The last several years have seen wireless phone service move from luxury item to fundamental communications tool that many find indispensible in their everyday lives. This phenomenon is not just unique to mature markets but also in developing areas throughout the world. The ITU estimates that in 2013, penetration rates in developed markets will reach 128%, while in emerging markets the penetration will hit 89%. The rate in developing markets becomes even more significant when factoring in economic capability, which means that among people that have the economic means in these emerging areas, the penetration is likely getting very close to developed markets. The success gained from getting wireless devices into consumers’ hands doesn’t have a beneficial corollary for operators that have seen a significant slowing in their aggregate subscriptions and revenues.
GSMA has reported a worldwide annual growth rate for subscribers of over 8% from 2008 to 2012 while from 2012 to 2017 this is expected to drop to about half this rate. Clearly in developed markets, this maturity has already occurred and been most dramatic with various estimates of growth below 2%. The more worrying trends for operators are around the plateau that is similarly occurring in revenue. From an aggregate level, GSMA reports total operator revenues between 2008 and 2012 grew by 4.2% but that during the following five years to 2017 this is projected to be 2.3%. In Europe, revenue growth has turned negative with a 2% decline that is expected to continue for the next several years. More specifically, at a subscriber level, ARPU during the last five years has declined by almost 8% worldwide. Given the nature of multiple subscriptions, ARPU is not the best indicator of trends, but even looking at a combined subscriber metric (ARPS) the decline worldwide has been -3.8% since 2008. All of these statistics point to an evolving marketplace for mobile operators over the next few years that will be dramatically different than the past several years. Mobile operators will have to adopt new tactics to effectively combat competition and fight the trends on revenue deceleration. A key weapon in this new battleground will be the effective use of big data.
One of the main assets that operators have to leverage in this environment is their relationship with subscribers and the knowledge operators have about these customers. Implementing big data solutions allows operators to take this rich but complex and unstructured customer information and transform it into meaningful insights and analytics that can drive revenue. The revenue gained using big data can be used to offset revenue declines from traditional transport sources and will enable revenue sources from other segments beyond consumer and enterprise.
There are several places where data analytics can play a vital role in reshaping the growth direction of operators and positively change the operator’s competitive battlefield. In this new environment of decreased subscriber growth, changes in market share for operators will increasingly come from taking customers from another operator. Of course both sides know this, so managing churn will continue to take a greater amount of operator focus. Effectively managing the user experience across the entire customer lifecycle is imperative to minimizing churn and attracting customers from other networks. Big data is an important facet in optimizing the customer’s experience by allowing the operator to synthesize multiple data sources into a comprehensive picture of the customer’s reality. Understanding this reality permits the operator to proactively address potential service issues as well as assure that the customer is on the right plan that best suits their usage. This level of customer intimacy creates a closer link with the subscriber and should enhance the overall relationship with resulting minimization of churn. Additionally, gaining a reputation for a high degree of customer service will be a valuable weapon in encouraging customers to change carriers in an environment where pricing differences between operators are nominal and differences in product offerings are minimal and largely hard to sustain.
A second aspect where customer intimacy created by effective use of big data will come into play is around the services offered by an operator. As mentioned above, it is difficult for an operator to create a service that is difficult for another operator to similarly offer. The differentiating factor for the operator is in their ability to tailor the specific portfolio of services and capabilities that are uniquely delivered to the subscriber. A deep knowledge of customer preferences and habits that can be obtained by analyzing both static subscription information as well as dynamic usage data will allow the operator to provide a service package that is customized for that individual subscriber. For example, customers who have significant interest in social networking can be offered packages that highlight this type of usage.
In order to stimulate usage and resulting revenue, operators can also use customer knowledge to present offers and promotions that will be the most relevant for individual customers. This relevancy maximizes the likelihood of a subscriber accepting an offer and strengthens the carrier’s relationship with that customer. Google has already demonstrated the significant value that is inherent in customer knowledge when trying to target advertising and create a higher probability of sales success.
In the future, as issues around customer privacy become more settled, this same customer knowledge can be used with customer permission to help third parties better tailor their services for the end user. Monetizing this customer information will then become another revenue stream for the operator coming from applications providers as a new revenue source. A further evolution will be to combine customer profile and policy requirements with data analytics to automatically and dynamically create new solutions. Based on parameters that have been previously defined by the customer, data analytics can determine the current context of the subscriber and then either allow or deny various capabilities, customer access, and applications to be employed. Again, all of these tactics tie the customer much closer to the operator and make it much more difficult for the customer to churn and find a similar level of support.
Wireless operators are entering a new phase in their competitive battle with a particularly enhanced focus on managing churn and creating new sources of revenue outside of traditional transport. A fundamental and sustainable differentiator for operators in waging this new war is developing a unique customer intimacy link whose foundation is the effective implementation of big data programs. Data analytics is the ‘not-so’ secret weapon in this new war that can be used to develop a deep understanding of customers’ needs and create proactive responses. Big data provides the ammunition that, when effectively deployed, can improve the customer relationship, reduce churn, and drive incremental revenue through service portfolios customized for the individual user. Operators who successfully fight these battles will be well poised for a long and profitable future.
Rob Chimsky is Vice President of Insights at Guavus.