


.png)
.png)

.png)
.png)


Darden Restaurants, Inc. is a major player in the restaurant industry, operating restaurants across a wide range of dining styles and price points. Recently, Darden announced plans to acquire Tex-Mex chain Chuy’s, a move that would add some 100 new locations across 16 states to the Darden portfolio.
We took a closer look at how the dining brand has performed over the past few months, and dug deeper into what impact the Chuy’s acquisition might have on Darden.
Darden's 2024 performance has been strong, with only three months – January, April, and July – showing YoY visit declines. January’s 2.9% decline was likely driven by unseasonably cold weather, while Easter weekend shifted visits across multiple retail categories in April 2024. And though July visits experienced a modest dip of 0.5% YoY, the drop was quickly offset by a 5.1% YoY increase in August.
This trend points to a recovery in consumer dining behavior, particularly in the full-service restaurant sector, where growth is being driven by consumers opting for higher-quality dining experiences over fast food options.
Darden owns and operates nearly 2,000 restaurants nationwide. Its three core brands – Olive Garden, LongHorn Steakhouse, and Cheddar’s Scratch Kitchen make up the bulk of these locations.
All three restaurant chains enjoyed overall positive momentum over the past few months, with LongHorn emerging as a standout performer. The chain saw its foot traffic increase in all months analyzed, with August 2024 visits elevated by 10.4% YoY.
Cheddar’s Scratch Kitchen and Olive Garden, too, experienced growth in all but two of the analyzed months, with August 2024 visits elevated by 3.1% and 6.9%, respectively, YoY. These trends point to consistent – and perhaps growing – consumer demand, a solid position as the holiday season approaches.
In July 2024, Darden announced its intention to acquire Chuy’s, an Austin-based Tex-Mex chain, a move that could add 101 stores to Darden’s already extensive portfolio. And while the acquisition is still pending, digging into the demographic and psychographic data offers some insight into what might make Chuy’s at home with the Darden family.
One defining factor of Darden’s restaurant portfolio might be its range – the chain offers dining options that appeal to people across a variety of income brackets. Its core brands – Cheddar’s Scratch Kitchen, Longhorn Steakhouse, and Olive Garden – cater to a customer base with household incomes similar to the nationwide median of $76.1K. But Darden’s broader portfolio includes several chains that appeal to wealthier patrons – visitors to Eddie V’s Prime Seafood, for example, came from trade areas where the median household income (HHI) was $105K.
Chuy’s visitor base, meanwhile, hails from trade areas with a median HHI of $86.2K. So the addition might help the restaurant group build on its core audience while appealing to higher-income diners who may be looking to “trade down” to a more casual, affordable meal without compromising on quality. This alignment allows Chuy’s to seamlessly fit within Darden's strategy, providing a diverse range of dining experiences while expanding its reach into higher-income markets.
Darden’s acquisition of Chuy’s also appears to be a strategic play to attract younger diners, a segment that continues to drive interest in Mexican and Teex-Mex cuisine. And examining the demographics of visitors across all Darden brands reveals that Chuy’s is particularly popular among “Young Professionals”, with 9.4% of its diners coming from trade areas classified as such by the Spatial.ai: PersonaLive dataset.
As young diners continue to be a category of interest for Darden, the Chuy’s acquisition may be the ticket to Darden maintaining its visit dominance in the coming years.
Darden continues to drive foot traffic across its wide portfolio of brands, offering something for every kind of diner. With plans to expand its core audience underway, will the restaurant group continue to improve its monthly visits?
Visit Placer.ai to keep up with the latest data-driven dining news.
This blog includes data from Placer.ai Data Version 2.1, which introduces a new dynamic model that stabilizes daily fluctuations in the panel, improving accuracy and alignment with external ground truth sources.

