Market Development Archives - Resource Centre

DICK’s Sporting Goods Strengthens Omnichannel through Brick and Mortar Planning

For data-savvy DICK’S Sporting Goods, an optimized network of brick-and-mortar stores remains critically important to customer engagement.

An April UBS report estimates that 80,000 US retail locations—or close to 10 percent of total stores in the country—will shutter by 2026, while e-commerce sales will rise to 27 percent of total retail purchases.

But those numbers don’t tell the whole story. Data-savvy retail companies are blending the two modes of shopping into an omnichannel strategy that can spark business advantage. Rather than framing online and physical sales as a zero-sum contest, leading executives recognize that stores and e-commerce can actually boost each other—a phenomenon known as the halo effect.

The largest sporting goods retailer in the US has taken this approach and emerged from the coronavirus pandemic stronger than ever. Bucking what some might think of as conventional wisdom in the era of one-click shopping, DICK’S Sporting Goods is adding to its network of brick-and-mortar stores to complement a growing online presence. Whether customers are browsing aisles of basketballs, lacrosse sticks, and running shoes, or swinging by for curbside pick-up of online orders, DICK’S strategically placed locations act as important customer engagement points in a thriving omnichannel network.

DICK’S Sporting Goods Expands a Thriving Retail Ecosystem

The company’s real estate division supports that network by relying on a geographic information system (GIS) to guide market development and retail optimisation. Using the business insight generated by GIS—known as location intelligence—the company’s real estate directors forecast customer demand in new trade areas and analyse the concentration and spacing of stores in developed markets.

For instance, the team cross-references census-based data on sporting goods expenditures against its own loyalty data on online sales to spot areas of high customer demand, signalling strong potential for a DICK’S store.

DICK’S analysts also used location intelligence to plan the geographic footprint of an unprecedented venture: an experiential concept store called House of Sport, opened this March in Victor, New York, with another to open in Knoxville, Tennessee in June. The sprawling New York location is the company’s biggest store ever at 100,000 square feet, equipped with an outdoor track, a putting green, and an indoor rock climbing wall.

Over the past year, the company’s holistic approach to brick-and-mortar stores and digital channels has been instrumental in serving customers. DICK’S e-commerce sales surpassed $2.8 billion in 2020, a 100 percent increase. The strongest growth came from in-store and curbside pickup, as BOPIS sales increased more than 350% over the previous year.

With more than 850 stores across the country, DICK’S Sporting Goods was well-positioned to cater to consumers replacing gym memberships with home exercise equipment due to pandemic restrictions, or jumping into outdoor sports to accommodate social distancing. Acting as mini-distribution centres, the stores helped the company fulfill online orders quickly and efficiently. Since these brick-and-mortar sites had been selected for their accessibility to consumers, they helped cut down on delivery times for online purchases.

The company was, in part, able to capitalize on such trends because it had already established a thriving network of physical stores in trade areas assessed annually by GIS analysts

“The heavy lift of data here is massive,” says Jack Holden, a GIS specialist and market research analyst at DICK’S. “We’re trying to get the result right, trying to get the right site, and help people understand the data to inform very important decisions.”

Fact-Checking Assumptions with Location Intelligence

Five or so years ago, DICK’S analysts wondered whether the relationship between physical stores and online shopping might ultimately be a cannibalistic one.

“The traditional thinking then, mostly outside the organization, was that brick-and-mortar was going to be really hurt by e-commerce, and that we might not need as many stores,” says Bill Grassel, director of real estate market research and strategy at DICK’S Sporting Goods.

One of the benefits of location intelligence is that it checks assumptions against facts on the ground—and this particular assumption ended up being wrong. “A lot of the spatial analysis that we’ve been able to do has said [that] when we add new stores, we actually see our entire omnichannel sales go up,” Grassel says. “Unless we had been able to analyse those customer behaviours at that level, we might have assumed, if we open a store, we’re going to hurt our e-commerce sales and vice versa,” he continues. “But we really found more of a symbiotic relationship between the two.”

The Sporting Life

Those and other location-based assessments are created by a team of four analysts that Grassel oversees. As one of the company’s real estate directors, Grassel is responsible for shaping forecasts about whether the company should open a new site, which markets are becoming over-penetrated, and where new opportunities exist.

Those decisions are ultimately approved by a real estate board. When Grassel and his fellow directors need facts to inform the board’s plans, they ring up Jack Holden, a GIS analyst and evangelist who’s driven by the desire to put the best data in his colleagues’ hands, often via smart maps.

