Transforming the customer care model using predictive and real-time analytics
Since the introduction of telephone service in 1877, or the first cable television service in 1948, the model of providing customer service has largely remained unchanged. That model consists of using historical call patterns supplemented by current operational activities such as a new device rollout or introducing a new service to size and train care operations.
Today, communications service providers (CSPs) and cable operators typically have thousands of care personnel for small and medium operations (one-to-ten million subscribers) to tens of thousands of care personnel for really large operations (50–100 million subscribers or more). The model waits for subscribers to initiate contact, also known as inbound communication, with the provider. Typically, upon initiation of contact, subscribers already have had a bad experience; very few calls are documented in which subscribers call to say “nice job!” Instead, they may have already voiced that opinion to friends and others through social media.
Transforming customer care
At this point, care agents go into action. Using analytics and available information they are tasked with three prime objectives:
- Resolve problems to end calls in a timely manner.
- If unable to resolve problems immediately, pass subscribers from a tier two level of service to a more costly tier three support option.
- Offer subscribers an up-sell option to their current service or product.
This model can be costly, and in most cases when the issue is resolved, the experience damage is already done.
In an effort to transform care, a new model fosters taking a proactive approach with big data and advanced analytics to deliver valuable communications to subscribers before problems arise or before they initiate contact.
How is this model accomplished?
Today, technology advancements and appropriate application of the technology enable monitoring individual subscriber experiences on a near-real-time basis. Then providers can apply sophisticated predictive modeling that identifies patterns previously hidden in the data. It identifies and notifies universes of subscribers who are similar to a small sample size for known or emerging issues, which is akin to the proactive care approaches already adopted in the consumer goods and automotive industries through the recall mechanism.
Taking this approach can significantly reduce call volumes, which in turn significantly reduces operating expense (OpEx). Delivering a differentiated customer experience further creates value realization. Imagine, for example, your phone company providing personalized service. This service may be guidance to extend your smartphone’s battery life, an offer for a better call plan than your current plan based on your usage, or a discount on tickets to sporting events involving your favorite teams. A near-real-time, multidimensional analytics environment can be a foundation for a model transformation through insight gained by using the following sample of questions:
- Which network locations drive a poor experience?
- How does network performance impact experience?
- Which devices are causing the most calls to be generated?
- Which service plans and billing questions are subscribers calling about?
- Which apps are related to call volume?
- What are subscribers saying on social media?
As an example, capturing the value for a 10 million subscriber-based company yields the following benefits at a minimum that can be expected in the first year:
- $15–30 million, or a 20–40 percent reduction in call volume
- $10–20 million, or a 10–20 percent increase in positive subscriber experience—as measured by the Net Promoter Score (NPS) and churn
- $10–20 million in generating new revenue opportunities by linking marketing and sales to the communications cycle
- $35–95 million in total value expected in year one
Leading CSPs and cable operators are already beginning to realize tremendous value by shifting the care model. This once-in-a-career opportunity can transform an industry—unless, of course, you have helped Apple transform industries four or five times during the last ten or more years.
IBM will make an important announcement about industry-specific analytics solutions. Join us for the video announcement on May 28, 2015.