How did the Placer 100 Index for Retail & Dining fare in August 2024? We dove into the data to find out.
The final days of summer were a critical retail moment, with all eyes on back-to-school traffic performance. Analyzing year-over-year (YoY) foot traffic performance for the Placer 100 Index for Retail and Dining shows that since May 2024, visits have been on a positive growth trajectory – reaching a summer highpoint of 3.0% in August.
Back to school, it seems, was a significant driver of retail and dining foot traffic. And recent indications that consumer confidence has turned a corner may bode well for the fast-approaching holiday season.
How much of an impact did back-to-school activity have on retail and dining visits in August 2024? Further analysis of the Placer 100 Index reveals that the top-performing metro areas last month were college towns, which suggests that a surge in students out and about – shopping for back-to-school essentials and dining out – was a likely driver of local foot traffic.
The State College, PA Metro Area, home to Penn State University, for example, saw a 14.5% YoY change in overall retail and dining visits in August 2024. And other college towns with large student populations were also top YoY visit performers during the month. Blacksburg-Christiansburg, VA (14.2%), home to Virginia Tech, Ithaca, NY (12.1%), home to Cornell University, and Bloomington, IN (12.1%), home to Indiana University Bloomington – to name a few – all experienced significant visit growth compared to August 2023.
While the Placer 100 Index experienced foot traffic gains last month, digging deeper into the data reveals that in August 2024 consumers continued to prioritize value as they dined and shopped.
In addition to rapidly growing discount grocer Aldi, four value-focused chains were among August 2024’s top YoY visit performers. Five Below (17.5%), Big Lots (15.7%), HomeGoods (13.8%), and Ollie’s Bargain Outlet (13.7%) all showed impressive YoY traffic – and three out of the four were also among the top chains in terms of YoY visit-per-location growth.
One of the biggest YoY visits and visits-per-location winners in August 2024 was Big Lots, which recently announced voluntary Chapter 11 proceedings and an ownership transition while continuing to rightsize. With soon-to-be-closed locations offering steep markdowns, the chain has been driving significant traffic. And since Big Lots offers small-ticket items as well as big-ticket home furnishings, a back-to-school push likely contributed to the chain’s jump in August visits.
HomeGoods was also among the top chains in August 2024, with both YoY visits and visits-per-location (9.8%) growth. The chain’s social media campaign featuring college students furnishing their living spaces appears to have buoyed foot traffic during the homestretch of back-to-school shopping.
With summer in the rearview mirror, the focus shifts to fall and the fast-approaching holiday season. Will retail and dining visits sustain their momentum in the critical months ahead?
Visit Placer.ai to find out.
This blog includes data from Placer.ai Data Version 2.1, which introduces a new dynamic model that stabilizes daily fluctuations in the panel, improving accuracy and alignment with external ground truth sources.

The return to office (RTO) has been on an upswing, with employers across industries cracking down on remote work and requiring employees to put in more face time. Indeed, July 2024 emerged as the busiest in-office month since the pandemic. But what happened in August?
We dove into the data to find out.
August is a time for family vacations – and millions of Americans planned to take the roads and skies this summer to get away from it all and enjoy some downtime. So it may come as no surprise that the accelerated mandate-driven RTO seen in recent months – moderated somewhat in August, with a larger visit gap compared to the equivalent period of 2019 than that seen in July or in June.
Still, despite an end-of-summer slump, the nationwide office recovery appears to be very much underway. Office foot traffic last month was just 31.2% below pre-pandemic levels. Or put another way, August 2024 office visits were 68.8% of what they were in August 2019.
Drilling down into the data for major urban hubs throughout the country shows a continuation of recent trends, with Miami, New York, Atlanta, and Dallas outperforming the nationwide baseline. In Miami and New York, office visits were nearly 90.0% and 85.0%, respectively, of what they were pre-pandemic. And Atlanta, where employers from the CDC to UPS have begun enforcing stricter in-office policies, held onto its high ranking, with visits 75.6% of what they were in August 2019.
Indeed, Atlanta, which has seen a surge in office leasing activity, saw 7.3% year-over-year (YoY) visit growth in August 2024 – followed by Miami (5.7%). San Francisco – which despite lagging behind other cities compared to pre-pandemic, has been making steady YoY gains – came in third with a YoY visit increase of 3.0%.
Who are the employees driving this summer’s accelerated recovery?
Analyzing the trade areas of office buildings nationwide reveals that between June and August 2024, the Census Block Groups (CBGs) feeding visits to office buildings (their captured markets) continued to see a decline in their share of households with children – indicating that parents still account for fewer office visits than they did pre-pandemic. Employees with children, it seems, remain especially likely to place a premium on flexibility – embracing work routines that allow them to more efficiently juggle home and work responsibilities.
Over the same period, the share of one-person households in offices’ captured markets rose substantially, highlighting the important role played by young professionals – who may be more likely to be single – in today’s office recovery. Whether driven by a desire to embrace in-office career growth and mentorship opportunities, or by a craving for more social interaction, these employees are returning to the office in ever greater numbers.
With the school year underway and summer vacations already a not-so-distant memory, office foot traffic is likely to resume its upward trajectory. Will September 2024 set a new post-pandemic RTO record?
Follow Placer.ai’s data driven analyses to find out.
This blog includes data from Placer.ai Data Version 2.1, which introduces a new dynamic model that stabilizes daily fluctuations in the panel, improving accuracy and alignment with external ground truth sources.