“I really enjoy looking at maps and what they’re able to tell us, and the different things people are seeing even when we’re looking at the same map,” Holden says. “Getting more and more people engaged with mapping is a goal of my position.”

Born in England, Holden grew up using maps with his father to chart hiking adventures across Europe. He went to school for geography and learned GIS, then got his first job at the oil and gas firm Perenco, using spatial analysis to study water intake levels in wells and ways to reduce the harmful effects of salt.

When he joined DICK’S Sporting Goods, headquartered just outside Pittsburgh, Pennsylvania, he was intrigued by the prospect of exploring a new sector, and found himself immersed in a different vocabulary and concepts unique to retail. “GIS was my foundation,” he says. “It’s the common ground that I take from one industry to another.”

His predecessor in the role at DICK’S, Todd Henry, introduced GIS as an enterprise technology and established the system’s analytical benefits. “He built the chapel; I’m maintaining and updating it and helping the team learn how to worship there,” Holden says. Part of that work involves fine-tuning the granularity of the data that real estate directors use to support decisions about store locations and market optimization. In the process, he often shows colleagues the next gear that GIS technology can achieve.

“One of the things I think is most valuable about having someone like Jack on the team is to really teach us not only how to use [GIS] day in and day out, but also what it’s capable of being used for,” says Kara Tirimacco, a market research senior analyst at DICK’S Sporting Goods who regularly presents location-based analysis to company executives.

Locating Latent Demand

After 72 years in business and with more than 850 stores, DICK’S’ retail expansion is gradual and intentional. Accordingly, much of the work that Holden and his colleagues do focuses on market optimization.

They create trade area maps that help reveal the cause of certain trends—like connecting a store’s poor performance to an overconcentration of DICK’S locations in that region.

“Without having that spatial dimension and being able to look at a market holistically, you might just say, well, this store doesn’t seem to be doing as well as it should,” Grassel says. “When you’re actually looking at it spatially, then you have this geographic component, and a lot of times that helps explain some of the profitability things we’re looking for.”

As market research analyst Richard Boyles, one of Holden’s colleagues, puts it, “You can’t map out LA in a CSV file.”

Mapping the Unexpected

In addition to guiding the expansion of the retail network, GIS-based insight also helps DICK’S respond to unexpected occurrences.

The onset of the COVID-19 pandemic was one such occurrence. The danger of the virus and the need to gather and share information quickly made maps and dashboards a natural fit.

“As devastating as this whole pandemic has been, opportunities arise out of trying to answer some questions about a very serious subject,” Holden says. In addition to directing colleagues to good sources of data on the pandemic and helping them create maps of their own, Holden produced dashboards showing where DICK’S stores were open, where stores were closed due to shutdowns, and the location of points of interest like testing sites. “We saw that come to life in a map,” Tirimacco says.

The use of GIS to chart COVID-19’s effects showed colleagues how location data could be used in analytics at DICK’S, Holden says. After map-based presentations, he and the team often field requests from coworkers asking if they can access the online GIS platform. “It’s neat to get more people involved and try and educate people a little bit in the geospatial world,” he says.

As markets recover, many consumers are anxious to get out of the house and engage in a little in-person retail therapy, making a fluid omnichannel approach a retail advantage. Thanks to its store-centered, location-smart strategy, DICK’S Sporting Goods will be ready with its doors open and its e-commerce channels thriving—serving customers however they choose to engage.

To learn more about the role of location intelligence in retail, explore these resources.

This article was originally published on the global edition of Wherenext

How Stores Can Thrive—By Learning from Failure

A new study suggests companies have as much to learn from store closures as they do from expansions, and location plays a compelling role.

When Netflix’s founders finally got a meeting with Blockbuster’s CEO and named their price, they were turned down and told the dot-com buzz was a passing fad.

Twenty years later, just a single Blockbuster store (in Bend, Oregon) remains of the network that once numbered more than 9,000, while streaming media pioneer Netflix sports a market capitalization of more than $240 billion.

It’s a cautionary tale of sudden technological change and fast-shifting consumer preferences—a reminder that in today’s unpredictable business climate, Davids and Goliaths can switch places faster than anyone might imagine. More and more, companies are turning to data analytics and tools like geospatial analysis to adapt before sweeping reversals of fortune take them by surprise.

