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Article
Who Attends the Super Bowl?
Our latest white paper, Who’s in the Stands? An In-Depth Look at Arena and Stadium Visits, uses location intelligence tools to uncover the demographic and psychographic characteristics of sporting events attendees – including Super Bowl fans. Read on for a taste of our findings.
Ezra Carmel
Feb 9, 2023
3 minutes

Our latest white paper, Who’s in the Stands? An In-Depth Look at Arena and Stadium Visits, uses location intelligence tools to uncover the demographic and psychographic characteristics of sporting events attendees – including Super Bowl fans. Below is a taste of our findings.

Super Travel Plans

As the biggest game of the year, the Super Bowl usually brings a tourism boom to the host city. The heat map below depicts the origins of travelers to the past three Super Bowls (excluding Super Bowl LV in 2021 which was held under COVID restrictions). Year after year, the distribution of Super Bowl attendees is relatively similar to the country’s population distribution – which means, perhaps unsurprisingly,  that the most densely populated regions are well-represented at the game. 

Heatmap of Super Bowl Visitor Origins

But the data also reveals that many Super Bowl attendees travel from the regions where the competing teams are based, which indicates that die-hard fans are willing to make the trip to see their local team potentially win a championship. The map also shows that visitors from the Super Bowl’s host city and surrounding areas are heavily represented at the game, regardless of whether or not a local team is playing. It’s likely that a significant number of football fans who live nearby take advantage of the rare opportunity to see a Super Bowl close to home. 

Super Bowl LVI in 2022, for example, was played at SoFi Stadium in Los Angeles, CA between the Cincinnati Bengals and the Los Angeles Rams. The event was heavily visited by fans from Southern California as the game was not only being played by the LA Rams, but also at their home stadium in Inglewood, CA. A greater contingent than previous years was also in attendance from Cincinnati, OH and its surrounding areas.  

A Family Affair

Many fans travel to the Super Bowl from the same regions every year, with the host city and the contending teams’ hometowns also providing significant factions of attendees. But analyzing Super Bowl crowds throughout the years also reveals an important demographic shift taking place among those traveling to the Super Bowl – the growing number of family-oriented visitors. 

Since 2019, the True Trade Areas of the Super Bowl stadiums include increasingly greater shares of larger families. Last year’s Super Bowl LVI had an in-person audience that reflected a trade area in which 17.9% of residents came from families of five or more, up from 11.9% at the Super Bowl three years prior. Conversely, Super Bowl attendees in 2022 reflected a trade area in which 37.7% of residents were part of two-person households, a decrease from 47.8% in 2019. 

The increase in attendees from areas with larger families could reflect the NFL’s initiatives to make football a more family-friendly sport, including rule and equipment changes aimed at increasing player safety and supporting youth football clubs. The trend towards an increase in attendees from larger families may also inform decisions about products to promote as well as amenities that will contribute to a family-friendly experience on game day.

Brands invest heavily in ads that air during the Super Bowl. But with the right insights, stadium advertising platforms have tremendous potential to reach target audiences in-person at the big game. While a large audience is part of the equation, in order to achieve maximum impact, an in-depth understanding of visitors is critical.

Article
McDonald's: "Adult Happy Meal" Sets a High Bar for QSR Promotions
R.J. Hottovy
Oct 14, 2022
1 minute

Key McDonald's Metrics

While focus and streamlined operations are key to restaurant growth strategies, we also continue to see evidence of the impact of innovation and nostalgia in driving visits. McDonald’s has had success with its past celebrity meal collaborations with Travis Scott and J Balvin, with our data indicating a mid-to-high teens lift in visits compared to the weeks prior to the promotion. However, McDonald’s "Adult Happy Meal" collaboration with streetwear brand Cactus Plant Flea Market might be its most successful collaboration today, with data suggesting more than a 30% increase in in-store visitation trends compared to the weeks leading up to the promotion (below). We’ve discussed the impact of limited-time offers (LTO) in the QSR space earlier this year, but McDonald’s has set a new bar for the industry (beating out Taco Bell’s Mexican Pizza launch in May).

