Customer Sentiment Analysis using Artificial Intelligence | Financial Industry

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

Digital Driver

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

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Pre-processing of Audio text data.

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Feature selection for selecting the most important features from call.

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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

  • A nondisclosure agreement (NDA) is signed to not disclose any sensitive information revealed over the course of doing business together.
  • Our NDA-driven process is established to keep clients’ data and IP safe and secure.
  • The solution discovery phase is all about knowing your target audience, writing down requirements, and creating a full scope for the project.
  • This helps clarify the goals, and limitations, and deliver quality products & services.
  • Our engagement model defines the project size, project development plan, duration, concept, POC etc.
  • Based on these scenarios, clients may agree to a particular engagement model (Fixed Bid, T&M, Dedicated Team).
  • The SOW document shall list details on project requirements, project management tools, tech stacks, deliverables, milestones, timelines, team size, hourly/monthly rate cards, billable hours and invoice details.
  • On signing the SOW, an official project kick-off meeting shall be initiated.
  • Our implementation approach, ecosystem, tools, solutions modelling, sprint plan, etc. shall be discussed during this meeting.

Our Award-Winning Team

A seasoned AI & ML team of young, dynamic and curious minds recognized with global awards for making significant impact on making human lives better

Awarded Bronze Trophy at CII National competition on Digitization, Robotics & Automation (DRA) – Industry 4.0

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50+

AI & ML
Engineers

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40+

AI & ML
Projects for
reputed Clients

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5 yrs

in AI & ML
Engineering

Awarded as Winner among 1000 contestants at TechSHack Hackathon

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