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Economic pressures created a challenging backdrop for the QSR space in 2025. Many consumers adjusted their dining-out habits, leading to uneven foot traffic across the category. Within this environment, AI-powered location intelligence suggests that Yum! Brands – the parent company of Taco Bell, KFC, Pizza Hut, and Habit Burger & Grill – has been comparatively well positioned. We dove into the data for a closer look at how Yum! and its portfolio performed in 2025 and the most recent Q4.
Although limited-service restaurants faced headwinds in 2025, Yum! Brands appeared to stay ahead of the pack. As a whole, the company's portfolio – QSRs plus the smaller Habit Burger & Grill – posted year-over-year (YoY) foot traffic growth in every quarter, outperforming the broader QSR category, which recorded YoY visit declines during much of the year.
Beyond value and compelling menu innovation, convenience and ease of experience remain central to why consumers choose limited-service chains. To reinforce its advantage, Yum! has spent the past year expanding its suite of AI-driven technology tools across its brands – platforms designed to optimize restaurant operations, delivery, and digital ordering. The company has even pointed to its proprietary software as an enabler of daily menu drops and viral promotions, reinforcing the other two critical motivations for limited-service diners: craveability and value. As these tools roll out to more locations, the data suggests Yum!’s competitive edge could continue.
An analysis of foot traffic across Yum! Brands’ portfolio highlights which concepts are driving the company’s visit gains. Pizza Hut and Habit Burger & Grill recorded YoY monthly overall visit and same-store visit growth in most of Q4 2025 – indicating that underlying demand remains intact despite heightened volatility in the current economic environment.
Of the four brands, however, Taco Bell remains Yum!’s primary driver of growth. The brand delivered the largest and most consistent YoY monthly overall visit and same-store visit growth throughout Q4 2025 – with National Taco Day promotions and the return of Cheesy Dipping Burritos likely contributing to elevated traffic.
Meanwhile, KFC experienced month-to-month visit gaps throughout Q4 2025 while mustering nearly flat same-store visits. This could suggest that while the brand has consolidated its footprint, existing locations see sufficient demand to support a broader turnaround strategy.
Even as economic pressures continue to reshape how consumers engage with limited-service dining, Yum! Brands appears well positioned to navigate ongoing uncertainty. A combination of operational investment and consumer-facing innovation suggests the company’s portfolio has built a durable foundation to support evolving market conditions.
Want more restaurant industry 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.

Saks Global’s Chapter 11 filing reflects a convergence of balance-sheet pressure and evolving consumer behavior rather than a sudden collapse of its brands or customer relevance. Following the acquisition of Neiman Marcus in late 2024, the company carried a significantly higher debt load, which reduced financial flexibility at a time when the broader luxury department store sector was facing uneven demand.
But while a missed interest payment was the immediate catalyst for the bankruptcy filing, traffic data suggests that the challenges facing Saks Global extended beyond balance-sheet constraints. AI-powered traffic data shows that Saks Fifth Avenue and Neiman Marcus were underperforming most major department stores both on average visits per venue and on rates of repeat visitors already in H1 – before supplier relationships became more visibly strained. So even if inventory constraints and vendor caution likely amplified these trends in H2, the data suggests that softer consumer engagement with these chains was also due to earlier challenges in delivering an experience that consistently brought shoppers through the door.
(Kohl’s is a notable exception – while it underperformed Neiman Marcus on year-over-year visits per venue in H1, the banner still maintained the highest rate of repeat visitation by far, pointing to a more resilient customer base that can help cushion short-term traffic volatility).
Analyzing in-store behavior at Saks Fifth Avenue and Neiman Marcus relative to other premium department stores is also revealing. Both banners skew more heavily toward midday and weekday visits than Nordstrom or Bloomingdale’s, a pattern that suggests a greater reliance on proximity- and convenience-driven traffic rather than by planned destination trips.
In contrast, Nordstrom and Bloomingdale's capture more visits during evenings, and weekends – times typically associated with browsing, social shopping, and occasions when shoppers are more willing to spend time in-store. These visit patterns reinforce the idea that Saks and Neiman Marcus are currently attracting more “pop-in” visits than experience-led ones.
