence that the company’s rightsizing strategy is beginning to bear fruit. Same-store traffic declines were narrower than the chain’s overall visit gap – just -1.5% YoY in July and -2.4% in August – suggesting that consolidation is helping shore up performance at remaining locations. At the same time, Advance is modernizing its supply chain to accelerate deliveries and strengthen its DIFM offerings – which, as with its peers, serves as a critical growth anchor for the chain. While it remains to be seen if these moves will drive sustained recovery amid shifting tariff pressures, Advance has restored profitability while implementing its strategic turnaround.
The auto parts sector remains robust, driven by an aging vehicle fleet and delayed new car purchases. And though tariff uncertainty remains, AutoZone, O’Reilly, and Advance are thus far navigating the new cost environment without major disruption. As 2025 unfolds, the second half of the year will show whether higher new-car prices push more consumers into aftermarket maintenance – and how customers, particularly in the DIY segment, respond if retailers need to pass through additional price increases.
For the most up-to-date retail visit data, check out Placer.ai's free tools.
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 has posed challenges for limited-service dining chains as inflation and higher prices continued to weigh on consumer traffic. We analyzed visitation trends in 2025 so far across major segments to better understand which categories are holding up – and which may need to adjust strategies.
This year brought significant challenges for the limited-service dining industry, as persistent price increases kept many would-be diners at home. Even industry giants like McDonald’s reported declines in same-store sales as lower- and middle-income consumers pulled back spending. Yet several categories, including the ever-impressive chicken segment, managed to buck the trend.
The chart below highlights the differences in YoY foot traffic for major limited service dining concepts in H1 2025. Pizza, burger, and sandwich chains experienced declines, while coffee, chicken, and Mexican-inspired concepts emerged as the growth drivers in terms of overall visit increases.
These segments were likely aided by aggressive unit expansion and consumer preferences shifting toward more affordable, customizable, and protein-forward options. Coffee continues to hold steady as a daily staple, while chicken and Mexican-inspired operators are capturing demand for protein-forward and customizable formats.
However, per-location data tempers this growth narrative. Visits per store declined across every major category – even those with overall visit increases – indicating that expansion may be outpacing underlying demand and pushing the segment toward potential oversaturation.
Recent summer data underscores the cautionary signals. Year-over-year traffic growth for coffee, chicken, and Mexican-inspired concepts was weaker in July than in the first half of the year. By August, declines had spread across nearly every category – with chicken chains in particular seeing a dip in traffic and an even steeper drop in average visits per location – leaving coffee as the only segment to sustain growth.
This broader slowdown in limited-service dining, combined with persistent economic uncertainty, suggests that consumers may be scaling back restaurant spending – even in categories traditionally viewed as more budget-friendly.
While 2025 has been marked by volatility, the underlying consumer appetite for convenient, protein-forward, and customizable dining is helping some limited-service segments stay ahead of the pack. Still, visit per location data suggests that expansion plans may need to be put on ice for the next few quarters.
Instead, operators that focus on menu innovation, building loyalty, and driving higher output per store stand to capture demand when economic pressures ease. As confidence rebounds, concepts that have expanded strategically may be especially well positioned to benefit from renewed consumer traffic.
For the most up-to-date dining data, check out Placer.ai’s free tools.
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.

After a strong spring for mall traffic, momentum slowed over the summer. As the chart below shows, visits in June declined year-over-year across all three formats, while July and August traffic leveled off.
Yet, even in this softer environment, indoor malls stood out as the only format to register growth – albeit modest – in both July and August. At the same time, outlet malls managed to close their YoY visit gap, likely buoyed by families looking to save on back-to-school shopping. This trend also points to the potential for a rebound in the format, as consumers’ growing focus on value continues to shape shopping behaviors in new ways.
A softer Labor Day capped off the slower summer, with slight dips in visits across all three mall formats compared to Labor Day weekend 2024 (though indoor malls continued to lead with the smallest YoY visit gap). Outlet malls saw the biggest drop, which combined with their flat August performance, suggests that shoppers frequented outlets earlier in the month rather than holding off for Labor Day promotions.
Taken together, these trends indicate that the summer slowdown was not simply the result of consumers holding back for holiday sales. Instead, with sentiment weakening, shoppers appear to be reducing discretionary purchases that typically drive mall traffic, or looking for better value on a routine basis rather than waiting for special sales.
The decline in average mall visit length offers another indicator of softening consumer sentiment and a cutting back on discretionary purchases. Visit length plummeted over the pandemic as consumers tried to limit their time spent in enclosed spaces, but the average visit duration to malls rose in 2023 and again in 2024 – suggesting that malls were slowly regaining their role as destinations for leisure, dining, and extended shopping trips.
The drop in August 2025, however, signals a reversal of that momentum, perhaps reflecting heightened consumer caution and a renewed focus on efficiency and essentials over browsing and discretionary spending.
Malls’ strong visitation trends just a few months ago caution against drawing overly dire conclusions, and the softer summer may represent a temporary reset rather than a lasting shift. Seasonal headwinds, travel, and consumer caution likely weighed on recent performance, while the steady resilience of indoor malls points to enduring shopper demand for in-person experiences. Outlet malls' success in closing their visit gap also adds reason for optimism.
The upcoming holiday season offers malls a chance to regain momentum and recapture consumer attention. While recent trends highlight caution and shorter visit durations, they also underscore consumers’ growing appetite for value and convenience – dynamics that indoor and outlet malls are uniquely positioned to meet. By pairing value-driven promotions with engaging experiences and festive activations, malls can reassert their role as destinations not just for shopping, but for leisure and community during the holidays. This combination positions shopping centers to benefit from seasonal demand, even as consumers remain more selective with discretionary spending.
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

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.