Although QSR chains saw more resilient visitation trends than other restaurant categories for much of 2022, the gap between the QSR, fast casual, and full-service restaurant chains had narrowed in September as lower-income consumers continue to face inflationary headwinds from menu price hikes across the QSR space while higher-end consumers continue to dine out. Nevertheless, the impact of McDonald’s adult happy meal promotion is evident in not only the massive spike in visitation trends for the full QSR sector last week (below). While not everyone may love these promotions, they can be an extremely effective way to drive visitation growth.

Placer.ai Series C - Why Placer Raised $100M
Noam Ben Zvi, co-founder and CEO, explains how Placer will use the Series C funds to ramp up the velocity of development.
Noam Ben-Zvi
Jan 25, 2022
9 minutes

We, the founding team, always loved data - ideating around it, engineering with it, understanding the world better with it. 

But what captivated us most was imagining data products that can be used by tens of thousands of businesses across the world.

Among all the ideas and visions we bounced around before starting the company, one stood out for its simplicity and potential impact - building a ‘Physical Market Intelligence Platform’ to provide everyone in the offline world (a.k.a the ‘real world’) with aggregate insights for decision-making. Or in layman’s terms, “a dashboard to get instant insights for any place to understand its audience, surroundings, and competition”.

In 2016, the Placer founding team gathered in a basement and spent a weekend sketching out a plan to turn this idea into a massive world-class data company. 

Why did we get so excited?

  1. We loved using insight tools like SimilarWeb and App Annie that were made for the digital world.
  2. A massive market - 80-90% of spend is offline and is not going anywhere, anytime soon. We did not believe in the ‘retail apocalypse’ narrative.
  3. An industry ‘flying blind’ - this immense offline world has suffered from a lack of information critical to its decision-making.
  4. Data is especially critical for the physical world. The famous Facebook motto “move fast and break things” (which we practice at Placer) does not work well in the physical world. Brick & mortar decisions are costly and irreversible. It also takes a LONG time to understand you’ve made a mistake.
  5. Market Research is aggregated data - no need for any personal identifiable information (PII). This means we could build a privacy-first company, without PII data challenges.
  6. It’s a hard problem - which presents the opportunity to build something special. And in hindsight it’s been 10x harder than we thought!

Whiteboarding without customers or tech debt is fun!!!

The more paper we stuck to that basement wall, the bigger the vision became! Everything is possible with the stroke of a pen… 

But very quickly, we hit some glaring challenges:

  • The platform had to be about answering key business questions. But to generate the BEST reports that do so, there are 100s of relevant datasets that we MUST aggregate
  • The retail ecosystem is DIVERSE - retailers, CRE, CPG, travel, hotels, billboards are all unique worlds in and of themselves. Can we build a platform that reflects this? 
  • And…growing up in a “digital bubble” - the founding team knew VERY LITTLE about the retail world, its major players and how they work.

The best way to approach a big challenge is breaking it down into smaller ones. So we worked hard to define Phase 1 - focusing on building a product that (1) was centered around the mobile location analytics dataset and (2) generated reports tailored for CRE and retail

5 years and 5 funding rounds later, we’re FINALLY feeling “pretty good” about Phase 1: we launched a world-class mobile analytics product that’s used by over 1,000 customers, and thousands more are using our free products

But it’s also been “frustrating”  - we were always strapped for cash and resources. We’re yet to integrate most of the datasets we need; key reports for certain verticals remain in the product pipeline; and in terms of usability and workflow features, we still have a lot to do in order to create a truly comprehensive platform (vs “read only” status insights tool).

That’s why the $100M Series C funding we just announced is so momentous for me and the rest of the Placer team. It finally removes the shackles and equips us with the tools and materials we need for Phase 2 - rapidly building the full Placer.ai Market Intelligence Platform.

So let’s dive into what that means…

How does it work?

