- Customer: behavior, experience, churn
- Devices: Uptake, Performace, failure
- Network: Performace, failure
- Campaigns: Uptake, Network Impact
- Services: Uptake, Performace, failure, Network Impact.
Tools Use By Telecos for analytics.
- k-nearest neighbors algorithm
- SciKits (Python)
Digital Transformation in Telecom
In a digital world, every user is connected to the digital space, and their experience determines the value of a service – and affects revenue, costs, and reputation. Every customer journey is made up of a complex series of interactions with individuals, technology, and automation. Each of these episodes contributes to the overall customer experience and impacts the quality of service delivered by the communications service provider (CSP) and its brand.
Many CSPs have already begun their digital transformations, with customer experience as a primary driver. In a recent TM Forum surveyed 100 CSPs about transformation, and nearly three quarters said that developing stronger customer relationships was a top
goals for their programs.
Eighty percent of operators said they consider “enabling customers to engage in a consistent and seamless experience across multiple channels that collect relevant
data and maintain a profile of each client using advanced analytics” a high priority. Likewise, 72 percent stated that “establishing a strategy-led comprehensive customer experience roadmap to drive organizational culture, executives, functions, and investments to achieve the target customer experience vision” is a high priority.
But the Big question is how? What’s it like to be a digital consumer? How can operators improve the overall customer experience and still increase revenue?
Discovering real customer insight is our biggest challenge.
Analytics are critical
To accomplish digital transformation and become truly customer-focused, CSPs need to better understand the customer journey. This requires sophisticated analytics and machine learning to take mountains of structured and unstructured data from multiple sources and use it to understand and support customers. In addition to the ‘past’ data that many operators already collect, they also need to take advantage of ‘fast’ or real-time data.
Defining and delivering digital services is complex, and ensuring that the resultant customer experience is efficient and effective requires careful planning and execution. Customer journey analysis and the role of analytics.
Customer journey analysis and the role of analytics
- What it means to analyze customer journeys
- Why using advanced analytics and machine learning are important
- How resultant data can improve customer journeys
- How Telefónica is modeling customer journeys
- What to do next.
Analyze customer journeys
As CSPs transform their businesses to become DSPs, it is important to recognize that every action and transaction that occurs during each episode along the customer journey determines whether a customer will subscribe and stay, or churn. Yet, while CSPs regularly list customer experience as an important driver for digital transformation, many customers continue to find it difficult to do business with them via any channel,
anywhere, at any time.
Ensuring a positive customer experience entails more than collecting metrics; it is about the entire experience. Starting with the upfront buying process, operators must turn their full ecosystem of organic and third-party capabilities into compelling offerings that customers can buy through any channel. Once delivered, they must fully support them consistently via those same channels. Doing this requires analytics, machine learning, and automation that are customer-focused and service-aware.
Before and after
While every customer goes on multiple digital journeys every day, there are two distinct customer journeys operators should consider: the journey to becoming a customer and the journey as a customer. The journey to becoming a customer is a typical retail route. At the highest level, it starts with a search for a product or service, during which time the operator has multiple opportunities to engage across a variety of channels. Second is the journey as a customer. As customers use each service, feature, function, and device, it is up to the provider to:
This customer journey is ongoing and enables operators to build a more accurate and detailed picture of each client, their intent, preferences, and behaviors. The
graphic below illustrates both types of journeys.