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Migration to the Mountain States, named for the sprawling Rocky Mountain range that runs through the region, has been on an upward trend in recent years. And one state in particular – Utah – has received an impressive influx of new residents.
Which areas are experiencing the most growth? And what is driving migration to the Beehive State? We take a closer look.
Utah, with its iconic national parks and burgeoning tech industry, is growing fast. According to Placer.ai’s Migration Trends Report, Utah experienced an 5.5% rise in population between January 2020 and January 2024, partially driven by inbound domestic migration: 1.8% of the state’s January 2024 population moved in between January 2020 and January 2024.
Utah has a relatively young population – the median age in Utah (according to the 2021 ACS 5-Year Projection dataset) is 31. But relocators to the state seem to be coming from older states – the weighted median age in the states of origins of newcomers moving to Utah over the past four years was 38.
But although Utah’s median age is lower than the median age in the states of origin, the median HHI in the Beehive State is higher than in its feeder states. Between January 2020 and January 2024, the weighted median HHI in the states feeding migration to Utah was $71K/year, lower than the Utah median of $79K/year (although higher than the national average of $69.0K/year).
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Although Utah as a whole has seen positive net migration over the past four years, the new residents are not evenly distributed across the state’s major metropolitan areas. Inbound domestic migration was particularly strong in the Provo-Orem and Ogden-Clearfield CBSAs (core-based statistical areas), with both states also seeing significant increases in their population (10.7% and 5.1%, respectively) over the past four years. But during the same period, the migrated share of the population of Utah’s largest CBSA – Salt Lake City – has declined, and the overall population in the Salt Lake City CBSA grew by just 1.0%. So what is driving migration to Provo-Orem and Ogden-Clearfield?
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January 2020 to January 2024 migration data reveals that relocators to Provo and Ogden come from CBSAs with a lower median age and HHI compared to those moving to Salt Lake City: Newcomers to the Provo-Orem and Ogden-Clearfield CBSAs came from CBSAs with a weighted median HHI of $73K and $72K, respectively, compared to a $75K median HHI for CBSAs feeding migration to the Salt Lake City CBSA. And the weighted median age in the CBSAs of origin for Provo-Orem and Ogden Clearfield was 25 and 32, respectively, compared to 33 in the CBSAs of origin for Salt Lake City.
The movement of younger people from lower-HHI areas to these CBSAs may indicate that many of those relocating to Utah to benefit from the state’s robust economy are specifically choosing the Provo-Orem and Ogden-Clearfield metro areas.
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Niche’s Neighborhood Grades – available in the Placer.ai Marketplace – assigns grades to various types of regions based on a variety of factors, including job opportunities. And comparing the Niche rating for “Jobs” assigned to Utah’s three largest CBSAs with the aggregate “Jobs” grade assigned to the CBSAs of origin also suggests that Provo and Ogden’s economic opportunities are driving migration to these smaller metro areas.
All three Utah CBSAs analyzed received a higher “Jobs” grade than their CBSAs of origin – indicating that the employment opportunities in all three metro areas are likely drawing newcomers. But while Salt Lake City only got a “B+” in “Jobs” – just one grade up from the aggregate grade assigned to its areas of origin – Provo-Orem and Ogden-Clearfield got a “Jobs” grade of “A-”, or two notches up from the “Jobs” grade in their CBSAs of origin. The highly robust job markets in these smaller CBSAs may explain why newcomers seem to prefer Provo-Orem and Ogden-Clearfield to Salt Lake City.
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Utah’s population growth makes it one of the most exciting states to watch, and the state’s promising employment opportunities seems to be a major draw for newcomers to the state.
Will Utah continue to experience population growth?
Visit placer.ai to keep up with the latest migration trends.
This blog includes data from Placer.ai Data Version 2.0, which implements improvements to our extrapolation capabilities, adds short visit monitoring, and enhances visit detection.
In a world where convenience is key and online shopping reigns supreme, many brands are turning to experiential retail to draw visitors into brick-and-mortar stores. We take a look at three companies with different types of experiential offerings – Michaels, DICK’S, and Lowe’s Home Improvement – to understand what experiential retail can look like in 2024.
Some retailers are encouraging consumers to engage fully in their brand by dedicating entire brick-and-mortar venues entirely to immersive experience. Sporting goods brands in particular, including Lululemon with its yoga studios and Nike and its training studios, have employed this strategy to directly engage with their core audience. And perhaps the best example of this is the DICK’S House of Sport concept, launched in 2021 by sporting goods retailer DICK’S.
DICK’S currently operates 12 House of Sports locations where visitors can repair their bikes, pick out a golf club, use a climbing wall or batting cage. The concept has been highly successful, especially as more people engage in some form of recreational sports or fitness activities, and the chain is looking to add at least 100 more of these experiential stores in the next five years.
Quarterly foot traffic patterns suggest that the new locations will be met with enthusiasm. Visits to the three longest-running House of Sports stores in Q4 2023 were 7.2% higher than they were in Q4 2022, while visits to DICK’S Sporting Goods stores nationwide were 2.3% lower for the same period. Psychographic data also reveals that House of Sport visitors also tend to be slightly older and more established than visitors to DICK’S nationwide – and this older audience may be more inclined to spend more than their younger counterparts.
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By creating an immersive athletic experience that taps into the growing popularity of personal fitness, House of Sport can continue to draw in visitors and foster community – and serve as a model for other sporting goods retailers looking to expand their experiential offerings.
Retailers who don’t want to devote an entire location to their experiential offering can also leverage their regular venues to offer visitors hands-on engagement with their products on certain days or time slots. Rising costs have led more people than ever to turn to DIY – and meeting that demand, leading home improvement retailer Lowe’s has introduced a DIY workshop on Saturdays and Sundays at 100 locations across the country. Visitors heading to participating Lowe’s stores will be able to participate in workshop stations and take advantage of all-day demos – with no registration required. The company also runs a family-friendly Weekending at Lowe’s program, which allows visitors to register to free workshops focused on child-friendly activities, such as creating a butterfly biome or a tabletop basketball game
Providing people with a hands-on, practical approach to home repairs may help Lowe’s expand its customer base as more people embrace DIY concepts. Participants in the DIY workshops may feel more confident in tackling new projects at home. They are also more likely to choose Lowe’s products due to familiarity with the store and its offerings — a win for the company.
