Havish's blog first appeared in RCR Wireless News
As systems become increasingly intelligent, companies are able to collect extraordinary amounts of data about their products and their customers. The term "big data" emerged several years ago to describe this large volume of both structured and unstructured data. But it's not the volume of data that's important, rather, it's what companies do with the data that matters. Ultimately, big data about products and customers can be analyzed to not only better understand products and customers, but understand how customers are using those products today, and predict how they want to use them in the future. This, in turn, helps companies make better strategic business decisions to meet those customer expectations and grow revenue.
Companies such as Apple, Nike and Starbucks each play in highly competitive markets, with dozens – oftentimes hundreds – of competitive options. What do they do differently to survive and thrive? They provide premium experiences to their customers, create premium value and charge a premium price. This same opportunity exists in the communications service provider arena – companies with similar services and similar pricing need new ways of thinking about how to differentiate their services from those of their competitors and create new revenue streams.
Enter adaptive customer management, a flexible new way of helping businesses look at the customer journey. ACM is helping CSPs gather big data insights about customers and processes, and matching that data with customer behavior and context to create premium – and personalized – customer experiences. This, in turn, is helping drive new revenue and creating deeper customer loyalty for the CSP.
ACM programs require flexible operating support and business support systems that manage the connection between the customer and the network, and the customer and business processes. These systems allow CSPs to identify individual customers or customer sets by their specific behaviors and offer targeted premium experiences at a time when the customer is known to be interested in that specific experience.
ACM leverages the insights derived from big data relative to customer behaviors and the context in which subscribers use services. Using the "adaptive" nature offered by flexible BSS/OSS systems, the CSP can adjust pricing, promotions and product offerings based on individual customer journeys that are revealed by the profile data. This precise targeting of needs provides value to the individual customer and avoids the perception that the customer is "overpaying" for features or services in off-the-shelf, non-personalized plans that the customer does not use.
ACM leverages dynamic customer data, including predictive/adaptive intelligence, dynamic market segment definition, pricing intelligence and an adaptive product catalog. Service providers can use these elements to understand and predict their customers' basic, periodic and spot needs, driving personalization as a competitive advantage:
Addressing customer needs at the right time is critical; making an offer after they have left a store or have gone over their allotted data usage for the month, for example, is not a premium experience. Being able to adjust packages and promotions to meet specific (or group) needs in real time or near real time is key. Knowing the customer and understanding how they use a service is critical. Under use of plan limits and features, for example, creates the perception that the subscriber is overpaying for unused features. At the same time, penalties for overuse can destroy customer loyalty and incite customers to look for cheaper options or "all-in" plans when they feel their options are limited or are consistently feeling as if they are overpaying for or under utilizing their services.
In an ACM process, the CSP analyzes the data gathered from the subscriber over time and applies analytics (time/location, usage, profile/third-party and context) combined with customer experiences (standard, lifestyle and premium) and chooses an appropriate action or offer. Examples of such offers might include:
Starting with a customer's basic usage needs, incrementally priced offers can be given based on knowledge of the subscriber's usage patterns derived from the CSP's database. ACM is what allows this experience to become personalized, however. Based on the customer's profile, the CSP can offer incentives distributed among periodic needs and spot needs, such as offers based on location, an upcoming holiday or remote access to a sporting event. The customer can choose the opportunity based on their immediate need, paying a nominal fee. This personalization of offers – enabled by flexible BSS/OSS capabilities – can lead to significant revenue gains while creating an enhanced customer experience.
Suddenly, the opportunities to inform customers of new offers based on their customized and personalized profile are limitless. For example, while many customers are aware of the available plans, devices and accessories a service provider may offer, they may not realize that partner offers are available, such as loyalty and rewards programs, new service bundles and so on. Using subscriber data, CSPs have the ability to upsell or cross-sell packages and promotions – both their own and those of third-party partners. The devil is in the details and only a flexible OSS/BSS system can ensure the delivery of the right offer at the right time to a receptive customer.
As competitive differentiators continue to shrink among CSPs, ACM is emerging as a new and vital tool to help providers differentiate their services, providing a nearly real-time premium customer experience. The end promise: increased customer loyalty and the introduction of new revenue streams.
For more information on how Excelacom can help you optimize Big Data to create a premium customer experience with ACM, please email firstname.lastname@example.org.