Malls ended summer with a bang. In May and June 2024, indoor malls, open-air shopping centers and outlet malls all experienced year-over-year (YoY) visit growth, with indoor malls – which offer an escape from the sweltering heat – leading the way.
In July 2024, all three mall types experienced slight YoY visit gaps. But these were likely due to a calendar shift rather than to any flagging back-to-school momentum: July 2024 contained one less Saturday and Sunday than the equivalent period of 2023, when malls draw some of their biggest crowds. (In January-August 2024, weekends accounted for 39.0% of visits to indoor malls, 35.6% for open-air shopping centers, and 43.0% for outlet malls.) This shift, which likely had the most pronounced impact on outlet malls, may have obscured stronger YoY performance in July 2024.
And this year’s intense weather didn’t stop consumers from visiting malls in droves to take advantage of back-to-school shopping – which was in full swing by August 2024. That month saw the most substantial YoY foot traffic growth of the analyzed period, with YoY visit increases of 7.3% for indoor malls, 5.8% for open-air shopping centers, and 6.1% for outlet malls.
Who shopped at malls in August 2024? With back-to-school shopping being a significant motivator for consumers, it may come as no surprise that college students and families with children were overrepresented among end-of-summer mall hoppers – though not for all mall types.
Analysis of all three mall segments’ captured markets reveals that in August 2024, the share of college students in the trade areas of indoor malls and open-air shopping centers exceeded the nationwide average by 67% and 170%, respectively. These malls may be popular with college students due to their greater accessibility for students without cars, and for their recreational atmosphere – making them a good place to catch up with friends while shopping.
Meanwhile, the captured markets of outlet malls included slightly higher-than-average shares of households with children, perhaps as families on tight back-to-school budgets prioritized steep discounts. Indoor malls were also slightly more likely than average to draw this demographic.
With Summer 2024 in the books, it’s fair to say that mall foot traffic thrived during this critical retail season. How will mall visits shape up come spring?
Visit Placer.ai to find out.
This blog includes data from Placer.ai Data Version 2.1, which introduces a new dynamic model that stabilizes daily fluctuations in the panel, improving accuracy and alignment with external ground truth sources.