Comparing year-over-year (YoY) visits at Lowe’s locations with DIY workshops to the foot traffic performance of the chain as a whole indicates that the DIY venue, while experiencing the effects of the ongoing retail headwinds, are managing to perform better than Lowe’s stores overall. And analyzing locations using the Spatial.ai: PersonaLive dataset reveals that Lowe’s DIY stores are particularly popular among rural segments, with more "Rural Average Income" and "Rural Low Income" segments in their captured markets than their potential market*.
*A chain’s potential market refers to the population residing in a given trade area, where the Census Block Groups (CBGs) making up the trade area are weighted to reflect the number of households in each CBG. A chain’s captured market weighs each CBG according to the actual number of visits originating to the chain from that CBG.
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Lowe’s can harness this data if it seeks to expand the DIY concept further to help it capitalize on its success among rural audiences – and other retailers can take note of the demand for hands-on workshops from this segment.
A third model for experiential retail empowers the customer to take the reins and decide when to schedule the in-store event – and who to add to the guest list. Craft chain Michaels, which has long emphasized child-friendly experiences like summer camps and free classes, recently introduced store-hosted birthday parties for kids up to age 13.
Demographic data from both potential and captured trade areas suggest that this focus on kids activities is succeeding in attracting the family households in its trade area. Michaels attracts a larger share of married couples with children in its captured market than in its potential market, and has a captured market household size of 2.6, slightly larger than its potential market household size. The share of households in Experian: Mosaic’s “Suburban Style,” “Flourishing Families”, and “Family Union” segments were also all higher in Michaels captured market than in its potential market.
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Michael’s seems to be positioning itself as a one-stop shop for crafters of all ages, and focusing on children’s events may help the chain attract more family segments to its stores. This serves as a reminder of the draw that quality children’s entertainment can provide and offers a blueprint for retailers wishing to attract more families to their locations.
These three chains prove that there are plenty of ways to attract people into brick-and-mortar stores. By offering workshops, events, and in-store attractions, the three chains are building brand awareness and increasing their foot traffic.
Will experiential retail continue to dominate in 2024?
Visit placer.ai/blog to stay up-to-date on the latest retail trends.
This blog includes data from Placer.ai Data Version 2.0, which implements improvements to our extrapolation capabilities, adds short visit monitoring, and enhances visit detection.
One of the major stories of 2023 was the rise in food prices, with costs up roughly 25% since 2020 – and the increasing costs of food and other goods have helped discount grocers thrive.
We checked back in with two grocery chains known for their bargain prices and private labels – Aldi and Lidl – to see how they’re doing.
Aldi offers prices that rival those of discount grocers, making it a major player in the discount grocery segment. And these attractive prices have helped the company see significant visit growth over the past few years. Year-over-year (YoY) monthly visits to Aldi were up throughout 2023 and into 2024, with some of the growth due to the chain’s aggressive expansion. And the company plans to grow even further – Aldi has announced plans to open another 800 stores over the next few years.
Lidl – another German-based grocer – opened its first location in Virginia in 2017. The chain currently has around 170 locations in the country, primarily on the East Coast, and is also expanding – albeit at a slower pace. Between February 2023 and February 2024, YoY visits to Lidl were up almost every month with only a slight dip in January 2024 – perhaps due to the unseasonal cold – a promising sign for the discount grocer as more consumers than ever choose low-cost food options.
Although both Lidl and Aldi are German-owned discount grocers, examining the demographics for the two brands' trade areas nationwide sheds light on the differences between the two chain’s consumer bases.
Analyzing the trade area median HHI reveals that Lidl attracts a higher-income clientele than Aldi: The median household income (HHI) in Aldi’s trade area was slightly lower than the the nationwide median, with the median HHI in the chain’s captured market even lower than the median HHI in its potential market. This indicates that Aldi locates its stores in areas that are accessible to the average consumer and succeeds in attracting also the slightly lower income segments within its potential trade area.
Meanwhile, Lidl’s potential market median HHI stood at $78.8K/year in 2023, and the median HHI in its captured market was even higher – $88.1K/year – indicating that Lidl stores are located in more affluent areas, and that the company caters to the wealthier households within those neighborhoods.
The share of households with children in Aldi’s potential and captured market was also almost identical to the nationwide average – indicating once again Aldi’s success in reaching the average U.S. grocery shopper. Lidl, on the other hand, saw more households with children in both its captured and potential markets, with the share of households with children in its captured market around two percentage points higher than the share of households with children nationwide. So while Aldi and Lidl do share some similarities in terms of origins, preference for private label, and pricing, the trade area analysis points to major differences between the two chains’ audiences.
*A chain or venue’s potential market refers to the people that reside in its trade area, based on the business’ True Trade Area and weighted by census block group (CBG) within the trade area according to the size of its population. Captured markets represent the population that visits the business in practice, and the data is obtained by weighting each CBG according to its share of visits to the chain or venue in question.
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Diving into the psychographic data for Aldi and Lidl adds another dimension to the trends revealed by the demographic data. While both brands are popular among suburban audiences – Aldi tends to attract a more blue-collar customer, while Lidl is frequented by a wealthier suburban segment. The share of visitors falling into the “Small Town Low Income” category was 7.5% for Aldi compared to 0.9% for Lidl. Conversely, Lidl saw 16.7% of its visitors falling into the “Upper Suburban Diverse Families” segment, while Aldi had 10.6% of its consumers in that category.
