Optimising Customer Support Services with Machine Learning
Enterprises have been using Machines to improve efficiency and productivity for long, though it may be advance machinery or shifting to robotics or cobots to further improvement, the need to increase efficiency is consistent. Machine Learning is the next thing which is helping enterprises to use the machines to improve and work more efficiently.
Customer Support is undoubtedly one of the biggest cost centers in modern-day operations, for big or medium scale businesses.
And Customer Support is also considered as one of the most complex parts as well.
Well does it really need to be one? the straight answer is ‘No“
Machine Learning is already set to bring in a major role in resolving challenges in a customer support function.
What is Machine Learning (ML)
ML is one of the parts of artificial intelligence (AI), it is a set of techniques that provides systems or computers an ability to automatically learn without being actually programmed. It can read the data whether it may be structured or unstructured and discover insights.
How does it help in Customer Support
When it comes to Customer support ML provides a higher level of convenience to the customers and efficiency to the support staff.
CS means a lot of data, of which the major part is an unstructured one. This data that is gathered through everyday conversion and communication which contains deep insights, ML when used intelligently can be helpful in understanding the customers, their thinking, wishes and so on.
How is Machine Learning used in the CS environment?
Here are quick top picks
Understanding the Intent
Most of the time your agent does not know why is customer contacting you or where probably he is asking for help.
Machine Learning can help CS agents predict the same. Machine learning collects data about a customer’s previous browsing, geo-events, contact pattern, and other online behaviors. That allows agents to plan and prioritize the customers need. In a way your agent provides personalized services to the connecting customer, assuring elevated user experience.
Timesaving – a win-win situation
Well, what is mostly observed by the researchers, people prefer getting in touch with customer support is through chat or messaging app option. that’s where chatbot comes in the picture.
While, chatbots are something that is equally disliked by people, when used intelligently it can have a greater impact. for instance, if a chatbot can extract what exactly the customer is looking from the text types, further tag it correctly, to direct it right customer support specialist, can bring in a win-win situation for both.
it saves time for the customer, saves time for an agent, reaches the right SME and improves the overall experience
With IoT, companies are now able to practically track their devices even while the customer is using it. For example, a Smart Machine connected to the internet can send back a signal to the manufacturer when a fault or unusual operation takes place. The manufacturer can get back to owning the company to inform arising issues with the required solution.
Virtual assistance is helping customers during their journey, providing insights to customers as well as feeding the analytic program at the back-end for future reference.
ML can help a enterprises to virtually assist the customer right from buying stage to finding out resolution when he is facing any issue. ML can also help in pushing a product which customer has checked or liked based on his online behavior, it can trigger alerts or updates to the customers.
While these are only a few things listed here, there is a long list where ML can help in optimizing Customer support.
To list a few – customer data capture, classification, proactive emailing, perform root-cause analysis of repetitive instances, reduce interaction time.
Crafsol with its ML and AI services has strong experience of building custom solutions for enterprises.
Get in touch to know more how we can help you in your fasten your customer support services.