Jessie Rudd, BI Consultant at PBT Group
In the space of just two weeks, an augmented reality game called Pokémon Go has managed to do the impossible. It has surpassed WhatsApp, Instagram and Snapchat and is on a par with Twitter for daily, active, ‘on the app’ users [1].
A game featuring Pokémon – originally a Game Boy video game that entranced children of all ages in the 90’s [2]. A game that has somehow, with the help of serious amounts of Big Data, rocketed itself into a whole new cross section of population.
Pokewhat?
If you are not a gamer, or addicted to your smart phone, then you are more than likely a little perplexed by the whole phenomenon. So then – what is Pokémon Go? To put it relatively simply, it is a location-based, augmented reality game for mobile devices developed by a company called Niantic for iOS and Android operating systems.
Augmented who?
Augmented reality is a technology that overlays a generated image on a user’s view of the ‘real’ world. This overlaying of images creates a composite view, viewable only via the application doing the overlay. So basically, you have a game that is overlaying itself on Google Maps, directing you to various sites to ‘capture’ various Pokémon. The brilliance behind this second generation phenomenon has been many years in the making.
It all comes down to Big Data.
In 2011 the company behind Pokémon Go, Niantic, released a game called Ingress. Ingress was one of the first of its kind. A fitness game, otherwise known as an exergame, Ingress relied heavily on the telematics that is present in all smart phones on the market nowadays. Telematics can be used to track body movement and reactions, which is exactly what Ingress did for Niantic.
This completely new and revolutionary method of collecting data, used the game to direct users and players to various ‘portals’ or sites which were initially extrapolated from geotagged photos on Google Earth. Players were also actively encouraged to submit more sites for consideration and to date, around 5 million sites have been approved for use [1]. Sites that were suggested, collated, collected and verified using serious advanced analytics and Big Data.
Sites that are approved for use by games like Pokémon Go, which, by the very nature of what they are, are going to give rise to a whole new mountain of Big Data. And not just any Big Data – relevant right now Big Data.
One of the biggest drawbacks and problems with Big Data is that it is more often than not, historical data, without context and relevant meaning. Not in this case. For the first time, on a scale that can truly be called big, Big Data is relevant – relevant and extremely powerful. This may explain why many attempts to hack the game have already been documented. This may also explain why people are being warned to be careful – which may also be why, this step in a new direction, is a little bit scary.
Let’s be real for a moment, using a simple example. Google, with very little effort, is already fully capable of determining where you are, how you got there, how long it took for you to get there, how long you will be there for etc. All because you set up an appointment on your Google Calendar, synced your reminder with your phone, looked up your destination on your Google Maps? Without too much effort, an entire company knows exactly where you are. The thing is however, there is an inherent trust in ‘corporations’. We assume, or hope, that they have an ethos in place that will protect us from abuse or exploitation.
So imagine then how much power someone with less than desirable intentions would have, should they be able to get access to the Pokémon Go server? How much traffic they would be able to direct or divert, exactly where they want?
Doom and gloom aside though. Let’s for a moment think about the practical applications of exergames like this. Let’s say I paid a company like Niantic to ‘place’ one of the ‘collectables’ near my coffee shop? My sales would skyrocket. The marketing possibilities are quite mind boggling.
Let’s take it a step further though. This same method of data collection could just as easily be tweaked by marketing companies to collect and collate real time data. This data can then be stored and analysed to become intelligent data, giving invaluable insight into where you shop, how long you stay in a shop for, and then of course billboard placements along the route you travel to get to the shop can be undertaken. Furthermore, having this data intelligence means that a business can develop and offer, customised offerings based on the initial real time location that was achieved from the data collection. In fact, when looking at the bigger ‘data’ pictures and thorough following the data processes – the possibilities are limited only by the imagination.
Data collection like this, along with data analysis, is very fast becoming mainstream. Unless marketing companies get good data collection methods in place, with well-equipped and forward thinking analysts who can also analyze the data effectively, they are soon going to find themselves lost in the world of 1 and 0.
In a world of Pokémon Go Mad and no real clue – how is one to navigate around it – does the answer lie in data collection, analysis and intelligence?