And while Aldi and Lidl have a hold on different suburban segments, the chains’ expansion strategies seem geared to grow each chain’s reach outside the other’s orbit. Lidl has been opening stores in big cities along the East Coast, including New York City’s tony Chelsea neighborhood, perhaps in a bid to reach more of the wealthier customers that favor the brand. Aldi, meanwhile, recently acquired grocery chains Winn-Dixie and Southeast Grocers, brands that typically attract a more price-sensitive consumer. This acquisition will significantly expand Aldi’s presence and will likely appeal to value-oriented shoppers, a segment already receptive to its offerings.
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The past few years have seen the grocery space adapting to an increasingly value-oriented consumer, and Aldi and Lidl have benefitted from this shift. As inflation cools and both companies expand their footprints, will they continue on their upward trajectory?
Follow Placer.ai’s data-driven retail analyses to find out.
This blog includes data from Placer.ai Data Version 2.0, which implements improvements to our extrapolation capabilities, adds short visit monitoring, and enhances visit detection.
Since COVID, millions of Americans have relocated from major population centers in California, New York, and Illinois (among others) to other regions of the country. Whether in search of job opportunities, affordable housing, or simply a change of scenery, thousands of people have decamped to places like Tampa, Florida, Bozeman, Montana, and Portland, Maine. And the great state of Texas – with its wide open spaces and relatively affordable cost of living – has emerged as a favored destination.
So with 2024 underway, we dove into the data to explore domestic migration trends in the Lone Star State. How much has the population of Texas grown as a result of domestic migration over the past several years – and which metro areas (CBSAs) are attracting new residents? Are people moving to major cities like Dallas, Houston, Austin, and San Antonio, or are they heading out to the suburbs?
Between December 2019 and December 2023, Texas’ population grew by 4.3% – with nearly a third of this increase driven by new residents hailing from elsewhere in the U.S.
Perhaps unsurprisingly, many of these new arrivals made a bee-line to Texas’ four most populous metropolitan areas – Austin-Round Rock-Georgetown, San Antonio-New Braunfels, Dallas-Fort Worth-Arlington, and Houston-The Woodlands-Sugar Land. During this time period, each of these CBSAs experienced positive net migration (meaning that more people moved to these areas than away from them) ranging from 0.4% to 3.4%.
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But a deeper analysis of foot traffic trends reveals that, even as the CBSAs as a whole added new residents, the primary cities anchoring the CBSAs often lost more domestic migrants than they gained. Austin proper lost 6.1% of its population to relocation, while Dallas, Houston, and San Antonio lost 4.2%, 3.9%, and 3.2%, respectively. Only Fort Worth – Texas’ fifth-most-populous city – experienced positive net migration over the past four years.
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Why are major metropolitan areas seeing population influxes, even as their central urban hubs experience outflows? Drilling down even deeper into zip-code level location intelligence provides a striking snapshot of what’s actually happening on the ground.
In all four CBSAs, zip codes belonging to the metro area’s flagship city were more likely to experience negative net migration – while those in further-away suburbs and towns were more likely to see positive inflow.
The relative growth experienced by Fort Worth can be understood against this backdrop: Fort Worth may be one of Texas’ biggest cities, but it is smaller – and less expensive – than Dallas, which dominates the metro area.
Suburban life offers residents many of the benefits of proximity to major urban centers, without some of the drawbacks – like smaller homes. And with more Americans free today to live further away from the office, many appear to be choosing suburban chill over big-city hassle.
Home to the Alamo, a premier state fair, and arguably one of the cultiest grocery chains in the country (H-E-B, of course), Texas has become a key destination for Americans seeking greener (and cheaper) pastures. And though major metropolitan centers in the Lone Star State have seen significant positive net migration over the past four years – much of that growth has taken place outside of the state’s biggest cities.
How will Texas’ population continue to evolve over the next months and years? Will big cities make a comeback – or are suburbs and smaller towns poised to remain the main drivers of growth?
Follow Placer.ai’s data-driven domestic migration analyses to find out.
This blog includes data from Placer.ai Data Version 2.0, which implements improvements to our extrapolation capabilities, adds short visit monitoring, and enhances visit detection.
Brands like M&Ms, Hershey’s, and Jelly Belly are redefining what it means to be as happy as a “kid in a candy store.” With their life-size M&M characters on a flagship in Orlando, FL, a chocolate Statue of Liberty sculpted out of 800 pounds of Hershey’s chocolate on the Las Vegas Strip, or a working jellybean factory tour in Fairfield, CA, manufacturers are literally bringing their brands to life. M&M’s World in Orlando, FL posted particularly impressive year-over-year visits in the second half of 2023.
Recently, Hollywood darling Timothee Chalamet starred in the fantastical movie Wonka, grossing $600M+ worldwide. In other headline news, the “tried to jump on the wagon but failed miserably” fiasco of the unauthorized Willy’s Chocolate Experience in Scotland reveals that the appetite for sweets and chocolate is insatiable. Never fear, if you missed the Candytopia pop-up a few years ago, you can head over to Dylan’s Candy Bar for an experience right out of Charlie and the Chocolate Factory. It’s clear that demand peaks in the summer, probably due to locations that see summer tourists. The holidays are another popular season for buying sweets.
At Hershey’s Chocolate World, one can be immersed in all-things chocolate, from creating your own candy to taking a selfie with a life-size Reese’s peanut butter cup. The dessert options are limited only by your imagination. That tower of S’mores sure looks tempting!
Many visitors also opt to visit the Hershey Story Museum or stay at Hershey Lodge or the Hotel Hershey.
If you prefer your sweets in liquid form, there are three Coca-Cola Stores--in Atlanta, Las Vegas, and Orlando--to satisfy your cravings. Here, you can buy a Coke plushie, flout the famous “Enjoy Coca-Cola” slogan shirt in a variety of languages, or dress yourself head-to-toe in comfy Coke PJs. One of the coolest options is an international tasting flight that lets you try out Coca-Cola beverages from around the world, with flavors like sparberry from Zimbabwe.
