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Final Four weekend capped off the NCAA “March Madness” basketball tournaments with a full schedule of fan experiences on both the men’s and women’s sides of the ball.
The Women’s Final Four took place between April 4th and 7th, 2024 in Cleveland, Ohio with on-court action at Rocket Mortgage FieldHouse. “Tourney Town” – an interactive basketball exhibition – ran concurrently at the Huntington Convention Center.
The Men’s Final Four commenced on April 5th at State Farm Stadium in Glendale, Arizona, culminating with the championship game on April 8th. The multi-day exhibition “Final Four Fan Fest” took place at the Phoenix Convention Center.
We dove into the location analytics and audience segmentation for visitors to several Final Four events to better understand the fans in attendance throughout the tournament weekend.
The men and women’s Final Four weekend attracted spectators from near and far, with each event attracting a unique mix of out of town tourists and locals.
Both men and women’s championship games attracted a relatively large share of out-of-town guests, likely due to the excitement surrounding a national title game. Analysis of visitors by home location revealed that the men and women’s championship games had the smallest share of visitors from less than 100 miles away – 29.8% and 33.3% respectively. In other words, these two events had the largest share of visitors that lived more than 100 miles from the venues.
The men’s open practice appeared to be more popular with long-distance travelers than the women’s, perhaps because all four men’s teams participated – as opposed to just two at the women’s open practice. The men’s practice was also followed by an all-star game which likely increased its appeal for visitors traveling from afar in the hopes of spotting their favorite players. The data revealed that more than half of the spectators traveled over 250 miles to watch the men’s practice, as opposed to under a quarter of spectators for the women’s practice.
Meanwhile, the women’s experiential exhibition at Huntington Convention Center drew more out-of-towners than the men’s exhibition at Phoenix Convention Center – only 23.3% of visitors to the women’s exhibition came from under 30 miles away, compared to almost half (48.3%) of the men’s exhibition visitors. The larger share of out-of-town visitors to the women’s exhibition may be because the event was close to the arena, making it a more convenient stop for non-local fans. On the other hand, the distance between the men’s exhibition in downtown Phoenix and the stadium in Glendale meant that the off-court experience was more out-of-the-way for tourists who had traveled specifically for the on-court action.

Analysis of Final Four visitors by income level provides further insight into the differences between each event’s fan base. According to the STI: Popstats dataset, the women’s events generally drew visitors from areas with a lower median household income (HHI) compared to the men’s events, although the gaps between the men and women’s visitor bases varied from event to event. Some of the difference in trade area HHI may be due to regional variance and the mix of locals and tourists at each event.
The visitor bases of the men and women’s championship games exhibited the widest disparity, with the men’s championship spectator base coming from areas with a median HHI of $99.9K, compared to $74.6K for the women’s championship’s trade area. The difference may be due to the relatively higher face value of tickets to the men’s championship game – even though the star-power of Iowa’s Caitlin Clark drove up the price of women’s tickets on the secondary market. In contrast, both the men’s and women’s practices and exhibitions were free or nearly free events and drove traffic from relatively lower-income areas – even though visitors to the men’s practice still came from more affluent areas than the trade area of the women’s championship match.
Visitors to the men and women’s convention center exhibition displayed the smallest income differences, with respective trade area median HHI of $80.0K and $76.6K. The data also reveals that visitors to the women’s exhibition came from a trade area with a median HHI that was higher than the median HHI for both the championship game and the open practice, perhaps because the exhibition drew a relatively large share of tourists who could afford to be in town for a slightly longer stay.

Further demographic analysis indicates that a greater share of singles – who tend to be on the younger side – attended the women’s Final Four events than the men’s. During the women’s championship, 41.0% of households in the trade area of the Rocket Mortgage FieldHouse were made up of one-person households. This segment also made up 34.2% and 36.3% of the households in the trade areas of the venues for the women’s practice and exhibition, respectively. On the men’s side, singles comprised just 29.3% of the championship’s trade area, 28.4% of the practice’s, and 27.0% of the exhibition’s.
This reflects the growing popularity of women’s college basketball players on social media which is bringing more viewership to the sport.

