Crafting out a marvellous customer experience management strategy can play a very vital role in affecting the bottom line numbers of an organisation. Today, more and more firms realise the true potential of engaging customer experience to gain competitive advantage. The only problem is the insufficient knowledge of firms to create such experience.

But the truth is, there is no escape to customer experience management, especially for telecom operators, when the ARPU is falling, and profits are diminishing. Let’s support this with some stats:

  • In the U.S., $1.6 trillion is the estimated cost of customers switching due to poor service- Accenture
  • Apparently, 95 per cent of the customers share their bad experiences with others- Zendesk (Figure 1)
  • 45 per cent of the bad experience is shared on social media- Zendesk (Figure 1)
  • By 2018, more than 50 per cent of organisations will implement significant business model changes to improve customer experience- Gartner (See Figure 2)


Customer Experience Management in Telecom

Telecom industry is sitting on the goldmine that requires proper digging. Hence a rigid CXM program will be the game changer for the telecom operators in the years to come. But the strategy that will lay out the winning rules of the game is important. Big Data Analytics is that strategy, a phenomenon that the world is trying to find ways to exploit, and gaining grounds in every telecom business.


Figure 2: Organizations Response to: “Did your organization’s customer experience improvement initiatives during 2014 involve any significant change of business model?” leading to the conclusion about the SPA

Source: Survey Analysis:
The State of Customer Experience Innovation, 2015, Gartner

The telecom industry is bombarded with conventional data for years now, from simple calls, billing details, Call Detail Records (CDR), Event Detail Reports (EDR), etc. In the last few years due to smartphone proliferation, technology convergence, intelligent networks, and mobile applications, there is a demanding need to convert these data-rich repositories into actionable insights that can provide the much-needed competitive advantage.

Can Customer Data Enable a Better CX Strategy?

However, to gain actionable insights, telecom operators need to know what to do with the extensive data and to leverage it to the fullest. This is where big data analytics steps in.

Access to data is not the challenge, however, harnessing the right data is. When operators get their hands on the right and meaningful data, it can help them to:

  • Transform business operations to achieve excellence
  • Deliver better services to generate new revenue streams
  • Develop better networks for consistent and high-quality service
  • Personalize the offering of services and increase ARPU
  • Improve customer loyalty
  • And not the least fraud management

Using Big Data, telecom providers can get more profound and real-time insights into:

  • Customer behavior
  • Customer service usage patterns
  • Customer preferences and interests

Using Big Data Analytics in Telecom

In telecom, there are multiple sources of structured and unstructured data. Some examples of structured data for Telco’s include call details, billing details, e- records, records of the location, and more. On the other hand, unstructured data consists of call management data, blogs, textual data, website content, data from audio/video, performance data, errors, social media, etc.

With proper big data analytics, there is a lot that can be achieved from such data. One of the vital benefits is fraud detection in telecom. Millions in revenue loss can be saved if voice and data frauds are observed and detected faster, thus preventing further misuse.

With real-time (or predictive) analysis of data from network sources, telcos can track traffic in real- time and manage the network to avoid congestions in peak periods. A proactive incident management system can be put into effect by identifying and resolving incidents before they occur.

Another key benefit is strategically identifying and running personalised campaigns through the real-time contextual information of customers. For instance, operators can launch social-based marketing campaigns, based on the insights drawn from customer’s social behaviour and telecom activity.

An example would be, a customer using 3 GB data pack every month. Suppose his data usage extends, leading to additional billing for a particular month. For operators, this is the potential customer for upgrading to a 4 GB data pack with a higher tariff. Big data analytics can help identify such customers and send a subsequent promotional message. What’s the positive effect of this? A happy customer and some extra pennies for the operator!

Data analytics also gives insights into value-added services that customers want, such as eHealth, mobile payments, astrology, and vehicle telematics. These services supported by data analytics will open additional revenue streams for telecom operators.

A segmentation outcome of big data analytics is the ‘Customer Migration Segmentation’. Such a segmentation allows operators to distinguish clearly between those customer segments that are increasing in value and those that are headed downwards. Big data has now allowed the operators to identify the low-churn segment that is at risk of migrating downward in value.

Big Data vs. CX – Near Future

In today’s world, customer satisfaction is not the key. Instead, personalization (read customer delight) is the key to success in any industry. Operators need to turn to optimise their processes with predictive analytics of user data (even real time analytics is insufficient).

Converting the data into actionable real-time information is an arduous task to tackle. However, if the service providers want to have a user-defined architecture for better customer experience management, this will be a compulsion in the years to come.

The challenges of taming big data to achieve actionable insights lie in the ability to collect and analyses the data. Operators now need to move beyond the hype of “cost-intensive parameter of big data” and deploy it successfully to reap the potential benefits to build, run and market their services.

More personalised service offerings of data analytics not only reduce the churn but also increase the revenue. In the future, big data implementation will become a fundamental pillar of network planning, and hence operators must start planning in that direction, from now!



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