A Physical Market Intelligence Platform is a big data puzzle. Piecing it together - in a nutshell - consists of four phases:

  1. The Ingredients - identifying and assembling the data.
  2. Ingestion - processing and aggregating that information.
  3. Delivery - making it presentable and accessible.
  4. Customizations - every vertical is seemingly interested in very similar data, but with a different lens. This requires nuanced packaging around information density, terminology, order of reports, and 3rd party data-sets.
The Placer.ai Market Intelligence Platform
The Placer.ai Market Intelligence Platform

Ingredients

A vast amount of interconnected data is required to create a truly accurate and complete picture of what’s going on at a location. This data falls into two broad categories:

  • Point of interest (POI) data offering information on places such as a grocery store, retail centers and wider areas.
  • Geospatial data such as impactful events in the area, traffic data and future development projects.

Now consider all things you see going on in the world and imagine how POI and geospatial data can capture and quantify them…

Here’s a snippet:

We track dozens of data categories and thousands of datasets and vendors in order to identify new data that can help answer our customers’ questions.

  • Our product team draws on our customers’ feedback and wider market research to identify and triage the datasets we need to answer the questions. 
  • Our BD team lines up commercial partnerships with the data providers.
  • Our data analysts and scientists carry out a lengthy quality assessment process, which includes testing the data’s relevance, accuracy, data trust compliance, coverage, compatibility, recency, accessibility and alternatives.

This is 50% of our work and is a huge data challenge - but also great fun!

Among the real world visibility datasets

Through partnerships and our App Marketplace, we’ve recently integrated online reviews, credit card data, demographics, vehicle traffic volume, crime figures and planned construction into our platform. And we have lots more datasets in our pipeline: retail sales, property sales, financial data, leasing comparisons and climate data to name just a few.

Vehicle Traffic Volume
Crime
Planned Construction

Ingestion

If the data are the ingredients, then ingestion is the cooking. This includes complex data science processes:

  • Anonymization - eliminating personal identifiable information
  • Normalization - adapting the data’s various fields to fit Placer’s data model
  • Cleansing - ensuring that the data is as accurate and complete as possible
  • Enrichment - adding existing data layers to the ingested data, or extrapolating information from it
  • Tagging - associating the data with relevant POIs, industry categories, and so on to create meaningful insights.

Tagging data to POIs is a massive task. Placer’s POI database contains millions of entities: a commercial real estate asset in a customer’s portfolio; stores of a retailer’s chain or that hold a CPG brand’s products; a billboard used for out-of-home advertising; a downtown area being regenerated by a municipality or business improvement district. We geofence each one so data can be tagged to it.

But a much greater complexity than the volume of data-POI matching is the fact that our data structure is mutable - it changes. Stores, restaurants, strip malls and other POIs open, close, merge and move. Our physical environment is constantly changing. One of our platform’s standout attributes is that it always reflects historical change.

In practice, this means that, for each POI change, we not only adjust our data tagging but also re-tag 5 years of historical data to ensure any historical comparisons are “like with like”. This is a huge investment of resources on the part of our data science, devops and engineering teams - exponentially increasing our data management burden.

Delivery

To complete the cooking metaphor, after selecting ingredients (datasets) and cooking them (data ingestion), we then lay out a buffet-style feast of solutions for our users:

Basic Reports and Insights

The most basic level of the platform is converting the data into real-world constructs that can be understood by industry professionals: tables, charts, maps and other graphics displaying cross shopping, trade areas (below), cannibalization, risk analysis, visit frequency and so on.  

Solutions 

A key tenet of the Market Intelligence Platform is the approach that insights like those are often not the answer to the questions that our customers are looking for. Rather, they are just part of the explanation behind the answer. That means providing a comprehensive suite of Solutions SUPPORTED by insights, not just a library of uncontextualized insights. 

An excellent example of this is Void Analysis. A key question for retail real estate is “who is my ideal tenant?” While our platform offered important insights (such as retailers’ average monthly foot traffic and cannibalization) for reaching an answer, landlords were doing a lot of legwork. The Void Analysis tool we released late last year enables CRE professionals to instantly analyze thousands of potential tenants through automatically generated reports that include ranking according to our unique Relative Fit Score. This significantly improves the speed and scope of a search for new tenants.

