Putting Big Data to Work for MVNOs

By: Andy Peers

The retail MVNO is an established marketing and branding tool. The mobile home-screen has always been a valuable piece of brand real estate, a chance to put a logo in front of the customer on an hourly basis. Today, however, there is plenty of competition for brand equity, and the demonstrable financial value of that logo is diminishing. If the only other time the consumer sees a logo is on their bill, it is perhaps time to re-assess what branded mobile can – and should – do.

Smart MVNOs are moving away from prepay and its declining revenues: the rise of the ubiquitous, do-it-all smartphone has made sure of that. They also don’t want to compete on price, because it’s a race to the bottom. Besides, even other MVNOs (especially the cheap international calls companies) can do a better job of price-based competition. So what can retailers do to extract additional value from their existing MVNO investments?

A good start would be for retailers to recognise that mobile is not just another product line: it is an exceptional source of rich data. This is data which can be put to work across the value chain. In the words of analyst Ovum’s report, Telco Big Data: Building a future business platform, “Telecoms operators finally have a good opportunity to generate new business models beyond traditional connectivity... Telecoms operators already collect thousands of different items of data, including usage, content and location, and no other industry has its customers interacting with the company 24 hours a day, seven days a week.”

Through a mobile device, we can transcend the hated snooping of browser histories (who wants yet more advertisements for something they have just bought – or decided not to buy?) and elevate our customer knowledge to a blend of current and anonymised profiling which yields frictionless marketing. We can establish where a customer lives and works, and their typical habits – like a Saturday mall visit. Marrying location and geofencing, we can establish how customers typically use competitors’ stores. Instead of drab proximity marketing – sending messages only because a user happens to be in the area, we can use multiple data sources to validate elaborate interactions based on exceptional relevance. This is marketing for the 99.9% of the time that a customer is not in your store; and we can use it both to drive traditional brand sales and also to derive value from the intrinsic worth of data itself.

Of course, there is a significant privacy issue here. But this data has already been surrendered by users – and other players in the market are already using it. OTT services are huge information-gatherers: Facebook tracks plenty of mobile metrics, and Google even routinely records audio from the smartphone microphone. Telcos and MVNOs are simply missing out.


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