Machine Learning For Effective Customer Experience Management-A Telco Perspective

There was a very successful salesperson; she had a very loyal clientele. The reason why she was cherished and loved by her clients was her effective customer service management. To create a warm and courteous relationship with her customers, a rule was set in her office, whenever a client called in to inquire about a product or service, an assistant would take her name and requested her to call back later. In the meantime, our salesperson would briefly skim through her file.

Now when the next time the customer calls, the salesperson would address her by name, ask about her children or work. The personalized experience with the salesperson made every client feel valued, which in turn generated many returning clients for her. Machine learning is simply cost-effective and time-saving automation of this process.

Machine Learning

Machine learning enables computers to make intelligent decisions using data. The computer acts without being particularly programmed such as self-driving cars, speech recognition software, and web search. Self-driving cars, for example, use GPS, navigation services, and an array of sensors to create a 3D model of the environment around them. Data collected is then augmented to make the best judgment of traffic and route. This judgment is precise and very reliable that it is believed using the self-driving car will reduce the number of road accidents to a great extent.

Machine Learning As a Tool For Customer Service Management

Machine learning is an important tool for effective customer service management. It is the science of making computers interact on a more intimate level with customers. Customer data can be used to identify the targeted audience; it can also give an idea of general public demand. Google has been using machine learning for some time, the same web page, if viewed by different people, will not appear the same. The advertisements and links are modified according to every individual’s inclinations and needs.

Uses Of Machine Learning In the Telecom Sector

Machine learning accelerates the digital transformation process allowing companies to be proactive. It is a cost-effective and time-saving means to boost the reputation of your business.

Efficient Customer Management

Machine learning enables efficiency in customer dealing. A customer service representative is provided with all related data at their fingertips. A customer service representative is supposed to cover many areas related to the company’s products and services. By providing access to organized data, the effectiveness of the call increases along with product discovery.

Cost Effective:

Customers might need 24/7 assistance and customer service. A 24/7 customer service is outrageously expensive and limited hours of a call center might not be suitable for the targeted audience. With machine learning, you can include chatbots that respond to customers and once your agents are back to work they can continue conversations.

Increase Customer Satisfaction:

As data generated is customer-specific, based on the needs of the target audience it results in greater customer satisfaction. The data collected through call centers can also be processed to see the pattern of public demand.

Focused Growth:

Data compiled through surveys and customers’ reactions to various campaigns launched by the company gives a better idea of the alignment or the misalignment of the company’s services with customers’ needs. This makes it easier to focus on areas that need betterment.

Attracting New Customers:

By observing the general trend of public demand in a particular sector, makes it easy to launch a campaign for a selected audience. Customer-centric data enables companies to focus on the areas of high demands within their range. Timely action on the feedback will attract new customers.

Customer Contact Management:

Machine learning programs can be used to save and link information of various contacts accounts of the customer. It will provide immediate access to the customer, and it will help develop a customer profile.

Better Behavior Prediction:

Programs using machine learning may be able to predict whether a customer is satisfied with the company. It can predict if a person is going to leave the network or trying to get a better deal. It can also predict how many of the total clientele are satisfied with the services based on their general trend in responding to offers launched by the company.

Better Customer Interactions:

If you can predict the demand of the customer, you are most likely to think of a solution to the problem is ever presented to you. Having all the information about a customer on hand, while dealing with them helps build a stronger bond between the company and the customer. Just imagine the trust you will earn if you can recognize their need before they ever complain to you.

Summary

In the fierce competition witnessed in the modern business world, businesses rise and fall over the internet. The key to winning over customers is by providing a positive customer experience. As a fact, negative customer service stories vibrate louder distorting business image. To cultivate a better relationship with customers you need to understand their needs and desires, so you could provide a solution to them. To understand their needs, you require data. Here’s where machine learning provides you the solution, automates and organizes data, and uses it to make decisions for you very quickly and effectively.

References

1. httlis://www.datasciencecentral.com/lirofiles/blogs/journey-science-in-telecom-take-customer-exlierience-to-the-next
2. httlis://www.analyticsinsight.net/how-machine-learning-imliroves-customer-service-in-telecom-industry/
3. httlis://blogs.sas.com/content/hiddeninsights/2017/05/12/artificial-intelligence-in-telecoms/