Want more data-driven visitor insights for sporting events? Visit Placer.ai.
This blog includes data from Placer.ai Data Version 2.0, which implements improvements to our extrapolation capabilities, adds short visit monitoring, and enhances visit detection.

During last week’s solar eclipse, people from all over the country converged on cities within the path of totality to witness the excitement first hand. And for municipalities and local businesses, the influx of tourists was expected to generate a boon.
But just how did the celestial event impact business activity on the ground? Which sectors benefited from the hype – and which geographic areas saw the biggest visit spikes?
We dove into the data to find out.
On April 8th, 2024, hotels in CBSAs where the eclipse could be viewed in all its glory (or close to it) experienced major visit boosts. And mapping hotel visits on the big day to CBSAs nationwide – compared to year-to-date daily averages – shows just how significant the cosmic alignment was for areas lucky enough to be located along or near the path of totality.

Within metropolitan CBSAs (CBSAs with at least 50,000 residents), Danville, IL – where visitors could either view a near-total eclipse or drive to a nearby location with 100% totality – experienced the biggest jump in Hotel visits, with visits to the category up 111.3%. But urban centers from north to south – including in New York, Indiana, Ohio, Arkansas, and Missouri – also experienced substantial hotel visit spikes.
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Hotels weren’t the only locations to reap the rewards of the solar eclipse. Fast Food & QSR chains in and around the path of totality enjoyed meaningful April 8th visit spikes of their own. And while the Hotel visit increases were more closely concentrated in prime viewing areas, Fast Food & QSR visits increased along a wider radius as people likely grabbed a bite to eat while making their way to a sun-gazing hotspot.

And the impact of the solar eclipse wasn’t limited to locations located in or near the path of totality. Retailers and dining chains nationwide got in on the action with special deals and limited-time offers meant to make the most of the unique interstellar opportunity.
In the week leading up to April 8th, 2024, Warby Parker drew crowds with the promise of free solar eclipse glasses. And while a burger joint may not be the first place people associate with eyewear, fast food favorite SONIC Drive In also attracted astronomy aficionados with a limited-time Blackout Slush Float that came with free eclipse viewing gear.
Krispy Kreme Doughnuts, for its part, marked the occasion with a limited-edition Total Solar Eclipse Doughnut. And though Mondays aren’t typically busy days for the chain, the special offering produced a clear visit uptick nationwide. In states along the path of totality, Krispy Kreme visits were up 55.5% on April 8th when compared to an average Monday this year, and in the rest of the country they were up 33.9%.
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For retailers across categories, landmark events from movie launches to cosmic occurrences have the potential to drive visit spikes and generate business. What other big opportunities lie in store for retailers this year?
Follow Placer.ai’s data-driven retail analyses to find out.
This blog includes data from Placer.ai Data Version 2.0, which implements improvements to our extrapolation capabilities, adds short visit monitoring, and enhances visit detection.

This year’s March Madness really lived up to its name, buoyed by the star power of Caitlin Clark, Angel Reese, Paige Bueckers, and Juju Watkins driving viewership to new heights. For the first time in history, the NCAA women’s basketball title drew more viewers than the men’s at 18.9M for the women’s and 14.8M for the men’s, per Nielsen.
Tickets to the Final Four cost $532 on average, an 82% increase over last year, and for the championship game, Rocket Mortgage Fieldhouse Stadium in Cleveland, OH was packed to the gills.
In the days leading up to the women’s final, nearby hotels saw visits increase as well.

