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SPRINT
Profiling Audiences Using Mobile Network Data
Background
Sprint are one of the four big US mobile telecoms service providers with more than 57 million subscribers. This gives them access to a huge amount of data on their customers, who increasingly rely on their mobile devices when going about their day-to-day lives.
In 2012, they founded the subsidiary Pinsight Media, with the aim of taking these data sources and using them to segment audiences for targeted, mobile advertising platforms.
What Problem Is Big Data Helping To Solve?
Lots of us think of advertising as an annoyance or an intrusion. Generally, advertisers have very little idea about who their message is getting through to, and as a result they spend a lot of money passing on a message to people who just aren’t interested in, or couldn’t possibly afford, whatever is being sold. When this happens (and obviously it happens a lot – most of us probably experience it every single day of our lives) then advertising becomes irrelevant and the effort and expense that the advertiser has put into getting their message to that person has been utterly wasted.
Targeted advertising as it has emerged in the direct-marketing industry and evolved throughout the digital age is the answer. It attempts to segment in as detailed a way as is possible, taking into account demographic, behavioural and locational data. There is a problem here, though, in that a lot of audience segmentation methods rely to a great extent on self-reported data. People can easily set up social media profiles with false information, for reasons of anonymity, and much of the data generated online is cut off from anything that could tie it to a real potential customer.
How Is Big Data Used In Practice?
Pinsight Media used network-authenticated first-party data to build up more accurate and reliable (and therefore more valuable) profiles of consumer behaviour, which allow them to offer more precisely targeted audiences to advertisers. This means there’s less chance of putting an advert they will find boring or irrelevant in front of them, and a higher chance they’ll see something they will consider spending money on.
This is similar to the targeted advertising services that are common today, thanks to the likes of Facebook and Google, but with the major difference that they are primarily built around network carrier data.
Jason Delker, chief technology and data officer at Pinsight, tells me: “Mobile operators in general have focused on their core business, which is deploying robust network infrastructure and feature-rich devices. They’ve not generally been focused on how to monetize the wealth of data they have. They have focused on metrics like network performance, churn reduction, customer care – and these are extremely important … but there’s this whole other business which they haven’t really engaged in.
“The mobile services, social networks and even the device manufacturers that mobile operators partner with have leveraged over-the-top applications and created this ecosystem focused around [targeted] advertising that generates hundreds of millions of dollars, and they’ve done it using data which is essentially inferior to what a mobile operator has access to.”
Pinsight Media have developed their own tool, known as a data management platform (DMP), which is used to create targeted advertising profiles using that unique data, which only Sprint have access to. They combine this with bought-in and freely available external datasets to further refine the precision with which advertisers can target their campaigns.
On top of that, they also develop their own applications, such as weather apps, sports apps and a browser for the social media sharing and discussion service Reddit. This allows them to collect more information, which can be tied to a user advertising ID based on a “real” person, as authenticated through Sprint’s user data.
What Were The Results?
In the three years since Pinsight Media were launched, Sprint have gone from having no presence in the mobile advertising market to serving more than six billion advertising impressions every month, making them a major player in the online mobile advertising game.
What Data Was Used?
The Pinsight service operates using three main types of data: locational, behavioural and demographic.
Locational data, Jason explains, is: “Multi-laterated data – a result of the 55-million-plus mobile devices we have that are travelling all over the country.
“As a result they are talking back and forth with radio towers – so we take the latitudinal and longitudinal coordinates of the tower as well as about 43 other different fields and attempt to use them to decide where a mobile device is at a certain time.
“If a user is travelling and performing multiple actions throughout the day – whether its text messages, phone calls, app usage, emails – [they] can generate thousands of event records per day and as a result we have a lot of location data that we can leverage.”
First-party-authenticated behavioural data comes from analysing the packet layer data captured by probes which analyse network traffic and were originally put in to assess and improve network performance. While the content of these packages is often encrypted (using HTTPS services), the platforms where the data is originating from is trackable. “What we were interested in were the publisher-level details, what are the actual services they are using?” says Jason. “And what was the duration? This means we can start to understand that maybe a person is a part of a particular audience. A person might well be a gamer if 20% of their app usage is spent on Clash of the Clans.”
Demographic data comes from the billing information supplied by the customer when they take out the account, augmented by third-party, bought-in data from companies such as Experian.
What Are The Technical Details?
The Pinsight platform ingests around 60 terabytes of new customer data every day. Data is split between two systems – with personally identifiable proprietary information kept on their own secure Hadoop in-house system – while application data and product platforms are run from Amazon Web Service (AWS) cloud servers.
The team use the Datameer analytics platform for its number crunching and have adopted the “data stewardship” philosophy put forward by US Chief Data Scientist D. J. Patil, where a data steward is selected from within every department with responsibility for ensuring analytics is implemented wherever possible. Data stewards are all trained on the Datameer tool. AWS Lambda infrastructure lets them ingest and manipulate large real-time data streams.
Any Challenges That Had To Be Overcome?
Of course, mobile data is particularly sensitive and private, owing to the details it can reveal about our private lives. To accommodate this, Sprint’s service is opt-in only; customers have to specifically give permission for their information to be used to provide them with targeted advertising.
Jason says: “Sprint is the only one of the four large wireless US operators that by default opts everyone out. Instead, we try to convince them – and it’s been very easy to do – that if they actually let us leverage that data we will send them things that are more relevant, so ads become less of a nuisance and more of a service.
“Customers are pretty wise to the fact that those types of service help fund and lower the cost of the core mobile operator services.”
What Are The Key Learning Points And Takeaways?
Mobile operators have access to a wealth of uniquely insightful and, importantly, verifiable data that can be used to make advertising more relevant and efficient.
Much of this data is highly personal, and shouldn’t be used without a customer’s explicit permission. However, anecdotal evidence seems to suggest that more and more of us are happy enough to give this permission, if it means being targeted with more relevant and less intrusive advertising.
Customer data can provide a very valuable additional revenue stream for companies that put resources into leveraging it. This can be used to drive down prices in the core business and pass additional value on to customers.
REFERENCES AND FURTHER READING
For more information on Sprint’s use of data, visit: