Telecom is one of the most advanced industries when it comes to understanding customer behavior and consumption. In the past decade, telecom industry has seen massive technological advancements. This technology, backed by structured data, makes a very strong case for better customer management.

Currently, the biggest growth driver in telecom is data. Customers demand high-speed data as well as high volumes of data. This need is increasing as customer transactions are moving online. Big telecom companies have understood these changes. Using their role as a service provider, they have started building an eco-system to cater to this need.

Telecom companies are moving towards Penta play. (providing wireline for home calls and WiFi). They support the IOT play to create a new marketplace for on-demand digital TV and movie channels. Customers are paying a high subscription cost for channels, even though they do not watch all. With a faster and upgraded eco-system, there would be a huge demand for smart TVs. Telecom players would be venturing into this arena.

As the market evolves, telecom companies need to provide a seamless customer experience. This experience also needs to unique, while fulfilling the customer requirements.

With a few changes in operations, telecom companies can adapt to the environment. They can thus provide a better customer experience than ever.

New Age of Training for Better Customer Experience

Many companies still stick to the old methods of training associates. They start with soft skills and move on to product-related training.  This method of training is fast becoming irrelevant. Modern feedback systems assess ASAT (Agent Satisfaction Score). They measure the quality of customer interaction provided by each agent. Based on the scores, associates can be high scoring, average scoring, or low scoring agents. Using text analytics, customer feedback is also used to analyze the associate’s performance.

These inputs define the areas that each agent needs to improve. The training manager can then work with the agent to strengthen his weak areas. Low scoring agents undergo training and monitoring until their performance improves.

With machine learning, it’s easier than ever to increase the quality of customer support. Training has also become easier by focusing on the weak areas, rather than on every aspect.

Currently, all the training are reactive. But, companies can move to a more proactive training process by:

  • Listening to its customers on social media and other platforms
  • Arriving at a list of top topics or emerging topics of interest.
  • Training the sales team on those topics.

This not only reduces repeat calls but also enhances customer experience. Training and retaining top performing associates is a major step in achieving consistency.

Voice-to-Text

The second biggest issue in associate management is human error during data entry. Entering wrong data into the CRM makes it difficult to take accurate and quick decisions. It also introduces a delay in responding to the customer and resolving issues. Some customers are also likely to not get any resolution, creating a bad experience.

Voice-to-text analyses on customer and agent speech help companies reduce error rates. This tool can also provide customer sentiment and modulation analysis. Currently, this system is very expensive and languages supported are few. So operators are using Voice-to-Text only in the case of high-value customers. In the future computation speeds  are going to increase and storage costs are bound to come down. Then, more languages and dialects would be added and this technology could be used on a wide base.

Customer Journey

As with any business, understanding the customer journey is crucial in telecom. Each customer of the company undertakes a different journey with a personal goal in mind. If the organization knows in advance his roadmap, supporting him would be much easier.

A typical customer’s journeys include- buy, sell, explore, get support, setup, use etc. . A company can understand this journey using customer feedback, text analytics and structured data. Knowing how the customer reaches out can help you fine tune your communication.

For example, assume there are two customers who have similar usage and recharge patterns but have an issue with their data packs. Using journey roadmaps, the company can understand each customer in detail. In the first case, the organization understands that this customer is new, and is exploring data. He needs more support to understand his handset, how he can use data and how he can solve minor issues by himself. In the second case, the customer is a long-time user and is well versed in such information. The company can solve his problem and even give him a higher consumption plan.

This illustration clearly gives a proper method to address each customer based on his journey in the organization. Implementing such a practice not only brings down repeat calls but would make his experience much better.

Alternative Systems

  • Smart Assist – One of the pain points which every customer faces when he calls the support center is the static IVR. He is forced to go through the entire flow, in spite of knowing what he wants. Here, he looses a lot of time and would never be happy with the experience. In such cases implementing Smart Assist would solve the issue and create a good experience. Based on customer transaction, it can predict why he might have called. Alternately, it can allow the customer to speak through his phone and directly go to the menu of his choice (voice based selection). This not only saves considerable time but also helps in giving precise information to the customer. Smart Assist predicts his problem by looking at his previous issues and his current plan. As the machine is self-learning, it improvises over time and provides a better experience to customers. It reduces manpower and training costs as well. It gives accurate tagging and other information to the organization to make quick and informed decisions.
  • Chatbot– This is one service that every telecom operator can provide. A Chatbot is a part of any company’s digital transformation journey. Chatbot frees up customer centers to resolve larger issues, while it handles a majority of the minor issues. Bots can also take requests from customers and raise CRM tags. They can also keep the customer updated, during their processes.

Future of customer experience would be a combination of structured and unstructured analytics. Digital transformation services such as Chat Bot and Smart Assist would help, solve and record information.  They would also use this information to provide seamless personalized experience to customers. In the future, most of the retention and acquisition games are not going to be built around price but on customer experience management.

 

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