At the Coca-Cola Store in Orlando, FL, visitation jumps during vacations like Spring Break, summer, and Christmas holidays.
Another beloved brand that has made its way into brick-and-mortar is King’s Hawaiian. Founded in 1950, they were famous for their round loaves of sweet and fluffy Hawaiian bread. Fast forward three-quarters of a century later, and they have added new options like savory dinner rolls or pull-apart pans of bread. One can experience gastronomic delights made with Hawaiian bread at their Torrance-based King’s Hawaiian Bakery and Restaurant.
The restaurant menu includes breakfasts featuring their famous King’s Hawaiian Sweet Bread as French toast, lunch and dinner options like Macadamia Nut Onion Rings, Chicken Katsu Curry Loco Moco, and Saimin noodles, but it’s the bakery that literally takes the cake. The Paradise Delight Cake has three layers of chiffon cake in enticing flavors like guava, passionfruit, and lime. It is then topped with layers of fresh strawberries, peaches, and kiwis. One can also choose from chocolate, coconut, pineapple, raspberry cakes, and more.
With Placer's ranking of "Breakfast, Coffee, Bakeries, and Dessert Shops" indicating that King's is in the top 1% nationwide and statewide, it looks like they've found a sweet recipe for success.
The Waldorf Astoria and Ritz-Carlton hotels are two of the most recognizable names in luxury lodging. Both opened in New York City – the Waldorf Astoria in 1893 and the Ritz-Carlton in 1911 – and are owned by two major hotel corporations: the Waldorf Astoria is part the Hilton Hotels & Resorts portfolio of brands, while the Ritz-Carlton is part of Marriott International, Inc’s portfolio.
Who is most likely to visit each brand? What are the similarities – and differences – between the two hotels’ guest segmentations? We take a closer look at the demographic and psychographic data to find out.
Analyzing the demographic makeup of the Waldorf Astoria and Ritz-Carlton’s trade areas by layering the STI: Popstats dataset onto captured market trade areas revealed that the Waldorf Astoria’s trade area has a higher share of households with children compared to that of the Ritz-Carlton (25.6% compared to 23.6%). But both chains had a smaller share of households with children in their trade areas relative to the nationwide average (27.6%). It seems, then, that singles or empty nesters may be more likely to book a luxury getaway than consumers with heavier parenting responsibilities.
Unsurprisingly, the chains also attract a particularly high-income clientele: The median household income (HHI) in both brands’ trade areas is over 50% higher than the nationwide median ($108.4K and $104.5K for the trade areas of the Waldorf Astoria and Ritz Carlton, respectively, compared to a nationwide median of $69.5K). The data also showed that Waldorf Astoria’s trade area is slightly more affluent than that of the Ritz-Carlton – perhaps due in part to the Ritz-Carlton’s recent attempts to court younger guests.
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Leveraging the Spatial.ai: PersonaLive dataset to explore the psychographic composition of the hotel chains’ trade area further supports the distinctions between the brands highlighted in the demographic analysis.
The psychographic analysis showed that the Waldorf Astoria had more family segments in its trade area than the Ritz-Carlton, while the Ritz-Carlton catered to more single and empty-nester households – as expected given the demographic composition of the chains’ trade areas.
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Luxury hotels are known for their impeccable service – and to curate the ideal guest experience, these brands need to accurately predict their visitors' dining and leisure preferences. Hoteliers can leverage the Placer.ai Marketplace and combine trade area data with various datasets – including data on consumers’ social media activity with tools like the Spatial.ai: FollowGraph dataset – to pinpoint their guests’ tastes and preferences.
Analyzing the preferences for certain types of foods or entertainment within the hotel chains’ trade areas revealed – once again – similarities and differences between the brands. Both chains’ trade areas included larger shares of “Farm-to-Table Cooking Enthusiasts”, “Asian Food Enthusiasts”, and “Craft Coffee At-Home Enthusiasts,” as well as more “Opera Lovers” and “Salsa Music Fans” than the nationwide average. But the foodie segments were slightly more over-indexed within the Waldorf’s trade area, while residents of the Ritz-Carlton’s trade area seemed a little more keen on Opera and Salsa. These hotel chains can leverage this data to determine the type of dining or entertainment options that will set these brands apart from the competition and best attract their specific audience.
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The Waldorf Astoria and Ritz-Carlton continue to define luxury lodging in the country while attracting some of the nation's most discerning guests. Understanding the demographic and psychographic guest segmentation of each chain can help inform your loyalty strategy.
For more data-driven travel & leisure insights, visit placer.ai/blog.
This blog includes data from Placer.ai Data Version 2.0, which implements improvements to our extrapolation capabilities, adds short visit monitoring, and enhances visit detection.
1. Expanded grocery supply is increasing overall category engagement. New locations and deeper food assortments across formats are bringing shoppers into the category more often, rather than fragmenting demand.
2. Grocery visit growth is being driven by low- and middle-income households. Elevated food costs are leading to more frequent, budget-conscious trips, reinforcing grocery’s role as a non-discretionary category.
3. Short, frequent trips are a major driver of brick-and-mortar traffic growth. Fill-in shopping, deal-seeking, and omnichannel behaviors are pushing visit frequency higher, even as trip duration declines.
4. Scale is accelerating consolidation among large grocery chains. Larger retailers are using their size to invest in value, assortment, private label, and execution, allowing them to capture longer and more engaged shopping trips.
5. Both large and small grocers have viable paths to growth. Large chains are winning by competing for the full grocery list, while smaller banners can grow by specializing, owning specific missions, or offering compelling value that earns them a place in shoppers’ routines.
While much of the retail conversation going into 2026 focused on discretionary spending pressure, digital substitution, and higher-income consumers as the primary drivers of growth, grocery foot traffic tells a different story.
