Telcos are sitting on a mountain of data. It pours in like a river from customer interactions, their bills and their usage.
Telcos are investing billions of dollars bringing together customer data and gathering more customer data from a variety of sources. New and easier reporting brings access to this data and new tools are making the tasks of predictive churn models easier to produce.
However, in most cases the models are virtually the same as those constructed years ago, based on outdated segmentation and inaccurate assumptions. Telcos need to examine the data that they have (or have access to) and how it can be used to manage churn. Retention strategies should be tailored based on customer segment, lifetime value and buyer preferences.
Get the basics right Multiple interaction points from traditional call centers and more recent web and mobile interfaces provide operators with a wealth of data points and transaction detail. Hidden in the data is the key to the next generation of offerings as well as "predicting the prediction". Operators can now determine not only the customer's social and professional segmentation through static data (traditional approach) but also more dynamic characteristics, such as customer locale (internationally through roaming), entertainment preferences, shopping patterns and television viewing behaviors.
Combining this information allows for true customer insight into the buyer's needs and values. A couple of years ago, an APAC triple-play operator determined the correlation between mobile plan usage and TV behaviors through advanced analytics and segmentation. It then tailored its cross-selling strategies based on the identified correlation. Naturally, telcos still need to be cognizant of privacy concerns. However, there are less customers' complains regarding privacy as Facebook and Google have already set the stage for a privacy "gray zone".
Some telcos are using customer knowledge and advanced analytics capabilities to manage their churn through predictive modeling. Sophisticated churn modeling techniques have long been used to predict different churn behaviors. For example, churn models are used to predict churn along key points of the customer lifecycle. The most obvious example is increasing churn as customers are getting closer to contract end date. Churn models are also combined with churn trigger events to make retention efforts more relevant. For instance, research shows that following a single poor customer experience event, a customer will churn 80% of the time during the next opportunity.
Overall, predictive modeling is effective in identifying high-risk customers. As telcos refine and improve their churn models, they become not only aware of potential churners, but they also have a more advanced profiling of the potential churners. For example, they now understand whether a potential churner has family members who are also the telco's customers or whether customers are well-traveled. Hence, they can tailor offerings to those buyer values or preferences. This is just the basics. As predictive modeling becomes more common, telcos need to also add an additional dimension to their analysis: customer lifetime value. Actively manage churn Customer profitability is a critical aspect of churn management as it will determine the appropriate course of action (see figure on previous page).
To be effective, retention programs must be combined with overall customer lifetime value analyses through the customer lifecycle. Not all churners should be retained as retention efforts should be focused on customers who are "salvageable" and profitable.
Conceptually, there are three types of actions for potential churners:
¥ Retain and "farm" - for high-value customers, telcos will need to make sure they proactively engage in a retention campaign (likely to be incentive based and personalized) and maintain the level of profitability of the customer, through relevant, tailored and valuable offerings.
¥ Retain and improve yield - for second-tier customers, telcos will want to retain them especially in mature markets such as Singapore or Australia where acquisition has become more difficult and costly. However, there should also be an effort, not only to retain those customers, but also to improve their yield and bring them from tier 2 to tier 1. This can be accomplished through upgraded services or reduced cost-to-serve options.
¥ Churn and discard - lastly, for tier 3 customers, this is where the opportunity exists. Telcos are resistant to letting go of these low-value customers as it will affect standard KPIs (e.g. net additions, voluntary churn, total subscribers' base) and potentially impact the markets' perception.
Actively retaining these customers would be worse as it would be a costly exercise, spending money on customers with no profitable impact. Letting them churn would be far more effective in driving profitability up. Customers churn for different reasons. A one-size-fit-all approach will not be appealing and does not make sense from an economical stand-point for the telcos. If done well, telcos can generate significant value from retention programs.
In APAC, a telco with less than one million subscribers generated $30 million per year in revenue through precision targeting, i.e. by defining the appropriate segment level treatments for its churners. The figure above shows the four focus areas for a successful retention strategy. Telcos have an opportunity to better manage their churn, not only to identify churners, but also on differentiated treatment, based on their segment and lifetime value. All churners are equal... in quantity, but some are much higher value than others.
D. Robert Rutledge is Accenture's APAC communications, media and high tech APAC strategy lead;
Guillaume Sachet is Accenture's communications, media and high tech ASEAN strategy lead