Regional Transportation to Spark Regional Transformation

NAR is being pitched as a project that will spark needed changes in American society. It would help the US lighten its carbon footprint and mitigate future climate-related damage, proponents say, while providing inland transportation routes as an alternative to existing coastal corridors that could be imperiled by sea level rise.

Project planners also see a social equity angle to NAR. As large cities like New York and Boston have become more costly, the resultant housing crunch has pushed lower-income and middle-class workers to distant suburbs.

By expanding travel options throughout the region, NAR’s backers argue that families will gain more flexibility regarding where to live. For instance, a family could live on the NAR network, with two earners travelling in different directions to work, rather than being forced to choose a single metro area that may not offer ideal employment options.

This could have a profound effect on the regional economy and beyond—especially if North Atlantic Rail paves the way for other regional high-speed transit networks. For example, if NAR’s boosters are correct that businesses in the region could expand their trade areas as travel times decrease and more customers can reach them, it could change the calculus for retailers, commercial real estate brokers, and service firms planning locations and service territories.

Businesses can get a jump on these decisions by using GIS to visualize where changes are likely to occur. Combining demographic data with their CRM data, business planners can analyse how customer activity might change in areas newly served by NAR and other rail networks.

A Location-Smart Approach to Change

Large businesses in the Northeast are already struggling to understand how climate change will affect where their workforces will want to live—especially as NAR cities like Boston attempt to revitalize areas that will be impacted by climate-related issues in the coming years.

The COVID-19 pandemic and the switch to remote work have further complicated these decisions. Will tomorrow’s business leaders continue to embrace work-from-home practices or bring employees back to the office? Could NAR’s decentralization of the region provide companies and workers more flexibility—making it realistic to live farther away from the office while spending part of the workweek in the office?

Either way, as the climate crisis increases the need for large-scale solutions, projects like NAR are likely to set off changes in how people live, shop, and work. Location intelligence will help engineering and construction companies plan these major transportation projects—while helping retail and service businesses anticipate and accommodate the new customers those projects will create.

The Last Picture Show

Blockbuster is one of many indelible American brands that have disappeared from strip malls and city avenues: Borders, Radio Shack, Toys R Us, and others met a similar fate. Earlier this year, the US’s last remaining video rental chain, Family Video, closed its remaining stores after a long slump.

Retail executives and analysts typically focus on growth strategies and case studies of successful expansions when looking for lessons they can apply to their own business. But a research paper published last year in The Professional Geographer on Family Video’s decline suggests that business leaders have just as much to learn from retail networks that have contracted or failed.

The study’s authors concluded that site location and related factors can have a major influence on a business’s health and the viability of any given store. Their analysis found that occasionally overlooked external factors—local population density, neighbouring businesses, store size—can have a significant, surprising effect on whether a store stays open or is forced to close.

Increasingly, forward-thinking companies are incorporating a geographic information system (GIS) into their analyses to detect such patterns in location data that the naked eye and spreadsheets can miss. The business insight leveraged from GIS, known as location intelligence, can help corporate leaders gain competitive advantage, head off risk, and capitalize on opportunities.

Size—and Population—Matters

In the paper, Joseph Tokosh and Xuwei Chen of Northern Illinois University analysed data on Family Video closures to pinpoint underlying factors. The chain was founded in the Great Lakes region and expanded in rural and suburban areas where Blockbuster had less of a presence, reaching 700 locations across 19 states and Canada at its peak. At the time of the study, 537 stores remained open.

After studying elements like building size, population demographics, and proximity to other retailers, the authors came to three main conclusions. First, larger stores (on the order of 5,500 square feet) were more likely to fail than smaller ones. The specialized nature of the video-rental market, its simple product line, and the fact that the outlets didn’t anchor a market like a department store might, all favoured smaller stores seeing greater success.

Second, they found that the higher the density of population around the store, the more vulnerable the business was to failure. Denser populations tend to attract more shopping options, forcing a relatively small brand like Family Video to match prices and inventory with big-box stores like Walmart that also sell DVDs. Moreover, since sparsely populated rural areas often lack infrastructure for high-speed internet and the streaming media services it supports, those regions have typically performed well for brick-and-mortar video stores.

Lastly, the study concluded that the company a store keeps—its choice of cotenants and the status of neighbouring properties—was one of the biggest determinants of success. Nearby vacancies raised the likelihood of store closure. This finding dovetailed with data showing that stores in large plazas were more likely to shut down than stand-alone locations. Even a single vacancy can have an unwelcome effect, reducing the attractiveness of a shopping complex and triggering a domino-style chain of closures.