Looking ahead, Saks Global’s path out of bankruptcy depends on repairing its balance sheet while rebuilding in-store experiences that support destination-driven shopping. To remain competitive, the company will need to restore consistent inventory, sharpen merchandising curation, and reinvest in service and experiences that encourage planned visits rather than incidental stop-ins.
At the same time, the data suggests a clear framework for rationalizing the footprint. Underperforming locations are likely those that skew heavily toward weekday, midday, and low-frequency visits, signaling reliance on proximity rather than loyalty or experience. These stores may struggle to justify continued investment, particularly if they sit in markets with limited repeat demand or weak engagement relative to peers. By using traffic trends, visit timing, and repeat behavior to guide closure or consolidation decisions, Saks Global can emerge from bankruptcy with a smaller but healthier store base – one aligned around markets where the brand can reclaim its role as a destination. In that sense, bankruptcy offers not just a financial reset, but a chance to refocus the business around the stores and experiences most likely to drive sustainable, long-term demand.
For more data-driven insights, visit placer.ai/anchor.
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.

Rising travel, lodging, and theme park costs are reshaping how people spend their leisure time. Instead of long-distance or high-ticket trips, consumers are increasingly turning to local outdoor spaces – an option that is lower cost, flexible, and repeatable. What began as a pandemic-era adjustment has solidified into a durable behavioral shift, with meaningful implications for retailers, restaurants, real estate owners, and civic leaders.
Visits to local parks remain well above 2019 levels, signaling that outdoor spaces are no longer a temporary substitute for other leisure options but a primary destination in their own right.
Importantly, people are not just showing up more often – they are staying longer. The share of park visits lasting more than 30 minutes has increased meaningfully compared to pre-pandemic norms, indicating deeper engagement rather than quick, utilitarian stops.
This shift elevates parks from passive amenities to active drivers of surrounding economic activity. Longer visits create more opportunities for nearby food, retail, and service businesses to capture spend before and after park usage.
Visits to outdoor retailers also remain mostly above pre-pandemic levels throughout 2025, even as year-over-year performance versus 2024 fluctuates month to month. Stronger comparisons against 2019 – especially during spring and fall – suggest that outdoor retail demand is supported by a structurally larger base of outdoor participation rather than a short-lived rebound. This resilience reinforces outdoor retail as a downstream beneficiary of sustained, lifestyle-driven shifts toward local recreation.
Park visitation patterns have also shifted later in the day. Evening visits – particularly between 6:00 PM and 10:00 PM – now account for a larger share of total traffic than they did in 2019. This reflects broader changes in work schedules, hybrid work adoption, and how people structure leisure around daily routines.
For businesses and municipalities alike, this timing shift is critical. Demand is increasingly concentrated outside traditional daytime hours, which has implications for operating hours, staffing, safety, and programming decisions
The sustained shift toward local, outdoor leisure has broad implications across retail, dining, real estate, and the public sector.
For retailers, especially those tied to outdoor activities or convenience-driven purchases, increased park visitation and longer dwell times translate into more frequent, trip-based shopping opportunities. Proximity to parks, trails, and outdoor corridors matters more as consumers increasingly combine recreation with same-day retail needs.
Dining operators can benefit from the same dynamics. As park visits stretch later into the day, food demand increasingly overlaps with evening meal and snack occasions. Restaurants positioned near parks or along common access routes are well placed to capture post-activity traffic, particularly if hours and menus align with evening usage.
For commercial real estate owners and developers, park adjacency has become a tangible performance factor rather than a soft placemaking feature. Consistent, repeat visitation to nearby outdoor spaces can help stabilize foot traffic for retail and mixed-use assets, especially as consumers pull back from destination-oriented travel and entertainment.
Civic stakeholders also play a central role. Rising visitation – particularly in the evening – raises the importance of lighting, safety, maintenance, and programming that reflect how residents actually use parks today. Well-supported parks not only improve quality of life but also generate economic spillovers for surrounding businesses.
Organizations that align their locations, operating hours, and investment decisions with this reality are best positioned to capture value as leisure continues to localize.
For more data-driven consumer insights, visit placer.ai/anchor.
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.
