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Q1 2026 is in the books and there were some key elements that popped when we looked at the data.
While we’re all about location data, few things get us as excited as the glorious combination of behavioral location analytics with sentiment data. So, we ran a poll of retail industry professionals with our friends at ShopTalk, and the results were fascinating. But two answers really stood out.
First, only 30% of respondents felt that ‘inspiration’ was a key element of the store experience. This was shockingly low considering how powerful the ‘discover mode’ aspect of the shopper journey can be. It also speaks to the massive potential in better maximizing this component to drive product engagement, sales and retail media opportunities.
Second, while 44% of respondents expected Agentic AI to boost digital commerce and 22% expected to simply fragment digital’s current share, 34% felt it would be a tide that lifted all boats. This is hugely positive in that it indicates a growing recognition that the benefit of digitally native innovations is not limited to the digital environment.
In January, all mall formats in the Placer.ai Mall Index saw a boost. A nice start for malls, but maybe just a fluke?
The February data came in and showed that all mall formats once again saw a boost. This gives more evidence to the going hypothesis that top tier malls are in the midst of a significant and ongoing renaissance. While this clearly has huge ramifications for site selection and placemaking at these centers, it also speaks to an ongoing potential for a significant swath of lower tier malls to drive their own revolutions with a greater focus on driving complementary offerings and local audiences.
I’m hardly unbiased when it comes to Target, but since the week beginning January 26th through the week beginning March 23rd – the retailer has seen nothing but visit growth, with visits averaging a 7.8% year over year lift during that period.
Does this mean that every problem is solved? No. But it does show that while there were clearly challenges faced in recent years, there is a unique potential for Target because of their market positioning and brand. We called them out as one of the clear candidates for a major recovery in 2026 and they are showing early signs that validate that call.
In September of 2024 Costco raised the cost of membership. Did this deter potential members and limit visits? Nope.
Instead, Costco has seen continued growth and an expansion of its audience with new groups becoming a bigger part of its overall mix. The result is the latest sign that Costco’s growth could actually have many more levels to hit with just the expansion of its audience.
In a guest post for The Anchor dunnhumby’s Erich Kahner broke down the grocery segment and powerful positioning that two groups had. Savings-First grocers like Aldi or Lidl were well positioned to grab visits with a clear value offering that emphasized price, an especially powerful tool in a period of seemingly endless economic volatility. On the other hand, Quality-First grocers like Sprouts were leading with an emphasis, not on price, but on exceptional product quality. And while these two concepts may seem like obvious draws for consumers, the ability to so effectively center an offering around a core promise gives these brands a unique market position and the ability to effectively deliver on and prioritize this position.
But there is a third group – the unicorns. In this case, Kahner focused on brands like Trader Joe’s and H-E-B and their ability to leverage authenticity, ideal product mix and a powerful understanding of their audience to deliver an exceptional and targeted experience. And this is critical because it represents the latest example that the antidote to bifurcation – the push to exceptional quality and exceptional value across categories – is authenticity. The ability to create an experience and product offering that stands out and truly resonates for a core audience.
Yes, there are continued improvements in office visitation led largely by more dramatic year over year lifts in areas that took longer to recover like San Francisco. However, there is an overall sense that the current state of affairs in office is generally stable. And this is great for office real estate.
Hybrid work has absolutely changed behavior, but it didn’t stop professionals from coming to the office – or many businesses from demanding this return. But there are clear indications of what drives more office visits. Proximity, industry, and family status all present clear signals of how often an audience will visit the office during a specific period. The positive here is that it shows a clear rationale for why people don’t visit, and it is not because they don’t value the office.
The takeaway? Expect an office-centric version of hybrid work to continue setting the overall pace.
For more data-driven retail & CRE insights, visit placer.ai/anchor
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.
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Club Pilates’ journey since its acquisition by Xponential Fitness represents a rare and large-scale success in the boutique fitness space. Since 2019, the chain has increased its monthly visits by over 200%, largely by expanding aggressively and saturating existing markets.