On the other hand, when Family Video locations had food or beverage outlets as cotenants, their likelihood of staying open increased. There’s an allure to pizza and movie nights that has endured well into the streaming era. When Family Video partnered with Marco’s Pizza, leasing space to the pizza chain in over 200 locations, the stores performed well: only 13 of those joint locations shuttered. Just as vacancies can pull a whole strip down, a popular restaurant can buoy the fortunes of the businesses around it.

Location Data-Driven Strategies

By giving the kind of data analysed in this study a visual context, GIS makes it possible to detect, evaluate, and even forecast trends before they impact a business’s bottom line. For a business numbering 4 locations or 4,000, a GIS analyst can produce smart maps showing data in a geographic context and pointing the way to responsive business strategies.

A small-scale business like Family Video facing the prospect of nearby vacancies could preemptively transition the site to operate as a dark store—closed to the public, but acting as a mini fulfilment centre to fill gaps in e-commerce and omnichannel retail.

Alternately, an e-sports or video game chain might build a market strategy around the correlation between smaller populations and lower reliance on internet-based entertainment, seeking out exurban and rural areas for its locations. Those same geographies might also appear on a smart map as opportunities for an internet service provider looking to break down the digital divide.

The insight that cotenants can boost commerce for adjoining businesses could point to valuable partnerships. A GIS analyst can create a map showing sales at each store in a retail network and revealing patterns connected to neighbouring businesses.

No one knows the future, as the Blockbuster and Netflix encounter amply demonstrates. But for those with tools like GIS who understand the value of seeking out hidden patterns, there are many prescient ones hidden in the data.

The Privacy Paradox: How Companies Gain Consumer Confidence in Data Sharing

A new study illuminates why companies must win consumer trust when it comes to data sharing—and where in the world trust is highest.

A paradox lies at the heart of consumer attitudes toward data sharing, according to a recent study containing important insights for business executives who shape data-driven strategies. In a survey of more than 10,000 respondents across 10 countries, HERE Technologies found consumers as anxious as ever about potential data abuses, with 53 percent reporting concern about sharing personal information digitally, up two points from 2018.

Yet more than two-thirds of consumers, or 70 percent, signalled a growing willingness to share location data, a metric that rose in every country surveyed except Germany. The openness to sharing is more common for services related to mobility, like ride-share apps, connected cars, and mapping platforms.

A close parsing of the study’s findings reveals a clear path forward for organizations that employ business and location intelligence to inform decision-making: companies stand a much better chance of accessing and deriving value from data when they are transparent, trusted, and demonstrate benefit to the consumer.

With the usefulness of location data being well-established in finding and mastering new markets, companies in retail, insurance, banking, and other industries do stand to gain, but must allay customer worries about how their data is used.

Location Data Has Never Been More Important—or Sensitive

Concerns about data privacy have been top of mind in recent years. One cybersecurity report found that within just the first six months of 2019, over 3,800 breaches exposed access to more than 4.1 billion records. Massive data breaches like Yahoo’s hacked user accounts and Marriott’s compromised reservation system continue to capture headlines. Meanwhile, new regulatory regimes like the European’s Union’s General Data Protection Regulation and the California Consumer Privacy Act have made data privacy a political issue. In general, consumers are simply more aware of how coveted their data can be, with 48 percent agreeing that their data is valuable to many collectors, according to the HERE study.

These facts have prompted companies to more carefully address communication and transparency around the use of consumer location data. At the same time, the speed of the information economy has made location intelligence a linchpin of market planning and competitive advantage. As noted in a Forbes piece on the topic, “the McKinsey Global Institute indicate[s] that data-driven organizations are 23 times more likely to acquire customers, six times as likely to retain those customers, and 19 times as likely to be profitable as a result.”

Location data—gleaned from smartphones, social media, IoT-equipped devices like fitness trackers, even dating apps—can be immensely beneficial to companies planning growth strategies. Plotting out movement trends on maps over time, executives can create location intelligence that reveals where certain groups of consumers are now and, more significantly, where they’re likely to be in the future.