Last week, we took a look at where the retail sector stood after Q1 2024, with a focus on superstores, home improvement, athletic footwear and apparel, and beauty. This week, to mark the release of short visit data with Placer’s Data Version 2.0 (which better captures visits that lasted 1 minute or longer for QSR/drive-thru locations) and the publishing of our latest dining whitepaper (The QSR Dining Advantage), we thought we’d take closer look at where the restaurant sector stands after Q1 2024.
When we looked at the restaurant category in January, most chains were reporting that visits were down on a year-over-year basis (which was partly a byproduct of inclement weather across much of the country) but that there was a sense of optimism about 2024. Looking at trends by category, we see that operators were justified in this optimism, as visit trends have increased on a year-over-year basis for most categories since late January. After adjusting for calendar shifts for both Valentine’s Day and Easter, we also see strong fine dining visits for these holidays, indicating that consumers remain motivated by holiday and events (a theme we called out several times last year).
We’ve also been fielding several questions about daypart shifts given that the Placer.ai Nationwide Office Building Index (an index of data from some 1,000 office buildings across the country) continued to show an uptick in visits during March 2024 and now stands at about 67.3% of March 2019 visits. Below, we show the percentage of visits by daypart for quick-service restaurant (QSR) and full-service restaurant chains. Given the lift in office visits, it’s not surprising that we continue to see improvement in early morning (6:00 AM-9:00 AM) visits, but it’s notable that we continue to see strength in late morning (9:00 AM-12:00 PM) and afternoon (3:00 PM-6:00 PM) visits. We’ve already seen many QSR chains test new menu items that better address consumer preferences in these dayparts–McDonald's CosMc’s is just one example--and we’d expect more in the months ahead. We also continue to see strength in late night QSR visits, something that we’ve called out in the past. On the full-service dining front, we see 2023 visits still down compared to 2019 levels, but with improvement versus 2021 in most cases. Here, it’s interesting that the afternoon visits to full-service dining chains in 2023 is down only slightly compared to 2019, while the gap during the evening daypart is much wider. This reinforces some of our previous analyses on earlier dining times
With our Data Version 2.0 update, we can now more accurately monitor dwell time by restaurant channel. After bottoming-out in Q2 2020 as most chains shifted to a largely takeout model, we’ve seen dwell time steadily increase across most restaurant channels the past several years. The QSR and fast casual categories remain below pre-pandemic levels, which isn’t a surprise given an increase in drive-thru and takeout orders compared to 2019 levels. Still, some of the operators we’ve spoken to have indicated that drive-thru bottlenecks have become more of an issue in recent quarters, which may reflect in the increase in dwell times for the QSR category the past 4-5 quarters. On the other side of the spectrum, dwell time for casual dining chains has fully recovered. We believe this has been helped by the continued popularity of eatertainment concepts, which have almost twice the average dwell time as most casual dining chains. We also see that fine dining dwell time now exceeds pre-pandemic levels, which may be the result of consumers’ aforementioned focus on holiday/event dining, which tends to drive dwell times higher.
Restaurant chains still face obstacles–the spread between food at home (grocery prices) and food away from home (restaurant prices) remains high and the $20 minimum wage for QSR workers recently went into effect in California (our data does not indicate major visit changes going into effect as it may be too recent for behavioral changes to be noticeable). However, March and early April visitation trends help the optimism that many restaurant operators felt at the beginning of the year. With Panera (and other chains) evaluating a possible IPO and many other brands finally accelerating growth plans (with an increased emphasis on higher-growth markets in the Southern/Southeastern U.S.), we’d expect visitation trends to remain positive on a year-over-year basis in the months to come.

Say the word New Mexico and one might picture the stunning cliff dwellings at Bandelier Monument, rich troves of Native American Pueblo culture, or the stunning artworks of Georgia O’Keefe. This vibrant state’s largest city is Albuquerque, but Santa Fe also lays claim to fame by being the oldest state capital in the United States.
In Albuquerque, a large development is taking place centered around the Indian Pueblo Cultural Center. While one may be a bit surprised at its location, which is within an outdoor shopping center, it serves as a perfect anchoring point for a convention or a leisure trip. The museum features insights into 19 Pueblo cultures, and also hosts an authentic Indian kitchen where one can try indigenous favorites such as red chile beef stew, calabacitas, and assorted fruit pies. There is a Holiday Inn Express & Suites and a Towneplace Suites by Marriott just across the street for those who need accommodations. Meetings, parties, and events can be held onsite with particularly memorable experiences to be had in the outdoor arena and fire pit. One can even hold a wedding at the venue. And in a sign of the convenience store trend we are seeing towards localization, Four Winds offers a walk-in humidor with cigar selection, the ability to fill a growler with local craft beers, and an assortment of food, beer, wine, liquor, and tobacco.
Further afield, an hour away in Santa Fe, visitors flock to the galleries galore, restaurants and bars like Coyote Cantina, or simply enjoy an ice cream while people watching at Santa Fe Plaza. One of the highlights for opera lovers around the world is coming to Santa Fe Opera House during its season, which runs from the end of June to the end of August. Here, one can enjoy the unique open-air aspect of the opera house while sobbing along to the sad fate of Violetta in La Traviata.
Junior Rangers might enjoy exploring Carlsbad Caverns, Aztec Ruins National Monument, or venture to Petroglyph National Monument. Adults seeking R&R can ski the day away in Taos or opt for a therapeutic visit to Ojo Caliente Mineral Springs Resort & Spa. A review of the resort describes it as “Just you, the blue New Mexico sky, peace and quiet.” Add to that a massage or spa treatment, and it sounds like just what the doctor ordered.

