Machine Learning Implementation With IVR
Earlier human work was preferred over a machine because a human was more accurate than a machine. After all a human could look at all angles and make an informed decision, and a machine could not.
But due to the machine learning today, machine might be more useful than a human in shaping customer experiences.
Machine learning (ML) is a type of Artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed.
Machine learning receives input data and uses statistical analysis to predict an output value.
Today machine learning can help brands scale their engagement operations and provide increasingly relevant experiences.
Machine learning has been actively deployed in multiple applications, it has been only a few years ago since it started showing up in customer experience applications. In the future will help us to create targeted and personalized customer experiences.
Now coming to the context of IVR, Now a days most IVR system has 4-9 choice and may be more due to IVR sub menu design. Also they are fixed choice, customer has to select anyone to go ahead.
Now there are two main issue with this:
- IVR choice is not much customer friendly as sometime customer’s issue could not fit on any of the choice given, so they used to select wrong choice, that result in to transfer the call into wrong team.
- Selection of choice of IVR taking time as customer has to listen all the menu choice.
Now due Machine Language implementation in IVR system, making the life of customer easy so improve overall customer experience.
- Faster and more efficient customer service : with machine learning and ASR (Automatic Speech Recognition), customers can now speak in their own words to the company, and the company will be able to understand more quickly what the customer needs, and solve their problem faster.
- Customer Analytics: Analytics takes information from customer data and uses it to predict future trends and behavior patterns. From a customer service perspective, predictive analytics help anticipate when a customer that’s shopping on your website will need agent help. It allows you to identify contact valuable prospects before they contact your agent, or even help you with inbound contact center volume based on the behavior of your customers online. Also you can get the idea of why a customer is contacting you again and again.
- Improvement through data: With machine learning, contact centers can improve the customer experience by teaching their software to remember and learn from past experiences. Contact centers can fine tune algorithms so they’re more accurate and teach their CRM programs. This costs much less than training a live agent.
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