Myles Sutherland, founder of the consulting firm One Degree North, has coined a term for these moving masses of location data points: human weather. “Imagine being able to track the patterns and impact of human activity like a meteorologist tracks weather fronts,” wrote business development strategist Jim Young in an article on the topic. This kind of insight could be invaluable to a retailer assessing the foot and car traffic near potential new sites, a restaurant chain determining whether to add a new late-night menu, or a real estate developer looking to acquire buildings in the next hip neighborhood. The powerful ways companies can leverage this kind of data underscores why organizations must assure consumers that their information is not being misused.

How Attitudes toward Data Use Are Shifting

Trends in data sharing vary by region—a notable fact for companies with an international presence. The HERE study found that data sharing was highest in China, with 90 percent willing to share, followed by India, Brazil, and the UK. The United States, where many data-sharing apps have originated, actually landed in the middle of the pack, with 71 percent agreeing to share location data. Japan, Germany, and France reported the lowest levels of trust and frequency in data sharing. The biggest rise in sharing frequency occurred in Brazil, up seven points from 2018.

Still, despite consumer reservations, openness to sharing location data is fairly common across the board, according to the study. That willingness rose sharply when doing so was seen as necessary or working to the consumer’s benefit, with 75 percent of respondents more apt to share location data when it contributed to safety or security. Enabling a service, saving money, gaining financial rewards, saving time, or increasing convenience were among the other top motivations that led to greater consumer tolerance for opening up their data.

Not surprisingly, six out of 10 consumers were more likely to share data when the collector was well-known. And a full 79 percent reported being likely or very likely to allow navigation or mapping services to access their data. This helps explain why public transportation and ride-hailing services saw the greatest gains in consumer trust, as did car manufacturers, with more consumers linking their phones to their vehicles. In these cases, the consumer saw clear value in sharing data, and the collector was an established brand or company whose reputation assuaged privacy concerns.

For business executives, these findings signal a blueprint for creating a data-sharing understanding with consumers. By creating trust, emphasizing transparency, and showing how location data will play to the consumer’s advantage as well as the company’s, business leaders can use that data to accelerate growth and bring key customers along with them.

(Find out more about how companies use market and customer analysis to expand.)

This article was originally published in the global edition of WhereNext.

NextTech: Visualizing Consumer Traffic

Using a modern version of a centuries-old technique, planners can study anonymized IoT data to see patterns of human movement.

Unlike many of today’s business tools, the flow map originated in the 19th century, invented by a French civil engineer named Charles Minard who created what has become an iconic map of Napoleon’s 1812 incursion into Russia. In stark shapes and lines, it depicts where the French troops traveled and how many of them succumbed to battle, weather, and illness during the army’s advance and retreat.

Like most useful information tools, Minard’s map offers a wealth of insight at a glance. Now, busy executives are repurposing the medium of flow maps to explore decidedly lighter topics—including consumer habits and how to connect with customers.

What it shows is the human equivalent of tracking rainfall through a river system. As more people use a given road, the height of the spine on the map grows. Feeder streams connect to tributaries, which empty into arteries, which lead to a destination—in this case, a mall.

The destination could be any place. For example, a clicks-to-bricks retailer might examine several empty storefronts to see how much traffic each attracts at certain times of the day. Likewise, a corporate real estate planner might examine a new office park to see how traffic flows during rush hour, and where professionals go for lunch.

This brand of location intelligence drives capital investments and strategic decisions across the business world today. [For a look at how leading companies like Apple use location intelligence, read this e-Book.]

Drawing Data from the IoT

The data comes from the Internet of Things (IoT)—connected devices like cars, phones, and fitness trackers. Instead of identifying individuals, IoT data is anonymized to create a broad picture of where people move.

Powering this NextTech is a geographic information system (GIS), the software that understands where people are moving within geographic areas and connects that movement to points on a map.

Esri’s Jim Young calls this movement human weather. He wrote:

The marketing industry, particularly out-of-home (OOH) advertising, already benefits greatly from human weather data. But as Charles Minard proved more than a century ago, some pictures tell a story more readily than others. Placing human weather data on a modern-day flow map like the one in the animation reveals at a glance how people move through the built environment, and could spur a major advance for the OOH advertising industry.

The industry is already resurgent. Innovative firms like JC Decaux are employing digital tools to better connect advertisers with target audiences. Adding flow maps to that analysis could lead to more precision in terms of where to place advertising and what rates to charge for each location.

For advertisers, retailers, and real estate planners, it’s a modern twist on a medium that first proved its value two centuries ago.