But same-store data suggests that the brand, having built a dense and expansive studio footprint, may be hitting its first ceiling, and expansion alone may not be enough to sustain the momentum of the past couple of years. Instead, the chain will likely need to combine new location openings with unlocking the latent value within its existing network of 1,400+ studios – growing membership, driving more engagement, improving utilization, and deepening customer relationships.
To that end, Xponential is pursuing a multi-pronged strategy aimed at boosting unit-level economics, including improving member acquisition and investing in digital upgrades to enhance conversion and retention. The company is also testing pricing and packaging strategies alongside studio refreshes and new class formats to increase engagement and utilization with the goal of improving profitability across the existing studio base.
But even as Xponential Fitness works to improve performance at existing locations, expansion – which has been Club Pilates’ primary growth engine to date – will remain an important part of the strategy, with the company aiming to open locations in both "new and existing geographies."
AI-powered location analytics reveal that most Club Pilates visits come from local clients, a trend which has remained remarkably consistent throughout the chain's aggressive expansion. In 2025, around 70% of visits came from patrons travelling less than five miles to reach the studio and more than 85% originated within a 10-mile radius – underscoring the highly local nature of the business.
Because most customers come from nearby, opening additional studios allows the brand to reach new local audiences rather than relying on a single location to cover an entire market. When spaced appropriately, this can grow total demand with limited overlap, while marketing across the market helps reduce the cost of acquiring each new member. As a result, even if same-store visits begin to level off, the brand can continue to grow by expanding its footprint – capturing new pockets of local demand that existing studios do not fully serve.
As Club Pilates enters its next phase, growth will depend both on opening new studios and on optimizing its existing network – improving utilization, deepening engagement, and refining pricing. With strong local density and a loyal, routine-driven customer base, the brand is well positioned to increase member lifetime value through digital enhancements and more personalized experiences. If executed well, this shift from pure expansion to expansion and optimization could elevate Club Pilates from a fast-growing chain to a true fitness super-brand.
For more data-driven consumer insights, visit placer.ai/anchor
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.
Traffic to malls increased in Q1 2026 across all three formats analyzed – indoor malls, open-air shopping centers, and outlet malls – largely thanks to strong performances in the first two months of the year.
But March 2026 visits were more subdued, with indoor malls seeing a slight year-over-year (YoY) decline of 1.1% and outlet malls experiencing a steeper drop of 4.1% compared to March 2025. Open-air shopping centers were the only format to maintain growth, though their 3.2% YoY visit increase – though solid – was still more modest than the stronger gains seen by the format in January and February.
So what happened in March? Why did open-air shopping centers fare better than their peers? And how can malls return to growth across formats going into Q2?
Some of the dip may be due to calendar differences – March 2026 had one less Saturday than March 2025 – and since Saturdays are typically malls' busiest day, the shift likely impacted overall visits for the month.
But a closer look at daypart trends can shed additional light on both the strength earlier in the quarter and the slowdown in March. In Q1 overall, growth was concentrated at the edges of the day: traffic before 11 AM and after 8 PM saw the strongest gains, with additional support from the early evening (5 PM–8 PM). In contrast, midday traffic – the largest share of visits – was relatively flat for open-air centers and slightly negative for indoor and outlet malls. Still, robust edge growth was sufficient to offset this softness and drive overall quarterly gains.
But in March, growth in morning and evening hours slowed – particularly for indoor and outlet malls – while midday declines became more pronounced. This meant that the off-peak gains were no longer sufficient to offset weakness in the core of the day – leading to the YoY traffic declines for indoor and outlet malls.
But even as traffic to indoor and outlet malls declined, open-air shopping centers maintained growth momentum due to two key advantages. First, the format maintained most of its morning and evening gains, and its midday traffic trends ease from growth to stability rather than from stability to decline like for indoor and outlet malls – so the growth at the edges was still enough to offset the flat visits midday. Second, open-air centers are less dependent on midday visits, with around 77% of visits to open-air shopping centers occurring between 11 AM and 8 PM, compared to 83% to 84% for indoor and outlet malls. This means that open-air shopping centers are more resilient to dips in midday visits than the other two formats.