In 2024, auto parts retailers are continuing to see visit growth compared to last year. We dove into the data for three of the industry’s leaders – AutoZone, O’Reilly Auto Parts, and NAPA Auto Parts – to explore the consumer behavior and profiles behind the space’s ongoing success.
Auto parts retail visits have been bolstered in recent months by still-high vehicle prices – which have incentivized many cash-strapped consumers to fix up the car they have rather than buy a new one. To be sure, the industry hasn’t been entirely spared the effects of inflation, which has caused many consumers to tighten their (seat)belts and defer non-essential car repairs. Still, one of the key factors benefiting the space has been the greater prevalence of older vehicles on the road, which are more likely to need significant – and essential – maintenance.
Since the start of 2024, AutoZone and O’Reilly have sustained consistent year-over-year (YoY) monthly visit growth. And though NAPA saw mild visit gaps in March, June, and August – coinciding with traffic fall-off to some of the repair shops it supplies – it too experienced YoY increases throughout most of the analyzed period.
As auto parts inflation continues to wane in 2024, more consumers may begin taking on repairs they postponed last year, providing these retailers with continued foot traffic boosts.
Less affluent consumers are more likely to be deterred from buying a new ride by high prices and interest rates. And analyzing the demographic characteristics of visitors to AutoZone, O’Reilly, and NAPA reveals that in H1 2024, the median household incomes (HHIs) of the chains’ captured markets were indeed significantly lower than those of new car dealerships ($75.6K).
The data reveals a divide between consumers in the market for new cars – who generally have higher income levels – and those that frequent auto parts retailers to invest in their current set of wheels. And consumers seeking to repair rather than replace may be even more inclined to do so while vehicle prices and financing costs remain elevated.
Analysis of consumer spending habits provides a further indication that AutoZone, O’Reilly and NAPA’s audiences are more likely to invest in upgrades and repairs than in the purchase of a new vehicle.
In H1 2024, residents of AutoZone and O’Reilly’s captured markets spent 17% less annually on buying used cars than the nationwide average, while residents of NAPA’s captured market spent 14% less.
And residents of all three auto parts retailers’ trade areas spent even less on new car buying. In H1 2024, AutoZone’s captured market spent 23% less on new cars than the nationwide average, and O’Reilly’s and NAPA’s captured markets spent 22% and 18% less, respectively.
AutoZone and O’Reilly’s relatively large share of DIY consumers – those who repair or upgrade their cars on their own to save money – likely contributed to their trade areas’ smaller car buying expenditures. Meanwhile, the slightly larger spend on both new and used cars in NAPA’s trade area – though still significantly lower than the nationwide average – may be due to the retailer’s predominantly commercial business.
Auto parts chains have been riding strong tailwinds on the road to success – and they appear geared up for more foot traffic success in the homestretch of 2024. As more older vehicles stay on the road and car-buying costs remain high, robust demand for parts is likely to continue.
Will the auto parts industry accelerate even further in the months to come? Visit Placer.ai to find out.
This blog includes data from Placer.ai Data Version 2.1, which introduces a new dynamic model that stabilizes daily fluctuations in the panel, improving accuracy and alignment with external ground truth sources.

It’s that time of year again. On August 22nd, Starbucks launched its much-vaunted autumn menu, including the iconic Pumpkin Spice Latte (PSL). We dove into the data to see what happened on the big day – and how Starbucks visitation patterns were impacted by the much-anticipated release.
Last year, Starbucks broke with tradition to move its PSL launch from Tuesday to Thursday. And perhaps due to Thursday’s proximity to the weekend (especially in the age of the TGIF work week), the step has proven advantageous – generating a sustained visit spike lasting through the weekend.
On Thursday, August 22nd, 2024, foot traffic to Starbucks surged 24.1% higher than the coffee giant’s daily average for the previous eight Thursdays. And the PSL effect worked its magic throughout the weekend, with visits to Starbucks on the following Friday, Saturday, and Sunday significantly elevated compared to recent daily averages for those days of the week.
Since its debut in 2003, Starbucks’ PSL has become part of the cultural landscape. Each year, the beverage’s release generates a social media frenzy. And between 2021 and 2023, the number of people visiting Starbucks on Pumpkin Spice Latte launch day increased steadily.
Last year, the PSL visit spike reached new heights, with foot traffic 27.1% higher than on August 27th, 2019 – the last pre-pandemic PSL launch. And despite Starbucks’ recent challenges, visits on PSL day held steady this year, maintaining last year’s impressive gains.
Comparing visits on August 22nd, 2024 to recent Thursday visit averages across the continental U.S. highlights the broad appeal enjoyed by Starbucks’ fall menu. Every analyzed state enjoyed a visit bump – though the extent of the boost varied considerably between regions.
Many southern states – including Alabama, Louisiana, and Mississippi, saw only slight foot traffic bumps, perhaps due in part to the region’s warmer weather, which may render the early autumn launch less compelling. (Mississippi in particular, it seems, really couldn’t care less about Pumpkin Spice.) But in other areas, led by North Dakota (45.5%), Kansas (42.6%), Utah (42.2%), Iowa (41.3%), and Pennsylvania (39.5%), visits skyrocketed.
Starbucks’ successful PSL launch shows that even as consumers count their pennies, people are finding room in their budgets for sweet, cozy indulgences that don’t break the bank. What does the winning release portend for the upcoming winter season?
Follow Placer.ai’s data-driven dining and retail analyses to find out.
This blog includes data from Placer.ai Data Version 2.1, which introduces a new dynamic model that stabilizes daily fluctuations in the panel, improving accuracy and alignment with external ground truth sources.

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.
