What could be a more telling indicator of who we are than where we spend our time? Digital marketing has been built around data about who we are in the digital world. However, marketers have the potential to understand audiences in real life as data about the physical movements of consumers and populations becomes accessible. Location data could become the lynchpin of marketing as a whole, in much the same way that website analytics occupied the central position for web-based marketing.

There's a ways to go before that, though. For location data to become a core feature of the marketing stack, vendors will need to overcome multiple challenges spanning technical, organizational and possibly even regulatory. The shifting privacy landscape makes for the most substantial change to the category. Tightening privacy regulations in Europe, mixed with a growing awareness of the amount of personal data collected by tech providers, could make it difficult for mobile location firms to collect data the way they always have.

The 451 Take

We've come a long way from geofencing. The initial application of location data was little more than an extension of mobile advertising. The basic idea was to show mobile ads to people within a certain proximity to a particular location. This application of mobile data has limitations. Yet vendors building this technology have since learned to harness location data more efficiently and expanded into new applications in advertising and marketing, including behavioral advertising, measurement and customer intelligence. The immediate challenges faced by location suppliers in the space is to find the ideal application to bring this data to market and to find ways to differentiate products that largely draw data from the same sources.

Although there's a growing variety of applications for location data, most remain rooted in advertising. While selling ads enables companies to scale, any vendor seeking sustainable growth would benefit from a direct, contractual relationship with the marketing department. Advertising applications – media sales and measurement data – offer the simplest way to land initial business because they are both the most well-understood apps and the ones with the most demonstrable ROI.

A survey of marketers shows that location data is poised to become a permanent part of the advertising stack. While only 25% of marketers told us they were using location data to measure the impact of their ad campaigns on store visits, those that do so placed an inordinate importance on such data as 57% of them said it was the most important part of their measurement stack.

A common sales tactic for many vendors in the space is to start a relationship with a marketer through ad-related offerings in hopes that additional applications can spread throughout the enterprise. While there are myriad interesting uses for location data, these broader sales are challenging. Take customer intelligence, for instance. Marketers can intuitively see the value of knowing more about their competitors' customers and where they overlap with their own. Yet unlike advertising, planning and executing other kinds of marketing campaigns employing location data isn't a well-trod area of practice today and many marketers have trouble assessing the value of such data.

As the applications change, so too has the environment for data privacy, which could weigh on these technologies in coming years, as we detailed in a previous report. The most certain of these is the imminent implementation of the European Union's General Data Protection Regulation, or GDPR, as it's commonly known. GDPR has strict regulations around who can collect data and what permissions you need from consumers that could make it challenging for data brokers to secure those permissions as few of them have a direct relationship with their customers. In the US, there are few legal limits, but recent revelations about Facebook could well lead to a GDPR-style model in the future. For marketers in this space, they should be aware of how their supplier gathers data and how vulnerable it may be to losing parts of that supply.

That's not to say that privacy concerns will necessarily undermine this whole segment. 451 Research's most recent Voice of the Connected User Landscape (VoCUL) survey on the matter shows that people are willing to share their personal info, including location, in exchange for value. Age matters with the latest results from our VoCUL survey. It finds that 36% of respondents 18-34 are willing to share personal information for better rewards. However, that lowers to 19% for those over 55+. Additionally, 38% of respondents 18-34 want to receive personalized information (local offers, mall promotions, etc.) based on their immediate location, compared with 22% of those over 55.

Mobile location ad networks

The first application of location data was using it to deliver mobile ad networks. Earlier this decade, several startups cropped up with the idea to serve mobile ads based on the physical location of the phone. In the proverbial example, a person walking near a Starbucks would be served an ad for the coffee chain. Similarly, the ads could be served for competitive 'conquesting' (e.g., serving McDonald's ads to people in a Burger King).

Although these applications captured a share of mobile ad budgets, there were several challenges. First and foremost, such campaigns often lacked scale. Or, at a minimum, the need for scale to attract major advertisers provided a perverse incentive to harvest accurate location data. Most of these companies ran an ad network business model, meaning they were arbitraging mobile ad inventory and needed to sell more ads to grow the business. Many of the maps that were developed to power location advertising networks were built using grids, rather than outlining precise locations.

Moreover, they relied on app developers, publishers and other ad networks to deliver the latitude and longitude (lat/long) coordinates via ad exchanges. Not only is collecting accurate location data challenging for app developers and publishers with the best intentions, app developers also need to insert the appropriate SDKs and gather permissions to collect GPS data, which itself can often be inaccurate by hundreds of feet. Early in the mobile ad market, many sellers realized that adding lat/long data to an impression would fetch higher rates at auction, creating an incentive to incorporate any location data, including lat/long points generated from IP addresses and others that would tell an advertiser little more than the country a device was found in.