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As Winter Storm Fern advanced across the U.S. in late January, consumer behavior followed a predictable pattern: early preparation gave way to a sharp pre-storm rush, followed by widening geographic divergence as conditions worsened. Retail visit data from January 22nd and 23rd highlights how quickly storm-driven demand intensified – and which categories and regions were best positioned to capture it.
Retailers saw a clear escalation in traffic from January 22nd to January 23rd, underscoring how storm proximity compressed shopping activity into a narrow window.
Home Improvement & Furnishings retailers saw the largest visit spikes on both January 22nd and 23rd as consumers focused on preparing their homes ahead of the storm. Visits were already 20.2% above the YTD (January 1st to 23rd) daily average on January 22nd and rose to 41.7% above average the following day – making the category the clear pre-storm leader. The pattern suggests shoppers were prioritizing purchases such as heating supplies, generators, weatherproofing materials, and snow-removal equipment as conditions grew more imminent.
Grocery Stores recorded the second-largest increases, reflecting consumers’ efforts to stock up on food and beverages in anticipation of staying home, with visits up 14.2% on January 22nd and climbing to 28.4% on January 23rd compared to the YTD daily average.
Value-oriented and necessity-driven categories also saw demand intensify. Discount & Dollar Stores experienced a modest 6.2% lift on January 22nd, which surged to 25.5% the following day. Drugstores & Pharmacies saw visits climb from 9.8% to 21.0%, while Superstores rose from 7.5% to 19.9% over the same period.
Pet Stores & Services stood out for their late-breaking surge: after seeing virtually flat traffic on January 22nd (+0.2%), visits jumped to 18.5% above average on January 23rd, suggesting that many consumers delayed pet-related preparedness until just before conditions worsened.
Across all categories, the doubling of visit lifts from one day to the next indicates that while some consumers planned ahead, a significant share delayed their storm preparations until the threat felt immediate.
The storm’s west-to-east progression was also reflected in shifting regional visitation patterns. On January 22nd, the largest visit surges were concentrated in parts of the Midwest, consistent with Winter Storm Fern’s earlier impacts across inland regions. By January 23rd, as the storm intensified and expanded across the South and Eastern Seaboard, retail visits spiked sharply in those areas as consumers rushed to complete last-minute errands ahead of worsening conditions. At the same time, parts of the Midwest saw more muted growth or visit slowdowns, suggesting that storm-related shopping activity there may have peaked earlier.
This data suggests that storm-related shopping remains a fundamentally local behavior, with consumers responding most strongly when severe conditions feel imminent in their immediate area. At the same time, the Midwest slowdown suggests that storm-related demand is finite and front-loaded, with visit activity tapering once households complete their initial preparation trips.
AI-driven location analytics reveals that storm-driven retail demand is not only intense but highly compressed, with visits surging in the brief window just before conditions deteriorate locally and fading quickly once preparation trips are complete. For retailers, capturing weather-driven demand seems to depend less on the size of the storm and more on aligning operations to where – and when – urgency is about to peak.
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.

Tractor Supply’s growing footprint continues to stand out in a retail environment where many chains remain cautious about physical expansion. We took a closer look at Tractor Supply’s market positioning to better understand how the chain’s deliberate expansion strategy sets it up for success in 2026.
Tractor Supply continued to scale its physical footprint in 2025, leveraging the acquisition of former Big Lots sites and reinforcing store growth as a core lever of its “Life Out Here” strategy. The chain’s expansion likely contributed to its steady year-over-year (YoY) visit growth throughout 2025. Meanwhile, positive average visits per location in most months suggests that new stores were capturing incremental demand rather than diluting traffic at existing locations – reinforcing management’s commentary around limited cannibalization.
Tractor Supply intends to open around 100 new stores in 2026 as part of its longer-term roadmap to 3200 stores (the retailer currently has 2,398 locations), setting high expectations for continued foot traffic growth in 2026.
As Tractor Supply expands, its strategy has been focused on rural and western high-growth markets where demand remains underserved. And with a relatively small store format, Tractor Supply has a distinct advantage over big-box chains that often face site-selection challenges in these markets.