The softness seen in March at indoor and outlet malls does not negate the strong start to 2026, which drove overall YoY visit growth in Q1. However, it does highlight what will be required to sustain that momentum going forward.
The data points to two paths to more durable growth: reigniting demand during peak midday hours through programming, tenant mix, and convenience-driven visits or reducing reliance on that window by expanding traffic in the morning and evening. Open-air shopping centers provide a model for the latter, with a more balanced daypart mix – likely driven by their dining, entertainment, and extended-hour experiences – that has helped cushion midday softness. For indoor and outlet malls, long-term stability will likely depend on a combination of both – strengthening midday performance while also building consistent off-peak demand.
For more data-driven retail insights, visit placer.ai/anchor.
Lands’ End is entering a new chapter. The recently announced joint venture with WHP Global signals a strategic shift for the heritage apparel brand – one that could expand its reach through licensing, brand partnerships, and new distribution channels.
Under the agreement, WHP assumes control of Lands’ End’s licensing business, while the brand retains its retail operations. And while Lands’ End has long been associated with its catalog and e-commerce dominance, AI-powered location analytics suggest that its physical store fleet maintains an important role.
As an apparel brand with a history of catalogue retail, Lands’ End continues to generate the majority of its sales online. Yet its physical stores remain a critical component of the business – and an increasingly bright spot.
Lands’ End outpaced the broader apparel category in year-over-year visit growth in three of the past four quarters, with the only decline in Q1 2026 likely tied to store closures as part of ongoing optimization. At the same time, visits per location have remained consistently positive and above category benchmarks, highlighting the strength of the remaining fleet. This suggests that brick-and-mortar continues to be an effective driver of growth as the brand moves into its next phase.
Further evidence of the fleet’s strength – and its long-term potential – can be seen in the audience it attracts.
AI-powered audience segmentation indicates that in 2025, the brand captured an outsized share of visits from Ultra Wealthy Families, as well as from singles – the combined one-person and non-family households – segments, relative to the traditional apparel category.
The significant share of affluent families points to a customer base with both spending power and relative insulation from macroeconomic pressure. Meanwhile, strength among singles – a cohort that skews younger and includes a meaningful share of Gen Z consumers – highlights traction with a target demographic critical to long-term relevance.
The prevalence of both these audiences in Land's End's trade area suggests a dual advantage. Strong engagement from affluent households may help support near-term stability, while resonance with younger shoppers could indicate a developing pipeline for sustained growth in the years ahead.
The performance of Lands’ End’s store fleet, coupled with the composition of its audience, suggests a brand with momentum in physical retail – a notable advantage as it retains control of that side of the business. A productive fleet and a resilient, evolving customer base provide stability today, and could offer a strong foundation for broader brand expansion in the years ahead.
How will Lands’ End leverage this momentum as it enters its next phase? Visit Placer.ai/anchor to find out.
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.
Lane Bryant faced significant challenges during the pandemic and has continued to gradually shrink its store fleet in the years since. And now, with nearly one in eight U.S. consumers using GLP-1 medications, plus-size apparel demand is beginning to shift in meaningful ways – introducing a new layer of complexity for the legacy retailer.
How is Lane Bryant navigating these challenges, and what does its customer base reveal about its ability to adapt?
In July 2020, Lane Bryant’s parent company filed for bankruptcy and closed more than 150 stores. But following its acquisition later that year by Sycamore Partners, the brand began to regain its footing – and recent location analytics suggest those stabilization efforts are taking hold.
While the reduced footprint has, unsurprisingly, led to lower overall traffic, average annual visits per location remain above 2019 levels, suggesting that demand has been successfully consolidated into existing locations. Average visits per location also held steady between 2024 and 2025, even as the company continued to quietly trim its unit count. The result is a smaller but more productive fleet, with steady activity supported by fewer, better-aligned stores.
Still, as Lane Bryant continues to stabilize, the question becomes how it can further increase store-level productivity. And analyzing the demographic profile of its trade areas offers insight into both its core strengths and where the next phase of optimization may emerge.