Rather than being diluted by new formats or eroded by e-commerce, brick-and-mortar grocery engagement is expanding. Visits are rising even as grocery supply spreads across wholesale clubs, discount and dollar stores, and mass merchants. At the same time, growth is being powered not by affluent trade areas, but by low- and middle-income households navigating higher food costs through more frequent, targeted trips. Shoppers are showing up more often and increasingly splitting their trips across retailers based on value, availability, and mission – pushing grocers to compete for portions of the grocery list instead of the full weekly basket.
The data also suggests that the largest grocery chains are capturing a disproportionate share of rising grocery demand – but the multi-trip nature of grocery shopping in 2026 means that smaller banners can still drive traffic growth. By strengthening their value proposition, specializing in specific products, or owning specific shopping missions, these smaller chains can complement, rather than compete with, larger one-stop destinations.
Ultimately, AI-based location analytics point to a clear set of grocery growth drivers in 2026: expanded supply that increases overall engagement, more frequent and mission-driven trips, and continued traffic concentration among large chains alongside new opportunities for smaller banners.
One driver of grocery growth in recent years is simply the expansion of grocery supply across multiple retail formats. Wholesale clubs are constantly opening new locations and discount and dollar stores are investing more heavily in their food selection, giving consumers a wider choice of where to shop for groceries. And rather than fragmenting demand, this broader availability appears to have increased overall grocery engagement – benefiting both dedicated grocery stores and grocery-adjacent channels.
Grocery stores continue to capture nearly half of all visits across grocery stores, wholesale clubs, discount and dollar stores, and mass merchants. That share has remained remarkably stable thanks to consistent year-over-year traffic growth – so even as grocery supply increases across categories, dedicated grocery stores remain the primary destination for food shopping.
Meanwhile, mass merchants have seen a decline in relative visit share as expanding grocery assortments at discount and dollar stores and the growing store fleets of wholesale clubs give consumers more alternatives for one-stop shopping.
While much of the broader retail conversation heading into 2026 centers on higher-income consumers carrying growth, the trend looks different in the grocery space. Recent visit trends show that grocery growth has increasingly shifted toward lower- and middle-income trade areas, underscoring the distinct dynamics of non-discretionary retail.
For lower- and middle-income shoppers, elevated food costs appear to be translating into more frequent grocery trips as consumers manage budgets through smaller baskets, deal-seeking, and shopping across retailers. In contrast, higher-income households – often cited as a key growth engine for discretionary retail – are contributing less to grocery visit growth, likely reflecting more stable shopping patterns or a greater ability to consolidate trips or shift spend online.
This means that, in 2026, grocery growth is not being propped up by high-income consumers. Instead, it is being fueled by necessity-driven shopping behavior in lower- and middle-income communities – reinforcing grocery’s role as an essential category and suggesting that similar dynamics may be at play across other non-discretionary retail segments.
Another factor driving grocery growth is the rise in short grocery visits in recent years. Between 2022 and 2025, the biggest year-over-year visit gains in the grocery space went to visits under 30 minutes, with sub-15 minute visits seeing particularly big boosts. As of 2025, visits under 15 minutes made up over 40% of grocery visits nationwide – up from 37.9% of visits in 2022.
This shift toward shorter visits – especially those under 15 minutes – is driven in part by the continued expansion of omnichannel grocery shopping, as many consumers complete larger stock-up orders online and rely on in-store trips for order collection or quick, fill-in needs. At the same time, the rise in short visits paired with consistent YoY growth in grocery traffic points to additional, behavior-driven forces at play – consumers' growing willingness to shop around at different grocery stores in search of the best deal or just-right product.
Value-conscious shoppers – particularly consumers from low- and middle-income households, which have driven much of recent grocery growth – seem to be increasingly shopping across multiple retailers to secure the best prices. This behavior often involves making targeted trips to different stores in search of the strongest deals, a pattern that is contributing to the rise in shorter, more frequent grocery visits. At the same time, other grocery shoppers are making quick trips to pick up a single ingredient or specialty item – perhaps reflecting the increasingly sophisticated home cooks and social media-driven ingredient crazes. In both these cases, speed is secondary to getting the best value or the right product.
So while some shorter visits reflect a growing emphasis on efficiency – as shoppers use in-store trips to complement primarily online grocery shopping – others appear driven by a preference for value or product selection over speed. Despite their differences, all of these behaviors have one thing in common – they're all contributing to continued growth in brick-and-mortar grocery visits. Grocers who invest in providing efficient in-store experiences are particularly well-positioned to benefit from these trends.
As early as 2022, the top 15 most-visited grocery chains already accounted for roughly half of all grocery visits nationwide. And by outpacing the industry average in terms of visit growth, these chains have continued to capture a growing share of grocery foot traffic.
This widening gap suggests that scale is increasingly enabling grocers to reinvest in the factors that attract and retain shoppers. Larger chains are better positioned to invest in broader and more differentiated product selection, stronger private-label programs that deliver quality at accessible price points, competitive pricing, and operational excellence across stores and omnichannel touchpoints. These capabilities allow top chains to serve a wide range of shopping missions – from quick, convenience-driven trips to more intentional visits in search of the right product or ingredient.
Consolidation at the top of the grocery category is reinforcing a virtuous cycle: scale enables better value, selection, and experience, which in turn draws more shoppers into stores and supports continued grocery traffic growth.
In 2025, the top 15 most-visited grocery chains accounted for a disproportionate share of visits lasting 15 minutes or more, while smaller grocers captured a larger share of the shortest trips. As shown above, larger grocery chains, which tend to attract longer visits, grew faster than the industry overall – but short visits, which skew more heavily toward smaller chains, accounted for a greater share of total traffic growth. Together, these patterns show that both long, destination trips and short, targeted visits are driving grocery traffic growth and creating viable paths forward for retailers of all sizes.
Larger chains are more likely to serve as destinations for fuller shopping missions, competing for the entire grocery list – or a significant share of it. But smaller banners can grow too by competing for more short visits. By specializing in a specific product category, owning a clearly defined shopping mission, or delivering a compelling value proposition, smaller grocers can earn a place in shoppers’ routines and become a deliberate stop within a broader grocery journey.