Void Analysis - Who is the best fit for my vacancy?

We are now working on the many additional solutions like Void Analysis in our development pipeline - sales forecasting, site selection for retail chains, market selection, market change reports, product optimization for CPG to name a few.

Placer REST API

To be truly useful, solutions must also be delivered in a way that fits various users’ workflows. A dashboard is a good start, but a full platform must offer a range of access points. This means data feeds, REST APIs, and other methods of programmatic access.

We’ll also add to that a rich layer of data exploration tools such as GIS, templates, graph builders, pivot table functionality and advanced entity search. This will provide users with maximum flexibility in how they explore and visualize our data.

The lion’s share of the work is still ahead of us here - more widgets, third party integrations, report generators, scheduled intelligence reports and alerts, and much more.

COVID-19 Economic Recovery Dashboard

The platform’s user interface must be fully customized to fit the needs of its different user types across verticals AND within companies (business users, data scientists, data analysts, third party users). An example of how we’ve begun to do this is a portfolio overview section for CRE analysts to rapidly scan properties’ performance metrics. Another is our COVID-19 Recovery Dashboard, particularly used by civic organizations to assess the impact of the pandemic on local economic areas.

The Anchor: Placer's CRE Executive Intelligence Report

As we presented “just data”, we quickly realized some customers were looking for humans to add a “research layer” and context around the data. So an analytical research team has become part of the product. They capture and present key market intelligence, respond to the latest industry trends and customer interests. “The Anchor”, a weekly CRE executive intelligence report launched last September, has now become an inbox staple for many of our customers.

Let’s build it!

To our current understanding, we’re just “5%” of the way to our Market Intelligence Platform vision. The remaining 95% will be built by scaling POI coverage, datasets, answering more questions and developing the other core components of the platform.

So our focus now is on ramping up the velocity of this development. And to do that, we need even more of the world’s best talent across the company. 

So, during 2022, we will use our new capital to double the size of our engineering team and significantly expand the data at our disposal. In parallel, we will also channel more resources to supporting our customers and contributing to industry understanding through our analytical research department and educational content. 

Placer.ai is committed to transforming the way real-world businesses make decisions. And we don’t want to waste any time going about it.

Placer.ai Raises $100M Series C At A $1B Valuation To Accelerate Growth and Product Development
We're happy to announce the closing of a $100M Series C funding round at a $1B valuation.
Ofir Lemel
Jan 12, 2022
2 minutes

Round led by Josh Buckley with participation from WndrCo, Lachy Groom, MMC Technology Ventures LLC, Fifth Wall Ventures and JBV Capital.

LOS ALTOS, CA (January 12, 2021)--Placer.ai, the leader in location analytics and foot traffic data, announced today the closing of a $100M Series C funding round at a $1B valuation. The round was led by Josh Buckley with participation from WndrCo, Lachy Groom, MMC Technology Ventures LLC, Fifth Wall Ventures, JBV Capital, and Array Ventures. The round also included the participation of leading commercial real estate investors and operators, including J.M. Schapiro (Continental Realty Corp), Eliot Bencuya and Jeff Karsh (Tryperion Partners), Daniel Klein (Klein Enterprises/Sundeck Capital), Majestic Realty, and others. The funding will be used to expand the company’s R&D capabilities to further increase the pace of innovation.

“Placer experienced significant growth during 2021 as a consensus formed across the market that accurate, reliable consumer behavior analytics is indispensable to brick and mortar decision-making,” said Noam Ben-Zvi, CEO and Co-Founder of Placer.ai. “Yet, location analytics is just the foundation for a much broader and more comprehensive vision. With this funding, we will accelerate the development of the Placer.ai platform, adding an unprecedented range of new data sets - such as vehicle traffic, planned construction, web traffic, purchase data, and much more - as well as more advanced solutions to empower any professional with a stake in the physical world to make better decisions, faster than ever before. ”

Since launching in November 2018, Placer.ai has been adopted by over 1,000 customers including industry leaders in commercial real estate and retail like JLL, Regency Centers, Taubman, Planet Fitness, BJ’s Wholesale Club, and Grocery Outlet. In the wake of COVID-driven upheaval, the company saw widespread adoption among a series of new categories, among them hedge funds and CPG leaders including Tyson Foods and Reckitt Benckiser.