One of the brand’s clearest advantages is Lane Bryant’s strong reach among family-oriented segments, which are overrepresented in its captured market – the areas within its trade area generating the highest share of visits – compared both to its overall trade area (its potential market) and to the national baseline. These segments, including parents of young children and households with teenagers at home, tend to skew younger than peak GLP-1 users, potentially offering the chain some near-term insulation from rapid GLP-1-driven disruption. Still, these cohorts are also seeing growing adoption – and as usage expands within this demographic, Lane Bryant will need to increasingly support customers through evolving size needs rather than rely on demand tied to a stable size identity.
At the same time, the data points to opportunities to expand reach across other segments. Among older households, Lane Bryant’s captured audience aligns with its trade area but falls below the nationwide average, highlighting potential whitespace that could be unlocked through footprint adjustments or more targeted engagement in markets where this segment is more concentrated.
Among younger “Contemporary Households,” by contrast – a segment that includes singles, non-family households, and married couples without children – the brand under-indexes relative to its trade area while slightly outperforming the national benchmark. This suggests Lane Bryant has geographic access to a larger pool of these consumers but has yet to fully capture their demand, pointing to an opportunity for growth through more targeted marketing and merchandising.
GLP-1 adoption is disrupting traditional plus-size apparel demand, while also creating new opportunities as consumers undergoing weight loss journeys increase spend while moving through sizes. Retailers that can support customers across these transitions with more flexible assortments will be better positioned to capture this shift. And Lane Bryant’s steady operational footing and well-defined core audience provide it with a solid foundation to compete in this next phase of growth.
For more data-driven retail insights, visit placer.ai/anchor.
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.
Oh baby! The competition for ownership of the baby retail space has once again intensified. Target recently announced the debut of its new “Baby Boutique” concept, which launched online on March 15th and is expected to roll out to 200 locations this year. The updated format greatly expands Target’s assortment of brands and baby items, including the debut of beloved and upscale baby brands like Uppababy, Doona, Bugaboo and Stokke, which previously hadn’t been sold at the retailer. Target’s strategy appears to be aimed at courting and retaining new and expectant parents who are looking for a one-stop shopping experience for baby products, whether in hardlines or softlines.
The baby category, in particular, has presented a white space opportunity for retailers across the country since the closure of buybuy Baby in 2023. Since then, Kohl’s launched a shop-in-shop concept with Babies”R”Us and buybuy Baby had a small but unsuccessful relaunch after being sold. That has left consumers with fractured options, including e-commerce only, department stores, mass merchants and local boutiques. Target’s push could propel it into the national leader role for the category, and also help the brand to revitalize itself after a challenging 2025 performance.
Looking at some of the insights behind this new pivot, it’s clear that Target is hoping to capture the attention of shoppers who would have normally shopped at the former buybuy Baby. According to Placer.ai’s foot traffic combined with Personalive consumer segmentation, Target’s shopper profile looks very similar to that of buybuy Baby during its operation. Specifically, the share of visits by Wealthy Suburban Families, Near Urban Diverse Families and Ultra Wealthy Families are all very closely aligned between the two chains, indicating that Target’s strategy could easily entrench itself with today’s consumer.
Despite the battle for national attention, there have also been innovations on a smaller scale in baby products. Babylist, a popular digitally native registry service, opened its first brick and mortar location in Beverly Hills in 2023, bringing the showroom experience to life for shoppers who want to test and learn before committing to baby gear. Baby items, particularly in hardlines like car seats and strollers, tend to be large ticket items, and many parents still want that tactile experience while shopping.
According to Placer’s foot traffic insights, the location has been successful in attracting the right customer base. The store allows shoppers to gain product knowledge and compare brands and models by category, making it easier to plan an online baby registry more effectively. Traffic has grown over the last year to the showroom, and the store's audience over-indexes for Ultra Wealthy Families, which both could drive conversion to the online marketplace.
Another group that has a high share of visits are Sunset Boomers, which would account for potential new grandparents. Grandparents are a vital shopper base for baby retailers, as they have higher levels of disposable income and are often purchasing gifts for others. Target could benefit from the buy-in of this group as it continues its journey into the world of baby-focused retail.
For more data-driven retail insights, visit placer.ai/anchor.
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.
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.