One of the major employers in New Mexico is Los Alamos National Laboratory. A visit to the National Historic Park there will take you on an intriguing journey of key sites that were relevant to the Manhattan Project. Between last summer’s Oppenheimer blockbuster and current global sensation The Three-Body Problem fanning interest in cutting-edge science, this is a must-see location.

Albertsons Companies is one of the largest grocers in the country, with around 20 grocery banners in its portfolio boasting around 2,200 stores in 34 states. Aside from its eponymous brand, Albertsons, the company owns major chains like Safeway and Vons, as well as smaller regional banners.
With Q1 2024 under wraps, we take a closer look at visit trends to some of Albertsons Companies’ main banners, examine the top-performing chains by state, and dive into the demographics in the company’s two largest markets.
Diving into 2023’s visits shows that the company’s eight major banners – Albertsons, Safeway, Vons, Jewel-Osco, ACME Markets, Shaw's Supermarket, United Supermarkets, and Tom Thumb – enjoyed year-over-year (YoY) visit growth during every quarters of the year. Visits to Jewel-Osco, and Shaw’s Supermarket were particularly elevated, with Q4 2023 visits YoY up 5.8%, and 5.9%, respectively.
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Albertsons Companies’ positive performance has continued in 2024. Visits to most of the chains remained positive YoY in January despite the chilling retail impact of early 2024’s arctic blast, and all banners saw significant growth in February and March.
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Albertsons Companies is headquartered in Boise, Idaho, and its eponymous banner is highly popular in the western United States. But the company has also gained a foothold in the South, Midwest, Mid-Atlantic, and Northeast – and solidified its dominance in the West – through several successful mergers.
The company’s strategy of acquiring regional channels means that most states now have an Albertsons Companies’ banner catering to local grocery shoppers. Nationwide, the company’s most visited chains are Albertsons and Safeway – likely due to the sheer number of locations – but regional chains like Tom Thumb in Texas and Jewel-Osco in the Midwest are still the reigning Albertsons Companies banners in their areas.

California and Texas, the country's two most populous states, also boast the highest number of Albertsons Companies-owned grocery chains. Analyzing the demographic differences between the trade areas of the top three Albertsons Companies banners in each of the two states shows how the company leverages its banner variety to reach a larger audience.
According to the STI:Popstats 2023 dataset, the median household income (HHI) in Texas is $75.9K. Two of the top three Albertsons Companies’ banners in the state had a trade area median HHI below the Texas statewide median – United Supermarkets at $58.7K/year, and Albertsons at $68.3K/year – while Tom Thumb drew visitors from neighborhoods with a median HHI of $99.5K. And in California, although all three most visited Albertsons Companies banners drew visitors from neighborhoods with a median income above the statewide median, the trade area HHI also exhibited a range – from $99.2K/year for Albertsons to $115.0K/year for Safeway.
The variance in median HHI by banner and state highlights the benefit of operating grocery banners that can attract a range of shoppers from all along the income scale. By offering shopping options that cater to shoppers of all kinds, Albertsons Companies can hope to maximize its market reach and attract a diverse array of consumers.
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Albertsons Companies has set up shop across the country and offers a wide range of shoppers multiple grocery experiences across regions and price points. Will its grocery banners continue to see elevated foot traffic into 2024?
Visit placer.ai to stay on top of the latest grocery developments.
This blog includes data from Placer.ai Data Version 2.0, which implements improvements to our extrapolation capabilities, adds short visit monitoring, and enhances visit detection.

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.
