Presented by Foursquare


For two years now, we have been waiting for things to return to “normal.” When can we grab coffee with friends? When can employees return to the office? When will customers return to stores?  The reality is that the pandemic has upended everything, from how people buy to what they are purchasing. What’s more, the old consumer model and trends that businesses have relied on are obsolete. At least for now.  Despite all the changes in consumer behavior, one thing is clear: we are seeing the unification of digital and physical emerging as a key trend for 2022.

Location is shifting from just an add-on feature to a necessity, and businesses are learning that it’s essential to build meaningful bridges between digital spaces and physical places, in a way that protects people’s privacy. In fact, 95% of executives say that geospatial data is important to achieve desired business results today, and 91% say that it will be even more essential in the next three to five years, according to a recent study from BCG.

There are a few reasons for this shift, says Ankit Patel, SVP of Engineering at Foursquare. First is simply that people are heading outside.

“Coming out of the pandemic, we’re seeing an explosion of people wanting to engage with the real world,” he says. “The foot traffic patterns and places where people frequented changed drastically at the beginning of the pandemic, and they are changing just as drastically now. Businesses need to understand their customers’ changing needs.”  For example,  return-to-office policies, supply chain issues, and rising gas prices are all dramatically influencing the places people go.

New consumer behaviors mean companies need to rethink the very products they create and services they provide. This includes how they’re staffing, outsourcing, and even the customers they are targeting.

Businesses need to be able to meet customers where they are, making location data an extremely valuable resource. The line between the digital and physical world is continuing to blur, with consumers interacting in both spaces seamlessly and necessitating companies to do the same as well.

The power of location data for decision-making

From a business standpoint, location intelligence presents opportunities in a number of different areas.

Quantitative investment models. Savvy investors leverage alternative data sets to help guide their strategies. Foot traffic can serve as a powerful signal as to which companies are either declining or surging in popularity. By adding that visitation data into their models, investors can forecast trends sooner and outperform the market.

Demand forecasting and supply chain optimizations. Businesses typically plan their inventory and forecast demand based on historical sales, sometimes incorporating external data sets like weather data or survey data.  By incorporating foot traffic data into their models, businesses can better identify, capitalize on, and predict  trends, such as the types of stores people are visiting and the peak times when they are shopping — thereby improving the efficiency of their models and reducing waste. Armed with real-world data, businesses can ensure they have the right products that people want in the right locations.

In-store shopping experiences. Retailers are increasingly using location technology to create better shopping experiences, from helping people find a store nearby,  to optimizing the store’s layout so that people can find the products they want when they arrive. Location technology serves as a powerful tool for retailers to stay ahead of ecommerce competitors, and to compliment their own ecommerce offerings.

Site selection. Location data has become indispensable both for commercial real estate, and for brands with brick-and-mortar presence looking to expand their footprints. According to a recent study, 60% of commercial real estate professionals report they struggle to make timely investment decisions to keep up with shifting market trends. Up to 58% admit they still rely on outdated or static data and tools to make business decisions.

For this reason, businesses are increasingly turning to location intelligence to make the right decisions about where to invest in real estate, taking into account movement patterns, changes in neighborhood landscapes and more.  In fact, the same study showed that 92% of commercial real estate executives expect their spending on location technology to increase in the next two years.  Using granular and timely insights to inform real estate strategies has become even more critical since the onset of the pandemic, as today’s business leaders are also facing decisions about whether — and where — to invest in office space.

Location data and advertising

For businesses trying to maximize the ROI of their advertising spend (which is all of them), cost per click is a standard metric — but not every business is designed for online conversions. Instead, many advertisers are looking to drive people into physical stores. Or they may be looking to influence more complex behaviors such as buy-online-pickup-in-store, order ahead, and click-to-collect.

Accurate, timely insights based on foot traffic data can help marketers understand the entire customer journey — how customers are interacting with their business, and more generally with the world around them. When businesses can accurately quantify the impact of their advertising on both online and offline behaviors, they can better optimize strategies in real-time to maximize their return on investment.

“We’ve seen that advertisers who don’t use location technology understand only half of their customers’ journey,” Patel says. “Unable to bridge their online and physical presence, these companies are leaving essential money on the table.”

In action: Improving user experiences with location

“In addition to driving smarter decisions, businesses want to incorporate location technology in order to power better experiences for their end users,” says Patel. “Today’s consumers expect personalization. With the help of our technology, product managers and developers can solve for that need.”

One example of this is Nextdoor, which helps users explore their neighborhood and engage with their community. The company uses Foursquare’s point-of-interest (POI) data to improve global business data coverage and quality, enabling them to surface local recommendations for users along with relevant attributes (such as business hours) in its onboarding and discovery experiences. POI data also helps Nextdoor with lead generation, boosting the number of local businesses that officially claim their own listings within the app.

Foursquare also has a partnership with Doordash, providing POI data for the ‘Request a Restaurant’ feature, which lets Doordash users request a recently opened neighborhood restaurant to be added to Doordash’s pick-up and delivery service. This feature has generated a new data stream for their team, helping them understand where their users are requesting certain cuisines, the trending types of restaurants across markets, and which cuisines are surging or declining in popularity in a granular way to inform recommendation algorithms. Fresh POI data with rich context cues means businesses can better understand their users, and tailor more meaningful experiences accordingly.

Big data and beyond

Big data is still a problem, despite the fact that we’ve been talking about it for years. Companies are grappling with how to store, process, and visualize petabyte-scale data, or billions of points of data. However,  companies aren’t actioning on some of their most valuable data — including location data. Even if they are, sometimes it’s hard to know, from all the data, how to make the right business decision. How do you get a good signal, distinguish correlation and causation, and make sense of how the pieces on the board are moving?

“The volume of data being produced and collected is skyrocketing, and it’s becoming increasingly difficult to understand what information is relevant and how to use all of this data in a meaningful way,” Patel says. “Investing in data science will be key. Using sophisticated algorithms and models, data scientists can extract knowledge and uncover insights to drive real, impactful business decisions.”

Looking at 2022 and beyond, businesses will need to expand in-house data science teams and integrate more advanced  third-party solutions, such as Foursquare’s Unfolded platform. It’s a geospatial analytics and visualization tool that makes it easy for users to drag and drop large data sets, surface insights, and produce powerful visualizations. A game-changing tool within Unfolded is Hex Tiles, a new tiling system that enables users to process, unify, and analyze bigger volumes of geospatial data than previously possible. What’s more, this can now be done in a matter of minutes, all within a browser.

The goal with these types of  innovations is to empower Foursquare’s customers and partners to discover the rich insights from location data and build better, more personalized experiences for users. “As with all things, we’re in a state now where I think it will be almost irresponsible for companies not to unlock the massive potential of location data to drive better decision-making,” he says. “2022 is turning out to be a pivotal year, I believe, in location data. Something that was once a competitive advantage will soon be a competitive necessity. Businesses that don’t adapt will be left behind.”


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