Part of EnergyBiz® Network »
Customer Care Group
This special interest group is where customer care professionals share tactics on how utilities are improving interactions with their customers.
Post
AI NLP & NLU engine for better CX in Call Centers
image credit: free
This item is part of the Utility Customer Care - Spring 2019, click here for more
Around the globe, call centers have the same issue as other types of client service centers: they have too much information to investigate. A single call center unit could produce thousands of hours per day of call recording. While it may be feasible to manually listen to prior recordings to verify the performance of a single rep's calls, it is not feasible for a company to obtain business understanding from its broad range of customer call recordings. While it may be feasible to manually listen to prior call recordings to verify the performance of a single representative's calls, it is not feasible for a company to obtain business understanding from its broad range of customer call recordings.
Your access to Member Features is limited.
Already Member? Sign In.
New to Energy Central?
Applying for membership with Energy Central allows you to connect with a network of more than 200,000 global power industry professionals.
The company has these following questions regarding their customers:
What do my clients report about our latest product's durability?
After significant changes to our phone script, do we receive more or fewer refunds?
A sentiment not only suggests clients ' potential intervention, but it can also be combined with other information–such as buying or canceling information. The communication of the client can be good or bad and ultimately affect the bottom line. Angry clients may have a greater chance of churning or refunding. This enables us to uncover the "why" and the "who" behind regular contact subjects and offer a definite, quantified financial action strategy. NLP is used to comprehend and forecast text-based communications trends. Speech Analytics is used to encode the text material of the recorded language.
This encoding allows us to recognize themes for customer support calls, monitor patterns over time, and evaluate operator performance. The NLP engine based on AI tests and analyzes calls and emails. Threads and discussions can be identified by the NLP engine. This will assist in understanding and analyzing the discussions ' feelings, sound, mood, feelings, utterances and other parameters. This will assist to use the clients ' historical information and their attitudes to target campaigns. Historical data helps the next best product to be predicted and recommended. Increasing attention has been paid to the rise of chatbots by natural language processing. These robots can respond quickly to basic customer requests and questions.
Discussions
No discussions yet. Start a discussion below.
Thank Bhagvan for the Post!
Energy Central contributors share their experience and insights for the benefit of other Members (like you). Please show them your appreciation by leaving a comment, 'liking' this post, or following this Member.
Related Special Issue Content
Utility Customer Care - Spring 2019
Get Published - Build a Following
The Energy Central Power Industry Network is based on one core idea - power industry professionals helping each other and advancing the industry by sharing and learning from each other.
If you have an experience or insight to share or have learned something from a conference or seminar, your peers and colleagues on Energy Central want to hear about it. It's also easy to share a link to an article you've liked or an industry resource that you think would be helpful.
Your access to Member Features is limited.
Sign in to Participate