A false dichotomy between fixed and mobile users is on the wane.
Converged telcos, those which offer both fixed and mobile services, have not had an easy ride. Initially destined to erect fortresses of client loyalty through convenient product bundling, they have amassed timid churn reduction victories. Similarly, the sharing of assets and operations across mobile and fixed businesses, a gargantuan source of promised synergies, has sometimes failed to deliver on the full expectation of its gains.
A particularly vexing obstacle to converged operators’ enhanced value extraction has been entity resolution – or the lack thereof. Households (the typical subscribing unit of fixed services) and mobile subscribers belong to two distinct, hard-to-reconcile spheres of identification which seriously inhibit single-customer views.
At the heart of that challenge lies an inability to establish which individual mobile users are latching, over wi-fi routers, onto fixed home data connections. This happens because mobile devices send very little in the way of unique identifiable metadata when running on wi-fi. Once a subscriber leaves the mobile network and enters the fixed one, he vanishes from the converged operator view.
Not knowing ‘who is who’ on each side of their services, converged telcos find themselves unable to develop basic cross-product intelligence, struggling to answer questions like:
- Which are the households with the highest mobile acquisition potential?
- Which are the households with the highest up-sell/cross-sell potential across both access technologies?
- What is the detailed device model composition of each household?
- How can I strategise my ground-level efforts to maximise whole-family acquisitions?
Unsurprisingly, this blindness is a major drawback: it makes it impossible for converged telcos to drive a more pointed consolidation of individual users under one single roof, wherever they are, whichever service they want to use.
“A particularly vexing obstacle to converged operators’ enhanced value extraction has been entity resolution – or the lack thereof.”
In order to solve this problem at a network level, converged operators must achieve two breakthroughs: firstly, the extraction of device-level traits that are expressive enough to provide minimal misclassification rates. Secondly, and perhaps most importantly, the implementation of pattern-detection logics that are scalable across live operational environments of network analytics solutions.
Besides addressing household-level ambiguities, this new ability would also enable a broader set of fixed-to-mobile identity resolutions. It could be applied, for example, to determine how mobile subscribers navigate among public wi-fi hotspots, feeding the production of digital location demographics and profiling.
Other use cases linger in the horizon. With the impending explosion in IoT adoption, determining who is surrounded by which ‘things’ will become a must. How can we still retain a person-centric view of the machines being used out there? How to define which devices are related to which individuals, and eventually delineate an explicit landscape of our extended digital selves? Cross-network identification techniques can surely have a contribution to answering those questions.
Ultimately, mobile and fixed users are one and the same: integral individuals, sometimes satisfying their connectivity needs over GPRS technology and some other times resorting to fixed networks for data exchange. Creating over-arching network identities is, thus, a long overdue competitive advantage that converged telcos must urgently tap into.