As grocery moves deeper into 2026, growth is being driven by the cumulative effect of how consumers are navigating food shopping today. Expanded supply has increased overall engagement, higher food costs are driving more frequent and targeted trips, and shoppers are increasingly willing to split their grocery list across retailers based on value, availability, and mission.
Looking ahead, this suggests that grocery growth will remain resilient, but unevenly distributed. Retailers that clearly understand which trips they are best positioned to win – and invest accordingly – will be best placed to capture that growth. Large chains are likely to continue benefiting from scale, consolidation, and their ability to serve full shopping missions, while smaller banners can grow by earning a defined role within shoppers’ broader grocery journeys. In 2026, success in grocery will be less about winning every trip and more about consistently winning the right ones.
To optimize office utilization and surrounding activity in 2026, stakeholders should:
1. Plan for continued, but slower, office recovery. Attendance continues to rise and has reached a post-pandemic high, but moderating growth suggests the return-to-office may progress at a more gradual and incremental pace than in prior years.
2. Account for growing seasonality in office staffing, local retail operations, and municipal services. As office visitation becomes increasingly concentrated in late spring and summer, offices, downtown retailers, and cities may need to plan for more predictable peaks and troughs by adjusting hours, staffing levels, and local services accordingly, rather than relying on annual averages.
3. Align leasing strategies with seasonal demand. Stronger attendance in Q2 and Q3 suggests these quarters are best suited for leasing activity, while softer Q1 and Q4 periods may be better used for renovations, repositioning, and targeted activation efforts designed to draw workers in.
4. Design hybrid policies around midweek anchor days. With Tuesdays and Wednesdays consistently driving the highest office attendance, employers can maximize collaboration and space utilization by concentrating meetings, programming, and in-office expectations midweek.
5. Reduce early-week commute friction to support attendance. Monday office attendance appears closely correlated with commute ease, suggesting that reliable and efficient transportation may be an important factor in early-week office recovery.
6. Prioritize proximity in leasing and development decisions. Visits from employees traveling less than five miles to work have increased steadily since 2019, reinforcing the value of centrally located offices and housing near employment hubs.
2025 was the year of the return-to-office (RTO) mandate. Employers across industries – from Amazon to JPMorgan Chase – instituted full-time on-site requirements and sought to rein in remote work. But the year also underscored the limits of policy. As employee pushback and enforcement challenges mounted, many organizations turned to quieter tactics such as “hybrid creep” to gradually expand in-office expectations without triggering outright resistance.
For employers seeking to boost attendance, as well as office owners, retailers, and cities looking to maximize today’s visitation patterns, understanding what actually drives employee behavior has become more critical than ever. This reports dives into the data to examine office visitation patterns in 2025 – and explore how structural factors such as weather, commute convenience, and workplace proximity have emerged as key differentiators shaping how and when, and how often workers come into the office.
National office visits rose 5.6% year over year in 2025, bringing attendance to just 31.7% below pre-pandemic levels and marking the highest point since COVID disrupted workplace routines. At the same time, the pace of growth slowed compared to 2024, signaling a possible transition into a steadier phase of recovery.
With new return-to-office mandates expected in 2026, and the balance of power quietly shifting towards employers, additional gains remain likely. But the trajectory suggested by the data points toward gradual progress rather than a return to the more rapid rebounds seen in 2023 or 2024.
Before COVID, “I couldn’t come in, it was raining” would have sounded like a flimsy excuse to most bosses. But today, weather, travel, and individual scheduling are widely accepted reasons to stay home, reflecting a broader assumption that face time should flex around convenience.
This shift is visible in the growing seasonality of office visitation, which has intensified even as overall attendance continues to rise. In 2019, office life followed a relatively steady year-round cadence, with only modest quarterly variation after adjusting for the number of working days. In recent years, however, greater seasonality has emerged. Since 2024, Q1 and Q4 have consistently underperformed while Q2 and Q3 have posted meaningfully stronger attendance – a pattern that became even more pronounced in 2025. Winter weather disruptions, extended holiday travel, and the growing normalization of “workations” appear to be pulling some visits out of the colder, holiday-heavy months and concentrating them into late spring and summer.
For employers, office owners, downtown retailers, and city planners, this emerging seasonality matters. Staffing, operating budgets, and programming decisions increasingly need to account for predictable soft quarters and peak periods, making quarterly planning a more useful lens than annual averages. Leasing activity may also convert best in Q2 and Q3, when districts feel most active. Slower quarters, meanwhile, may be better suited for renovations, construction, or employer- and city-led programming designed to give workers a reason to show up.
The growing premium placed on convenience is also evident in the persistence of the TGIF workweek – and in the factors shaping its regional variability.
Before COVID, Mondays were typically the busiest day of the week, followed by relatively steady attendance through Thursday and a modest drop-off on Fridays. Today, Tuesdays and Wednesdays have firmly established themselves as the primary anchor days, while Mondays and Fridays see consistently lower activity. And notably, this pattern has remained essentially stable over the past three years – despite minor fluctuations – as workers continue to cluster their in-office time around the days that offer the most perceived value while preserving flexibility at the edges of the week.
At the same time, while the hybrid workweek remains firmly entrenched nationwide, its contours vary significantly across regions – and the data suggests that convenience is once again a key differentiator.
Across major markets, a clear pattern emerges: Cities with higher reliance on public transportation tend to see weaker Monday office attendance, while markets where more workers drive alone show stronger early-week presence. While industry mix and local office culture still matter, the data points to commute hassle as another factor potentially shaping Monday attendance.
New York City, excluded from the chart below as a clear outlier, stands as the exception that proves the rule. Despite nearly half of local employees relying on public transportation (48.7% according to the Census 2024 (ACS)), the city’s extensive and deeply embedded transit system appears to reduce perceived friction. In 2025, Mondays accounted for 18.4% of weekly office visits in the city, even with heavy transit usage.