"Placer provides instant, simple and actionable insights to questions we've been asking as operators for over 30 years. The pace of innovation, the unique trust that the company has developed, and the massive market demand all point to the magnitude and scale of what this team can achieve,” said Jeffrey Katzenberg, Founding Partner of WndrCo.

"We have long felt like the disruption Placer can bring is massive, but the market demand has far exceeded our initial expectations," said Josh Buckley. “We see a powerful opportunity to continue partnering with Placer to improve the way decisions are made in the physical world, fundamentally improving the way these businesses and organizations operate."

Try Placer.ai for free here.

About Placer.ai:
Placer.ai is the most advanced foot traffic analytics platform allowing anyone with a stake in the physical world to instantly generate insights into any property for a deeper understanding of the factors that drive success. Placer.ai is the first platform that fully empowers professionals in retail, commercial real estate, hospitality, economic development, and more to truly understand and maximize their offline activities. Find more information here: https://placer.ai/

Placer.ai Raises $50M Series B To Expand Location Analytics Capabilities
Placer.ai Raises $50M Series B To Expand Location Analytics Capabilities
Ofir Lemel
Apr 27, 2021
3 minutes

Round led by Josh Buckley, Todd Goldberg and Rahul Vohra with participation from Fifth Wall, JBV Capital, and Aleph VC

LOS ALTOS, CA (April 27, 2021) --Placer.ai, the leader in location analytics and foot traffic data, announced today the close of a $50M Series B funding round. The round was led by Josh Buckley, Todd Goldberg and Rahul Vohra, with participation from Fifth Wall, JBV Capital and Aleph VC. The funding will be used to grow the company’s R&D, expand sales and marketing teams, introduce additional reports and data sets, and grow the recently announced marketplace.

Since launching in November 2019, Placer.ai has been adopted by over 500 customers including industry leaders in Commercial Real Estate and Retail like  JLL, Brixmor, Taubman, Planet Fitness, and Dollar General. Yet, the recent upheaval caused by COVID led to widespread adoption among a series of new categories including Hedge Funds and CPG leaders.

“As a business deeply rooted in offline retail, we expected COVID to present a unique challenge. Yet, adoption actually increased as a result of our ability to introduce certainty into such an uncertain environment. The result has been a clearer and deeper understanding by the market of the absolute imperative of location data to improve the decision-making process,” said Placer.ai CEO and Co-Founder Noam Ben-Zvi.

“But our current offering is just the beginning, and we are fully focused on expanding the capabilities both through the development of a range of new features and tools, and the integration of a wide range of data sets through our marketplace. Placer.ai is rapidly becoming the market intelligence platform for anyone with a stake in the physical world.”

In the last year, Placer.ai continued to expand its presence in core markets like Commercial Real Estate, Retail, Municipal governments, and Hospitality while advancing into new segments like CPG and Hedge Funds. The result has been growing market adoption and an increasingly large and diverse reach. 

"Fifth Wall has some of the largest owners and operators of real estate as our limited partners and several were customers of Placer.ai, giving us a unique perspective on the company’s growth and potential. We saw firsthand the impact that the data is already having in reimagining the way business is done in retail and real estate broadly,” said Kevin Campos, Partner on the Retail & Consumer Investment team at Fifth Wall. “Yet, what’s even more exciting is that we’re still only seeing a piece of the puzzle and know that there are so many other sectors where the data can be applied. We’re thrilled to help grow and execute this vision alongside this exceptional team.”

"Placer allows businesses that operate offline to make data-driven decisions, fundamentally improving the way they operate. This is the same type of tooling that online businesses have used to grow, moving from hunches to definitive answers," said Josh Buckley. “I'm excited to be partnering with the company's next phase of growth and product development."

