Pokémon GO and Monetizing the Massive Value of Geolocation Data

by   |   September 1, 2016 5:30 am   |   0 Comments

Anshu Prasad, left, and Arpita Ghosal

Anshu Prasad, left, and Arpita Ghosal

Our abilities to collect and utilize geolocation data are evolving rapidly. Put simply, geolocation adds the “where” to the Internet of Things. Vast amounts of data are being generated from billions of location-aware sensors and Internet-enabled devices, including smartphones and tablets. This flood of new data, particularly when combined with other forms of big data, provides valuable information that can be intelligently mined to deduce patterns and uncover new insights.

This immense potential is driving the development of new location-enabled products and services to enhance customer experiences and create new business opportunities.

Geolocation-enabled tools are just a part of an emerging ecosystem of advanced analytics tools. Fascinating new use cases are emerging regularly, catalyzing business innovation and prompting the development of new ways to monetize the value they generate. However, there are striking gaps between leaders and laggards in their ability to capture this value. Traditional companies operating on corporate timelines are typically unable to manage the pace of change required, let alone exploit or monetize it to maximum advantage.

Pokémon GO

Nowhere is this more evident than in the recent Pokémon GO phenomenon. This GPS-powered smartphone game uses augmented reality to blend the real and the digital worlds, and tasks players to locate creatures and treasures as they navigate their physical neighborhoods. Perhaps because of its massive popularity and unprecedented adoption rate – within the first week of launch, Pokémon GO had more daily users than Twitter and received more tweets than Brexit – the business world has been slow to appreciate its monetization value.

One key aspect to appreciate is the network effect as ecosystem players beyond Niantic (the game developer) and Nintendo (the company with ownership rights to the characters) capture value from Pokémon GO’s runaway success. Of course, Niantic is earning revenues from in-app purchases and Nintendo from licensing and collaboration fees. To underscore the excitement the game has generated, Nintendo reported that $7.5 billion had been added to its market capitalization within a few days of the game’s launch.

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But it’s important to remember that Apple and Google also are generating revenues from their in-app marketing and sales as users continue to play the game. Retail locations, bars, and restaurants are trying to partner with Niantic to become “real-life locations” in the game and drive customer traffic to their businesses. There are also indirect effects being reported, with some players calling the game a disguised fitness app and claiming to lose as much as five pounds per week from the additional walking. Add to this the potential for game developers such as Niantic to open up new revenue streams through sales of their aggregated geolocation data to third parties interested in personalized marketing, and value creation possibilities expand considerably across the broader ecosystem.

Apple’s in-app sales model provides another example to appreciate the interdependence and reciprocity that benefits both Apple and broader ecosystem participants. In-app sales drive revenues for partners by providing access to Apple’s loyal customer base and a consistent user experience. In turn, Apple benefits from ecosystem partners providing its users a unique and ever expanding assortment of books, games, music, media, and storage services.

Companies looking to capture value from geolocation data should consider these examples and look for data sources and monetization opportunities beyond those that directly benefit their enterprise. These may range from indoor and outdoor precision marketing solutions to location-based initiatives in the healthcare domain. Automotive sensor data can help manufacturers accelerate product design, improve vehicle performance, and enhance driver safety. Their dealer networks can use this same data to better target customers needing preventive maintenance or other services to enhance retention and build customer loyalty. Whether we consider the geolocation data alone or its combination with supplemental data, the potential for companies to use this data to better engage customers is virtually limitless.

Geolocation Data Challenges

However, as with most rapidly growing technologies, and big data more broadly, effective use of geolocation data requires managing several risks and consistent challenges – namely capturing, cleansing, integrating, and storing huge volumes of complex data. Though the technology to capture and store vast amounts of data has grown rapidly over the past few years, ensuring data quality, especially in a real-time environment, remains a key challenge. Most organizations also need to develop the advanced data science capabilities required to analyze, visualize, and use geolocation insights. They also often struggle with how best to embed these insights into their strategic and operations decision-making processes.

Using geolocation data also poses some specific additional challenges. Privacy and security concerns associated with the capture, storage, and use of location data are concerns for companies, regulators, and users alike. Incidents already have been reported in which criminals have used geolocation data to lure victims to unsecure locations. Regulators and advocacy organizations have cautioned parents against allowing children to play games such as Pokémon GO unsupervised. Others have highlighted the extensive access and right of use to geolocation and other data that users sometimes unwittingly give app developers such as Niantic when accepting broad user-permission agreements as a condition to accessing the app. And corporate IT departments fight an unending battle to limit exposure of their networks to data theft and other cybercrime by restricting employees from using corporate credentials to log in to apps and social platforms.

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Much like the technology landscape, perspectives on who should be held accountable for protecting the privacy and security of geolocation data are rapidly evolving. When data are aggregated from multiple third-party sources, ultimate accountability for security and data privacy becomes harder to determine. Companies must understand who owns the source data and whether users have provided affirmative opt-in authorization for its use. It’s also important to understand where direct consent may not be required – for example, an asset owner using telematics to track the location of commercial vehicles without direct consent from the driver – and to establish protocols accordingly.

Companies looking to exploit geolocation data also need to stay informed about emerging regulations, which often differ by country. For example, the EU recently approved new rules on personal data protection, including usage of geolocation data. U.S. lawmakers increasingly are introducing legislation intended to address privacy issues associated with the collection, use, and disclosure of geolocation information. Awareness of and compliance with multiple regulatory regimes likely will remain a necessity for companies exploring global uses for geolocation data.

But even with the many challenges, the potential value to be unlocked from geolocation data means it is here to stay. And, given the innovation and pace at which new use cases are emerging, anticipating a diverse ecosystem with interactions between developers, data aggregators, data originators, regulators, and users will prepare new market entrants for the landscape they will need to navigate. Innovators will continue to invest in new data sources, analytics capabilities, talent, and processes to capture new business value. Regulators will play an increasingly important role in setting and monitoring data standards and guidelines. The various stakeholders will need to demonstrate a commitment to uphold privacy and security standards to engender trust among the other ecosystem players. Ultimately, individuals will need to be better informed about how their choices and actions will shape the development of the next generation of innovations enabled by geolocation data.

Anshu Prasad is a partner with A.T. Kearney and leads the firm’s global Analytics Practice. He is based in New York and can be reached at anshu.prasad@atkearney.com.

Arpita Ghosal is a consultant with A.T. Kearney Procurement and Analytic Solutions. She is based in Gurgaon, India.

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