The contrast highlights an important nuance: Where transit is fast, frequent, and integrated into daily routines, it can support office recovery, offering a potential roadmap for other dense urban markets seeking to rebuild early-week momentum.
Another powerful signal of today’s convenience-first mindset shows up in commute distances. Since 2019, the share of office visits generated by employees traveling less than five miles has steadily increased, largely at the expense of mid-distance commuters traveling 10 to 25 miles.
To be sure, this metric reflects total visits rather than unique visitors, so the shift may be driven by increased visit frequency among workers with shorter, simpler commutes rather than a change in where employees live overall. Still, the pattern is telling: Workers with shorter commutes appear more likely to generate repeat in-person visits, while longer and more complex commutes correspond with fewer trips. Over time, this dynamic could shape office leasing decisions, residential demand near employment centers – whether in urban cores or in nearby suburbs – and the geography of the workforce.
Taken together, the data paints a clear picture of the modern return-to-office landscape. Attendance is rising, but behavior is no longer driven by mandates alone. Instead, workers are making rational, convenience-based decisions about when coming in is worth the effort.
For cities, the implication is straightforward: Ease of access matters. Investments in transit reliability, last-mile connectivity, and housing near employment centers can all play a meaningful role in shaping how consistently people show up. For employers, too, the lesson is that the path back to the office runs through convenience, not just compulsion, as attendance gains are increasingly driven by how effectively organizations reduce friction and increase the perceived value of being on-site.
1. AI is raising the bar for physical retail as shoppers arrive more informed, more intentional, and less tolerant of friction – though the impact varies by category and format.
2. As discovery shifts upstream, stores increasingly serve as confirmation rather than discovery points where shoppers validate decisions through hands-on experience and expert guidance.
3. AI-based tools can improve in-store performance by removing operational friction – shortening trips in efficiency-led formats and supporting deeper engagement in experience-led ones.
4. By embedding expertise directly into frontline workflows, AI helps retailers deliver consistent, high-quality service despite high turnover and limited training windows.
5. AI enables precise, location-specific marketing and execution, allowing retailers of any size to align assortments, staffing, and messaging with real local demand.
6. Retailers can also use AI to manage their store fleets with greater discipline and understand where to expand, where to avoid cannibalization, and where to rightsize based on observed demand rather than static assumptions.
7. AI is not a universal lever in physical retail; its value depends on the store format, and in discovery-driven models it should support operations behind the scenes rather than reshape the customer experience.
Physical retail has faced repeated claims of obsolescence, from the rise of e-commerce to the shock of COVID. Each time, analysts predicted a structural decline in brick-and-mortar. And each time, physical retail adapted.
AI has triggered a similar round of predictions. Much of the current discussion frames retail’s future as a binary outcome: either stores become heavily automated, or e-commerce becomes so optimized that physical locations lose relevance altogether.
But past disruptions point in a different direction. E-commerce changed how physical retail operated by raising expectations for omnichannel integration, speed, and clarity of purpose. Retailers that adjusted store formats, merchandising, and operations accordingly went on to drive sustained growth.
AI likely represents another inflection point for physical retail. As shoppers arrive with more information, clearer intent, and even less tolerance for friction than in the age of "old-fashioned" e-commerce, physical stores will remain – but the standards they are held to continue to rise.
This report presents four ways retailers are using AI to get – and stay – ahead as physical retail adapts to this next wave of disruption.
E-commerce moved discovery earlier in the shopping journey. Instead of beginning the process in-store, many shoppers now arrive at brick-and-mortar locations after having deeply researched products, comparing options, and narrowing choices online – entering the store to validate rather than initiate their purchasing decision.
AI-powered shopping accelerates this pattern. Conversational assistants, recommendation engines, and AI-driven discovery across search and social reduce the time and effort required to evaluate options – and this shift is changing consumers' expectations around the in-store experience.
Apple shows what it looks like when a physical store is built for well-informed shoppers. Given the prevalence of AI-powered search and assistants in high-consideration categories like consumer electronics, Apple customers likely arrive at the Apple Store with more preferences already shaped by AI-assisted research than other retail categories.
Apple Stores were designed for this kind of customer long before AI became widespread. The layout puts working products directly in customers’ hands, merchandising emphasizes live use over promotional signage, and associates are trained to answer detailed technical questions rather than walk shoppers through basic options.
That alignment is showing up in store behavior. Even as AI-powered shopping expands, Apple Stores continue to see rising foot traffic and longer visits thanks to the store's specific and curated role in the customer journey – a place where customers confirm decisions through hands-on experience and expert guidance.
Some applications of AI extend trends that e-commerce has already introduced. Others address operational challenges that previously required manual coordination or tradeoffs.
AI can reduce friction and make store visits more predictable by improving staffing allocation, reducing checkout delays, optimizing inventory placement, and managing traffic flow. These changes reduce friction without altering the visible customer experience.
Sam's Club offers a clear, recent example of AI solving a specific in-store bottleneck. For years, customers completed checkout only to face a second line at the exit, where an employee manually scanned paper receipts and spot-checked carts.
In early 2024, Sam’s Club introduced computer vision-powered exit gates, allowing customers to exit the store without stopping as AI algorithms instantly captured images of the items in their carts and matched them against digital purchase data. Employees previously tasked with receipt checks could now shift their focus to member assistance and in-store support.
The impact was measurable. Sam’s Club reported that customers now exit stores 23% faster than under manual receipt checks, a result confirmed by a sustained nationwide decline in average dwell time. During the same period, in-store traffic increased 3.3% year-over-year – demonstrating how removing friction with AI can deliver tangible gains.
AI optimizes stores for different outcomes. At Sam’s Club, it shortens visits by removing friction from task-driven trips. At Apple, upstream research leads to longer visits focused on testing, questions, and decision validation. In both cases, AI aligns store execution with shopper intent – prioritizing speed and throughput in efficiency-led formats and deeper engagement in experience-led ones.