“Our journey with Placer.ai started at the very beginning as one of the company's first beta customers. Seeing the disruptive power of the product up close, the speed at which the company developed new features, and the tremendous traction they achieved in the marketplace led us to invest less than a year later and in every round since," said Sandy Sigal, CEO of NewMark Merrill Companies, an owner and developer of over 80 shopping centers and Chairman of BrightStreet Ventures, their venture capital arm. "Several years later, the customer growth, their ongoing product development, and the continuing value they have brought to our organization has only deepened our conviction and makes continued support a no-brainer for us."

Learn more about Placer.ai.

Reports
INSIDER
Report
5 Grocery Growth Drivers in 2026
How Expanded Supply, Trip Frequency, and Shopping Missions Are Reshaping Food Retail and Creating Multiple Paths to Growth
February 19, 2026

Key Takeaways

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.

What is Driving Grocery Growth in 2026?

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.

More Trips, More Formats, and a Shift Toward Mission-Driven Shopping

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. 

Scale Captures Demand – But Fragmented Trips Leave Room to Grow

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.

The Core Drivers of Grocery Growth in 2026

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.

1. Expanded Grocery Supply Is Fueling Growth While Traditional Grocery Stores Hold Their Lead 

Expanded Grocery Access Is Increasing Overall Category Engagement

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.

Traditional Grocery Stores Maintain a Stable Share of Visits Despite Growing Competition

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.

Mass Merchants Face Share Pressure as One-Stop Competition Expands

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. 

2. Low and Medium-Income Households Driving Larger Visit Gains 

Grocery Growth Is Shifting Toward Lower- and Middle-Income Trade Areas

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. 

Higher Food Costs Likely Driving More Frequent, Budget-Conscious Trips

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.

Necessity-Driven Shopping Is Powering Grocery Visit Growth

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.

3. Rise in Short Grocery Trips Driving Offline Grocery Gains

More Frequent, Shorter Grocery Trips

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. 

Omnichannel Grocery Shopping Fueling Short Trips to Physical Stores 

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. 

Grocery Shoppers Are Splitting Trips Across Multiple Retailers

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.

Different Trip Types, One Outcome: Continued Store Traffic Growth

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. 

4. Consolidation as a Growth Driver 

Large Chains Continue to Pull Ahead in Visit Share

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.

Scale Enables Broader Assortment, Stronger Value, and Better Execution

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.

5. Competition for "Share of List" Growing Grocery Visit Pie 

Both Long and Short Trips Are Driving 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.

Large and Small Chains Win by Competing for Different Shopping Missions

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. 

What These Trends Mean for Grocery Growth in 2026

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.

INSIDER
Report
Office Attendance Drivers in 2026: The New Rules of Showing Up
Dive into the data to learn how convenience-driven behaviors are impacting the office recovery – and how stakeholders from employers to office owners and local retailers can best adapt.
February 5, 2026

Key Takeaways:

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.

When Policy Isn’t Enough

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. 

Office Attendance Reaches a New High, But Momentum Slows

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. 

Weather, Workations, and a New Kind of Seasonality 

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 Quest for Convenience and the TGIF Workweek

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.

Commute Friction Shaping the Start 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. 

Proximity as a Key Attendance Driver

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.

Friction in Focus 

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.

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Five Ways Retailers Can Leverage AI Without Losing What Works
Read the report to learn how AI is changing store roles, operations, marketing, and fleet strategy – and how to apply it without undermining what already works.
January 29, 2026

Strategic Insights

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.

Another Inflection Point for Physical Retail?

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.

1. Driving Engagement & Conversion in Physical Retail

The Store as Confirmation Point

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’s Early Bet on the Informed Consumer Pays Off

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.

2. Creating Seamless In-Store Experiences 

AI Inside the Store

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.

Using AI to Remove Exit Friction at Sam’s Club

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.

Aligning AI with Store Purpose

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.

3. Scaling Expertise on the Sales Floor

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.

4. Reaching the Right Audience at the Right Moment

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.

5. Building Smarter Store Fleets With AI

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.

AI Won’t Matter Equally Across All Retail Formats

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.

Raising the Bar for Physical Retail

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.

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