Analysis of AI-based potential market data combined with the STI: Market Outlook dataset shows that the unmet demand (demand minus supply) for building materials and supplies within Tractor Supply’s potential market – i.e. the areas from which it drives traffic – far surpasses unmet demand in the wider Home Improvement category’s potential market. This comparison – in just one of the retail categories that Tractor Supply occupies along with its peers – suggests substantial white space for the chain, driven by a footprint that prioritizes underserved markets rather than the more established ones where many industry counterparts compete.
And as Tractor Supply expanded between 2024 and 2025, unmet demand for building materials and supplies in the chain's potential market increased, even as unmet demand across the broader Home Improvement category declined. Together, these trends point to a site selection strategy that places Tractor Supply in high-demand regions where few retailers are positioned to fully meet consumer needs.
What can we learn from Tractor Supply’s strategy and 2025 performance? Sometimes, it pays to be smaller, and unlock demand away from the competitive landscapes where bigger players operate. By pairing an accelerated store-opening strategy with purposeful site selection, Tractor Supply appears well-positioned for sustained traffic growth.
Will Tractor Supply continue to build momentum in 2026? 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.
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Recent traffic trends to major dining chains show the divergence within the full-service dining space going into 2026. While Brinker International's flagship brand Chili's Grill continued reaping the benefits of its popular food bundles and drinks specials, Maggiano's Little Italy – the company's more upscale concept – struggled to reach 2024 visitation levels in Q4 2025.
For both Dine Brands Global, Inc. and Texas Roadhouse, Inc., traffic changes were mostly due to storefleet reconfigurations. Dine Brands' three banners contracted in 2025, leading to overall visit declines at Applebee's and Fuzzy's (IHOP maintained stable traffic patterns) – but all three concepts outperformed in terms of average visits per venue as the company's rightsizing efforts appeared to be bearing fruit. Meanwhile, Texas Roadhouse, Inc. showed the opposite pattern as its three banners expanded, leading to overall visit growth – but average visits per venue decreased, suggesting that traffic gains were mostly driven by unit expansion.
These patterns reflect a more selective consumer environment heading into 2026, where growth is increasingly shaped by brand positioning, value perception, and disciplined fleet strategies rather than broad-based demand recovery. A closer look at monthly visit trends across major banners further illustrates these dynamics.
After leading the full-service restaurant category in 2024, Chili’s once again emerged as a standout performer in 2025, delivering consistent monthly visit gains despite a softer consumer environment. The brand has successfully established and maintained a clear value proposition, helping keep Chili’s top of mind for consumers seeking an affordable sit-down dining option
At the same time, recent monthly traffic trends suggest that sustaining this momentum into 2026 may require continued innovation, whether through refreshed bundled offerings, targeted promotions, or menu updates that reinforce value without eroding margins. But even if traffic growth moderates in the year ahead, maintaining the elevated visitation levels achieved over the past two years would still leave Chili’s in a notably strong competitive position within the full-service dining landscape.
Applebee’s and IHOP saw YoY declines in overall visits, but same-store traffic generally held up better – indicating that fleet rationalization helped stabilize per-restaurant demand. These trends point to the importance of right-sizing footprints and prioritizing unit-level productivity in a constrained consumer environment.
Visits to Texas Roadhouse in 2025 were up 2.1% compared to 2024, in part thanks to the chain's ongoing expansion. Same-store performance also remained positive for much of the year, suggesting that the larger store fleet can be supported by existing demand.
And even as traffic trends moderated toward the end of the year, the chain’s overall 2025 visit growth suggests an underlying demand that is strong enough to support Texas Roadhouse’s expanding footprint despite the most recent slowdown.
Overall, traffic patterns at these three major FSR players point to a more selective and competitive full-service dining environment heading into 2026, where broad-based demand recovery remains elusive. Brands that clearly communicate value or actively optimize their store fleets appear better positioned to defend store-level demand, while expansion-led growth models face increasing pressure to deliver stronger unit-level productivity. As consumer discretion remains constrained, execution and positioning – not scale alone – will likely define traffic winners in the year ahead.
Fore more data-driven consumer insights, visit placer.ai/anchor
Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make estimations for visits to locations across the US. The data is trusted by thousands of industry leaders who leverage Placer.ai for insights into foot traffic, demographic breakdowns, retail sale predictions, migration trends, site selection, and more.

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

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

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