Natural Language Processing Measured Sentiment Analysis

Business Impact

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One of the difficult tasks for any call center representative or firm is to identify the intent of their customer’s calling.

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Most of the time, Call center representatives are unable to gauge the mood of the customer calling in and end up serving/responding to them in the wrong way. This leads to an increase in negative feedback from customers about the services and products.

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Most firms are facing difficulty in identifying customers’ moods and providing solutions accordingly – hence the dip in their brand value.

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With AI, call centers or any customer support/services firm can now overcome this key setback of being unable to gauge the customer’s sentiment.

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We have developed a model that can understand the mood of the customer and provide appropriate services for the customers.

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This AI model uses a Speech-to-Text model and analyzes a huge volume of calls and segregates call feedback based on the analyses.

Technology Stack

Solution Approach

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Conversion of call audio to text format (Speech to text conversion).

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Feature selection for selecting the most important features from call.

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Pre-processing of Audio text data.

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Building a classification model to predict whether the customer in the call is further serviceable or not.

Trusted and Proven Engagement Model

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  • Our implementation approach, ecosystem, tools, solutions modelling, sprint plan, etc. shall be discussed during this meeting.

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5yrs

in AI & ML
Engineering

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40+

AI & ML
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