By Graham Bradley, Director, Mobile, EMEA at INRIX
Mobile network data holds many potential opportunities for revenue growth; most of us are wedded to our handsets, and this extensive usage creates a treasure trove of data waiting to be unlocked by operators.
For example, this information could be used to target customers with relevant location-based services or provide retailers with information on footfall or travel habits.
So what’s stopping operators from unlocking this pot of gold? The main barrier is the technical difficulty involved in processing and aggregating such enormous quantities of information. What’s more, this data only serves to highlight certain demographic or personal information about individuals.
Population analytics is a data-driven analytical technique for answering questions about large groups of people – as its name suggests, whole populations rather than individuals. Its power comes from its ability to not only understand where anonymous groups of people are at a given time, but where they have been, how they got there and where they may be going next.
The value of this data cannot be overstated; through forging the right partnerships operators will negate the need to invest in large, costly and time consuming technology infrastructure – a key consideration as they seek to take advantage of the clear benefits of this new analytics approach.
The sheer volume of mobile data today means that sample sizes correlate statistically with real-world population volumes. But the intricacies of mobile technology mean that without additional sources of data to combine this information with, it’s difficult to resolve the level of detail needed to build accuracy into any population modelling.
But what if mobile data is overlaid with other accurate sources of location information, such as GPS data from connected vehicles and devices? In the right hands, the combination of mobile data and GPS data becomes something much more than the sum of its parts – a true foundation for population analytics and a catalyst for a significant new wave of innovation across a multitude of sectors.
Population analytics is a promising investment for operators looking to differentiate themselves from OTT players that use mobile internet to drive their own services. Operators can leverage vast amounts of anonymised data from their own networks to drive new value-added services and additional revenues with partners, which is something that OTT players can’t do so easily.
In a global industry forecast by Telco 2.0/STL Partners analysts to be worth more than $11 billion by 2016, here are two examples of how operators can use population analytics intelligence based on their data:
Smart cities: existing city infrastructures are under strain, designed at times when populations were far smaller. As such, governments and public sector planners can no longer build their way out of congestion; they are tasked with finding other means of extending and re-engineering cities to cope with fast-growing urban populations. Using population analytics, they can determine how many people move around urban spaces, where they come from and where they return to. This is critical data for making informed decisions about building new roads or creating new transport routes.
Retail: population analytics can provide unrivalled demographic insights to retailers and marketers. Although the “who” of course remains anonymous, big data can reveal what a store’s true catchment area is and the demographic and postal area of key markets. This can be used as part of a location targeted marketing campaign that is tailored to individual shoppers’ habits and preferences.
Population analytics is still in its relative infancy, but is generating considerable excitement as the potential of its applications and associated revenues become clear. In the immediate term, though, it is mobile operators who have a critical role to play in building its foundations.
They stand to benefit in a wide variety of ways, everywhere from additional revenue streams, entry into new vertical sectors and the provision of value-added services for enterprise customers.
But to succeed, they need to partner with organisations with the data skills and assets to complement their own; whose experience in managing and integrating data from multiple sources at scale give them a significant head start to their new destination – growth.