Beyond shaping store roles and streamlining operations, AI can also address a long-standing challenge in physical retail: delivering consistent, high-quality expertise on the sales floor despite high turnover and seasonal staffing. In the past, retailers relied on heavy training investments that often failed to pay off. AI can now embed that expertise directly into frontline workflows, allowing associates to deliver confident, informed service regardless of tenure and strengthening the in-store experience at scale.
In May 2025, Lowe’s rolled out a major in-store AI enhancement called Mylow Companion, an AI-powered assistant that equips frontline staff with real-time, expert support on product details, home improvement projects, inventory, and customer questions.
Mylow Companion is embedded directly into associates’ handheld devices, delivering instant guidance through natural, conversational interactions, including voice-to-text. This enables even newly hired employees to provide confident, expert-level advice from day one, while helping experienced associates upsell and cross-sell more effectively. The tool complements Mylow, a customer-facing AI advisor launched the same year to help shoppers plan projects and discover the right products, leading to increased customer satisfaction.
While AI alone cannot solve demand challenges—especially amid macroeconomic pressure on large-ticket discretionary spending—early signals suggest it may still play a meaningful role. Location analytics indicate narrowing year-over-year visit gaps at Lowe’s post-deployment, pointing to a potentially improved in-store experience. And Home Depot’s recent announcement of agentic AI tools developed with Google Cloud suggests that these technologies are becoming table stakes in this category.
As more retailers roll out similar capabilities, those that moved earlier are better positioned to help set the bar – and benefit as the market adapts.
Beyond improving the in-store experience, AI also gives retailers a powerful way to drive foot traffic through precision marketing. By processing large volumes of behavioral, location, and timing data, AI can help retailers decide who to reach, when to engage them, where to activate, and what message or assortment will resonate – shifting marketing from broad seasonal pushes to campaigns grounded in local demand.
Target offers an early example of this approach before AI became widespread. Stores near college campuses have long tailored assortments and messaging around the academic calendar, especially during the back-to-school season. In August, these locations emphasize dorm essentials, compact storage, bedding, tech accessories, and affordable décor – supported by campaigns aimed at students and parents preparing for move-in. That localized approach has been effective in driving in-store traffic to Target stores near college campuses, with these venues seeing consistent visit spikes every August and outperforming the national average across multiple back-to-school seasons from 2023 to 2025.
AI makes local execution repeatable at scale. By analyzing visit patterns, past performance, and timing signals across thousands of locations, retailers can decide which products to promote, how to staff stores, and when to run campaigns at each location. Marketing, merchandising, and store operations then act on the same demand signals instead of separate assumptions.
Crucially, AI makes this level of localization accessible to retailers of all sizes. What once required the resources and institutional knowledge of a big-box giant can now be achieved through precision marketing and demand forecasting tools, allowing brands to adapt each store’s messaging, assortment, and execution to the unique rhythms of its community.
Beyond improving performance at individual stores, AI can also give retailers a clearer view of how their entire store fleet is working – and where it should grow, contract, or change. By analyzing foot traffic patterns, trade areas, customer overlap, and visit frequency across locations, AI helps retailers identify which sites are truly reaching their target audiences and which are underperforming relative to local demand.
AI also plays a critical role in smarter expansion. Retailers can use it to identify markets and neighborhoods where demand is growing, customer overlap is low, and incremental visits are likely – reducing the risk of cannibalization when opening new stores. By modeling how shoppers move between existing locations, AI can flag when a proposed site will attract new customers versus simply shifting traffic from nearby stores, grounding expansion decisions in observed behavior rather than demographic proxies or intuition alone.
Equally important, AI helps retailers recognize when expansion no longer makes sense. By tracking total fleet traffic, visit growth, and trade-area saturation, retailers can assess whether new stores are adding net demand or diluting performance. The same signals can identify locations where demand has structurally declined, informing rightsizing decisions and store closures. In this way, AI supports a more disciplined approach to physical retail – one that treats the store fleet as a dynamic system to be optimized over time, rather than a footprint that only grows.
The impact of AI on physical retail will vary significantly by category and format. Not every successful store experience is built around efficiency, prediction, or pre-qualification. Retailers with clearly differentiated offline value don’t necessarily benefit from forcing AI into customer-facing experiences that dilute what makes their stores work.
“Treasure hunt” formats are a clear example. Off-price retailers like TJ Maxx, Marshalls, Ross, and Burlington continue to drive strong traffic by offering unpredictability, scarcity, and discovery that cannot be replicated – or meaningfully enhanced – through AI-driven search or recommendation. The appeal lies precisely in not knowing what you’ll find. For these retailers, heavy investment in AI-led personalization or pre-shopping guidance risks undermining the core experience rather than improving it.
Similar dynamics apply in other categories. Independent boutiques, vintage stores, resale shops, and certain specialty retailers succeed by offering curation, serendipity, and human taste rather than optimization. In these cases, AI may still play a role behind the scenes – supporting inventory planning, pricing, or site selection – but it should not reshape the customer-facing experience. AI is most valuable when it reinforces a retailer’s existing value proposition. Formats built around discovery, surprise, or experiential browsing should protect those strengths, even as other parts of the retail landscape move toward greater efficiency and intent-driven shopping.
AI is forcing physical retail to evolve with intention. By creating a supportive environment for customers who arrive with made-up minds, removing friction inside the store, offering the best in-store services, and orchestrating demand with greater precision, retailers are adapting to the new world standards set by AI. All five strategies focus on aligning stores with shopper intent – what customers want, how the store supports it, and when the interaction happens.
The retailers that win in this next era won’t be the ones that use AI to simply automate what already exists. They’ll be the ones that use it to sharpen the role of physical retail – turning stores into places that help shoppers validate decisions, deliver value beyond convenience, and show up at exactly the right moment in a customer’s journey.
In the age of AI, physical retail wins by becoming more intentional – designed around informed shoppers, optimized for the right outcome in each format, and activated at moments when demand is real.