Sources of data

Although many location data providers still depend on data from the mobile advertising bid-stream to power their services, most have extended their sources of data to include partnerships with app developers to gather more accurate data. Data that comes directly from apps tends to be more accurate because the data is collected closer to the source.

That data can then be used directly to build consumer profiles and to serve as seed data to train models that can sift through and cleanse bid-stream data. Several location data providers are also app developers themselves. Foursquare and UberMedia both began life as app developers. As did Placed – its app was built for the purpose of tracking consumer location in exchange for rewards. NinthDecimal and Gravy Analytics were early in building out direct partnerships with app developers. More recently, Cuebiq and SafeGraph launched with models that exclusively make use of app partnerships.

Companies collecting data through app partnerships and, sometimes, their own apps divide along two lines: those seeking a comprehensive picture of consumer behavior and those looking for a panel, or representative sample. The majority of vendors in this space fall into the former bucket because audience-level targeting drives most digital ad campaigns. But there are a few such as Foursquare, Placed and SafeGraph that have deployed panels to get a read on populations, rather than individual-level movements. When executed correctly, these approaches carry less risk from a privacy standpoint, although they can't offer capabilities where individual-level data is required, such as certain types of ad targeting.

Developing applications

Selling mobile advertising continues to be a major application for most players in this space. GroundTruth, PlaceIQ, Near, UberMedia, Verve, Foursquare and others all continue to provide mobile campaign services (although it's worth noting that advertising wasn't necessarily the initial application for all of these firms). This is unlikely to change as many organizations need access to ad exchange data to build their consumer information capabilities and generate revenue.

Still, the types of mobile advertising these companies sell has shifted. While geofencing remains a notable application, employing historical location data to target audiences has become more prevalent. Although closely related to geofencing, this type of advertising targets audiences based on where they have been, rather than where they are at a given moment. For example, instead of reaching customers at an advertisers' location, these campaigns can be used to reengage infrequent visitors, find new customers or reward loyal ones. Rather than simple competitive conquesting, advertisers can gain a more nuanced understanding of how their customers and potential clients engage with competitive brands.

These sorts of campaigns would be difficult to execute without accurate mapping data. Many of these providers have enhanced their mapping data in recent years to include more precise boundaries of buildings, parking lots and other structures. To achieve more precise behavior targeting, vendors will need to extend their mapping data beyond brand locations and into other places that offer insight into consumer preferences – workplaces, churches, little league fields, and so on.

A natural extension for many advertising specialists is measurement. Rather than selling campaigns, vendors can sell their location data to advertisers via an audience data management platform. They can also sell advertisers the same data to measure the impact of their advertising campaigns by overlaying a campaign's target audience with store visitors. Or measure changes in foot traffic as a campaign unfolds. NinthDecimal, PlaceIQ, Foursquare, UberMedia, Gravy, 4INFO and Placed (acquired by Snap last year) all play in this market.

Some of these companies – along with other new entrants – have also expanded into offering customer intelligence software that's powered by the underlying location intelligence. SaaS products from firms such as Cuebiq, Near (formerly known as AdNear) and UberMedia give marketers reporting and visualization tools to learn about their customers outside of an advertising context.

Most marketers that depend on visits to a physical location already have some understanding of the traffic to those locations. These applications of location data promise to layer intelligence about where else those consumers are going, giving them more insight into behaviors that occur beyond a marketers' four walls. Location intelligence deployed broadly for applications such as customer intelligence and competitive intelligence is among the most nascent applications of such data. Vendors such as Cuebiq, Foursquare, Near and UberMedia deliver customer intelligence through reporting and visualization dashboards, powered by their location tech and data, and sold as a SaaS license.
Scott Denne
Senior Analyst

Scott Denne is a Senior Analyst with 451 Research, where he helps direct the firm's coverage of technology mergers and acquisitions. He also contributes to 451 Research's Customer Experience & Commerce Channel with coverage of the advertising technology industry.

Sheryl Kingstone
Research Vice President & General Manager - VOCUL

Sheryl Kingstone leads 451 Research’s coverage for Customer Experience & Commerce, which covers the many aspects of how customer experience is a catalyst for digital transformation. She oversees the company’s coverage of a variety of customer experience software markets spanning ad tech, marketing, sales, commerce and service.

Keith Dawson
Principal Analyst, Customer Experience & Commerce

Keith Dawson is a principal analyst in 451 Research's Customer Experience & Commerce practice, primarily covering marketing technology. Keith has been covering the intersection of communications and enterprise software for 25 years, mainly looking at how to influence and optimize the customer experience.

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