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Average revenue per user has long been the benchmark metric in the wireless industry with fortunes gained and lost on even small changes in an operator’s ARPU result. However, ARPU was borne from a wireless age when voice, postpaid and subscriptions were the dominant drivers of success. The last couple of years have seen the wireless industry go through dramatic changes, as data traffic has become the growth engine while aggregate traditional transport revenues have plateaued in mature markets focusing operators on new drivers of income and profitability. One evolving result of these changes has been to make ARPU increasingly irrelevant as a measure. Several forces are now coming to critical mass that will likely seal the fate of the ARPU metric and the philosophy of what constitutes the success that it embodies.
The obvious changes that have occurred are the significant growth in data as the primary driver of operator revenue and the increasing prevalence of prepaid services, even in markets that were historically postpaid focused. Data and prepaid have independently changed the nature and level of revenue. Perhaps an even more important trend related to revenue, though not quite as obvious, has been the extreme growth in embedded wireless. Mature markets today are seeing over 100% penetration, a clear indicator of the trend toward people carrying multiple wireless devices. Current road warriors are armed with at least three wireless devices when considering cell phones, tablets and laptops. This trend will progressively reach more mainstream consumers as everyday products are becoming wirelessly enabled, such as e-readers, MP3 players, GPS devices and cameras, with more devices likely to be added to this category in the future.
Each of these devices also comes with somewhat different wireless revenue plans and pricing models, representing different business relationships between the user and the operator. On one hand, there can be a more traditional relationship where the subscriber selects their preferred wireless operator and pays a monthly bill based on a chosen plan. However, in the case of an e-reader, the user does not select a wireless operator directly, nor overtly pay for their service even though the operator supporting their e-reader may be the same operator for their more basic cellular service. Several other relationships could exist in a similar or slightly altered fashion between the user and the operator. Not only are usage and pricing levels different in these relationships, but profitability and service relationships can also be very different. In this environment, the concept of ARPU starts to lose any constructive meaning as it only describes one facet of what has fast become a multi-faceted interaction between the user and the operator.
The end result is that operators and the industry must take a very different philosophy when viewing users and providing an appropriate benchmark for success. The fundamental aspect of this new perspective requires a change from looking at the user as a single discrete relationship to examining the user more holistically and incorporating the various and disparate ways of interaction with the operator. Verizon Wireless has already taken a step in this direction by stating in 2012 that they would start to look at average revenue per account rather than ARPU, to take a broader view of actual subscriber revenue performance.
Beyond just the measurement of revenue, the changes will need to run much deeper in the operator organization with a broader cross-organizational view of the subscriber bearing equal importance. Customer care organizations are increasingly stretched to look at customers and services from all subscriber interactions no matter what device or access methodology the user engages with the operator. On the product and marketing sides of an operator, the challenge has been to move beyond traditional sources of revenue, which have essentially come from transport and gain new revenue generators. These new sources will also require a 360-degree view of the customer in terms of characteristics, demands and patterns. As operators gain a better view of their customers at an overall level, this data can be used internally to improve customer experience management and externally to create new revenue sources as well as potentially sell this knowledge to help enhance third-party applications and services.
The key enabler that is coming to the fore in making this move to a more complete customer perspective is the effective use of big data analytics. Inherent within the concept of this holistic view is the need to take data from various different sources, fuse it together, correlate it and identify valuable insights that can be generated from the data. On the surface, this sounds straightforward, but an operator generates billions of records per day from a wide array of platform sources from both operational and business environments. In addition, to be relevant in acting when needed, this analysis must occur in a real-time or near real-time basis. This is where some of the traditional business intelligence methodologies that have been adopted by operators will be limited, since the collection and analysis may take days and weeks, where new customer applications will demand action in minutes and hours.
Using network performance data coming from infrastructure elements and marrying this with customer call record information as well as customer subscription and device information can create a new type of client DNA that will allow operators to really understand their customers and more effectively measure their business. The analysis will also allow the operator to move from being simply reactive to situations, into a more proactive mode where the operator can predict potential issues ahead of time, manage these issues in a more structured fashion and ultimately make better business decisions.
Perhaps most importantly, as operators gain greater expertise and experience in utilizing these analytics, they can use intimate customer knowledge to change the revenue paradigm. New services and sources of income can be created in areas such as e-commerce, gaming and mobile advertising. As the Internet has shown, customer knowledge is the key element in assuring relevancy for the particular user, and this relevancy is critical to maximizing revenue from new services in the mobile environment. A wireless operator who knows its customer’s devices and inherent capabilities, a customer’s location and mobility habits and customer usage patterns, can better tailor the services and offers available to that customer. In the future, customer policy and preference selections can also be added to the analysis such that the operator can take effective action based on customer direction in response to a situation observed or projected to occur. Furthermore, these insights with customer permission can be shared with third party applications to enhance those environments, providing a richer user experience inside and outside the operator’s network as well as enable another source of revenue for the operator. All of this creates a much closer relationship between the operator and the customer, which will be hard for a non-incumbent operator to match and thus creates a strong barrier to churn for the customer. In summary, the shift in market and technology dynamics is creating a death knell for the ARPU metric but breathes life into a much more precise revenue model where operators can identify and prioritize customers by profitability through a rich suite of subscriber analytics.
