Adaptive Customer Management Creates Exceptional Customer Experience Through Big Data Analytics

Havish's article first appeared in Pipeline Magazine.

As a society, we collect an awful lot of data: about people, about processes, about things. The volume, variety and velocity of Big Data is growing exponentially, and over the next 10 years, global traffic is predicted to reach over 100 trillion gigabytes. Research firm IDC argues that the world's information now doubles about every year and a half. It's the intelligence of our systems that's precipitating this rapid growth—the volume of structured and unstructured data being collected isn't necessarily valuable on its own; but what companies can now do with this data is becoming incredibly important.

Data collected specifically about customers—their likes, dislikes, purchasing patterns, abandonments, frequency of purchases and other variables—is being analyzed to not only better understand customers and the products they're interested in and using, but also to predict how they want to use them in the future. The analysis of this data is also helping companies make better strategic business decisions to create better customer experiences and, as a result, develop new revenue streams and increase revenue.

Companies such as Apple, Nike and Starbucks have perfected the creation of superior customer experiences. Each of these companies play in highly-competitive markets, but have found a way to rise above the competition by providing premium experiences, creating premium value and charging a premium price.

This same opportunity exists for competitive service providers (CSPs). Looking at the market today, there are dozens of wireline and wireless service providers, each offering similar services or bundles to their potential customer bases. This has changed significantly from just a few years ago, when it was easy to distinguish the market leaders by the sophistication of their offerings. Now that the gap has been closed, service providers need to embrace a new way of thinking about how to differentiate their services from those of their competitors and create new revenue streams. The standard bundle—the staple for service providers for the past decade—isn't enough. For example, many standard wireless bundles include a certain amount of data or a certain number of texts or minutes. Customer that don't come close to those limits in the standard off-the-shelf plans may feel like they are "overpaying" for services they are not using.

Apple, Nike and Starbucks have figured out how to use data that they've gathered about the market, their products, their processes and their customers to create these premium experiences. What they've done is not rocket science, but it is based on technologies that manage some aspect of the customer relationship. Customer relationship management (CRM) and customer experience management (CEM) are the familiar terms in this space; but, in the service provider space, Adaptive Customer Management (ACM) has emerged to allow service providers to gather data about customers and key processes (such as customer interactions and customer profiles). CSPs then match that data with customer behavior and context and use it to improve the customer journey by creating better customer experiences that lead to increased revenue. The objective is to proactively influence interactions with the customer so the outcomes are better both from the customer's and company's perspectives.

What is ACM and Why is it Different?

The key word in this type of customer management technology is "adaptive." Service providers can use existing structured or unstructured data to adapt their processes and their offers, often in real time, and make them better for their customers. However, a successful ACM program requires flexible service provider OSS/BSS systems that manage the connections between the businesses processes, the customer and the network.

These systems allow providers to precisely identify individual customers or groups of customers by an action or a set of behaviors and manage the experience, such as by providing targeted premium offers and experiences at a time when the customer is known to be interested in that specific experience. By knowing their customers better and gaining critical insights into their profile and behavior through the data they've gathered, as well as having a flexible BSS/OSS system in place to act on that data in real time, providers can enhance customer satisfaction, avoid churn and realize a premium price for these services. They can adapt pricing, promotions and product offerings based on individual customer journeys revealed by the customer profile data. The creation of consumer personalization and choices allows the provider to grow business, retain customers and promote loyalty.

ACM leverages dynamic data and, when combined with its BSS/OSS system, it can develop predictive/adaptive intelligence, dynamic market segment definition, pricing intelligence and an adaptive product catalog.

Different Customers, Different Needs

Through ACM, providers can drive personalized services by understanding and predicting three different types of needs and using them to create a competitive advantage:

  • Basic needs – 24 x 7 x 365, including basic voice and data levels. 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).
  • Periodic and lifestyle needs – Tapping known patterns from subscriber's data, adding usage and revenue.
  • Spot needs – Predicting events and usage patterns for premium revenue based on an occasion, event, time or location.

Managing customer data properly can help create more personalized customer relationships that use these different types of needs to strengthen the bond between customers and providers by informing customers of products, services and third-party partnership that in turn can help create new revenue streams. For example, a customer is likely aware of a provider's published plans, devices and accessories. But they may not realize that partner offers can also be part of the offering, as well as customer loyalty and rewards programs. Based on awareness of subscriber usage patterns gleaned from the data using ACM, providers can create specific packages for individual customers or customer groups that can generate revenue, such as suggesting a device upgrade or an increase in text or data usage.

With a flexible BSS/OSS system in place, it's easy to think how a provider can begin to target users with specific offers based on their profile. Starting with a customer's basic needs (for example, monthly data usage of 4 GB and anytime calling), incrementally priced offers can be made based on knowledge of the subscriber's usage patterns derived from the provider's database. Using ACM, the provider can manage the customer experience in a positive way. Based on the customer's profile, the provider can offer incentives based on periodic or spot needs, e.g., a sporting event, an upcoming holiday or even on the customer's specific location (such as a partner offer at a local coffee shop). The customer can choose the opportunity based on their immediate need, paying a nominal fee. This approach—use of Big Data along with BSS/OSS capabilities—can lead to significant revenue gains while simultaneously improving customer satisfaction.

What's becoming increasingly clear is the need for "right time" data, which usually means "real time" data. It is critical to address or predict a customer's needs at the right time: when they walk into a store, open a website, display an action that indicates a need or a desire or have a history that indicates a particular action is likely to happen.

That also means that a customer's history is also critical to detecting patterns and predicting behavior. Providers can analyze data gathered from the subscriber over time and apply insights 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 action or offer should be made. These actions might include the following:

  • Static and frequent location offers;
  • Usage and interest-based offers based on time and location, including third-party offers;
  • Spot offers based on predicted usage;
  • Offers based on "frequently driven" commute patterns, vacation patterns;
  • Offers based on a specific date – holiday, birthday, etc.; and
  • Special offers based on price, value or context (may include granular-level pricing and low-end to high-end consumer pricing strategies).

Adaptive Customer Management is emerging as a new way for service providers to utilize the wealth of data they've collected about their customers and their behavior, and utilize their BSS/OSS systems to personalize offers and packages based on a series of criteria. It allows them to truly provide the differentiated services their customers desire, reducing churn while separating them from the pack of competitors with similar services. Most importantly, ACM provides a clear path to new sources of revenue—something that should make every service provider stand up and take notice.

For more information on how Excelacom can help you implement ACM to create an exceptional customer experience through Big Data, please email us at