Adaptive Customer Management Leverages Big Data for Superior Customer Experiences

We hear a lot about Big Data, but data alone is virtually useless unless organizations can extract meaning from the volumes of data collected by their systems. For communications service providers (CSPs), Adaptive Customer Management (ACM) has emerged as a technology that service providers can use to gather data about customers and key processes, match that data with customer behavior and context and in turn, improve the customer journey by creating better customer experiences that lead to increased revenue for the CSP.

You may be familiar with a variety of technologies that manage some aspect of the customer relationship (CRM) or customer experience (CEM). But for our purposes here, the word "adaptive" is key.

The success of an ACM program depends upon the availability of flexible OSS/BSS systems that manage the connection between the customer and the network and between the customer and business processes. These systems allow CSPs to identify individual customers or customer groupings by their behaviors and subsequently offer them targeted premium experiences at a time when the customer is known to be interested in that specific experience.

This precise targeting of needs provides value to the individual customer and avoids the perception that the customer is "overpaying," as is often the case with off-the-shelf plans when the plan provides features that the customer does not use.

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ACM supports the creation of superior experiences and customer value that can earn revenue for the CSP. Indeed, ACM provides a method for a CSP to differentiate its services when the competitive landscape contains multiple competitors, all offering nearly identical products and services. Fortunately, the experience created through the combination of ACM with Big Data and flexible BSS/OSS systems helps providers enhance customer satisfaction, avoid churn and realize a premium price for the services. ACM leverages the insights derived from Big Data relative to consumer behaviors and the context in which subscribers use services. Specifically, using the control offered by BSS/OSS systems, the service provider can adapt pricing, promotions and product offerings based on individual customer journeys revealed by the profile data. The creation of consumer personalization and choices allows the CSP to grow business, retain customers and promote loyalty.

ACM leverages dynamic content from the data universe, including predictive/adaptive intelligence, dynamic market segment definition, pricing intelligence and an adaptive product catalog. The orchestration, learning and value creation of ACM includes the following main components:

  • Execution orchestration
  • Campaign performance
  • Offer provisioning
  • Machine learning

Service providers are advised to implement a solution theory that includes taking the opportunity to understand and predict their consumers' basic, periodic and spot needs, driving personalization to be a competitive advantage. The opportunity landscape includes basic needs, lifestyle offers and premium promotions.

  • Basic needs – 24 x 7 x 365, base service voice and data levels
  • Periodic and lifestyle needs – tapping known patterns from subscriber's data, add usage and revenue
  • Spot needs – predicting events and usage patterns for premium revenue. Based on an occasion, event, time and/or location

Right Place, Right Time

It is critical to address customer needs at the right time. Under-use of plan limits and features creates the perception that the subscriber is over-paying for unused features. By the same measure, over-use penalties kill loyalty and fuel competitors, as customers are incited to look for cheaper options or "all-in" plans from competitors.

Starting with basic needs, e.g., 4 GB data usage, any location, any time, incrementally priced functions can be offered based on knowledge of the subscriber's usage patterns derived from the CSP's database. Here is where the opportunity to manage the customer experience in a positive way enters the picture: based on the customer's profile, the CSP can offer incentives distributed among periodic needs and spot needs. For example, offers can be based on location, an upcoming holiday or remote access to a sporting event. The customer can choose the opportunity based on his or her immediate need, paying a nominal fee. This approach, regular use of Big Data resources along with BSS/OSS functions, can lead to significant revenue gains while simultaneously retaining a satisfied customer.

Managing customer data properly can lead to the expansion of personalized customer relationships, such as informing customers of products, services and third-party partnerships for new revenue streams. For example, a customer may be aware of the available plans, devices and accessories. But they may not realize that partner offers are available, such as bundled plans with voice, wireless, data and video, as well as loyalty and rewards programs. Based on BSS/OSS awareness of subscriber usage patterns, segment strategies can be implemented to stimulate subscriber activities that can generate revenue, such as encouraging a device upgrade or increase talking or data usage.

The CSP analyzes the data gathered from the subscriber over time and applies this insight using an experiential-based decision process. This process takes essential analytics (time/location, usage, profile/third party and context) combined with customer experiences (standard, lifestyle and premium) and "decides" which actions can be "earned" in each case. Examples include:

  • Static and frequent location offers
  • Usage based predictive analytics
  • Usage and interest-based offers based on time and location, including third-party offers
  • Customer experience: identify standard, lifestyle and premium experiences
  • Spot offers based on predicted usage
  • Frequent commute pattern, vacation, special dates offers
  • Alternative customer choice based on price, value or context (may include granular-level pricing and low-end to high-end consumer pricing strategies)

Adaptive Customer Management promises to contribute to a new level of product differentiation as communications services become more alike among competitors. ACM not only provides a means of improving customer experiences and reducing churn, but also offers new sources of revenue and network efficiency metrics.

For more information on how Excelacom can help you develop an effective Adaptive Customer Management strategy, please email us at