CESTS

CUSTOMER ENGAGEMENT SENTIMENT TRACKING SYSTEM (CESTS)

Introduction

In the current competitive scenario, excellent customer service is not any option, but rather a need of the hour. The conventional forms of feedback like post-call surveys and IVR-based ratings cannot provide the exact essence of customer sentiment. To address such deficiencies, we have proposed the Customer Engagement Sentiment Tracking System or CESTS, which is an in-time system that will further enhance the quality of the interaction between the customer and the agent by engaging advanced AI technologies.

The Problem with Existing Feedback Systems

  1. CESTS is a system created with the aid of artificial intelligence, which takes into consideration voice, language comprehension, and pattern matching for the provision of customer sentiment analysis. Below is the procedure:
  2. Call Recording and Transcription: The device records a user 's speech and the corresponding text is generated through the speech recognition.
  3. Sentiment Analysis: The approach examines diction and intonation in order to categorize customer sentiment as positive, neutral or negative.
  4. Real-Time Feedback: As would be expected, this aspect of the system presents real time useful comments to the agents, expected to enhance their communication skills.
  5. Dynamic Interaction Tracking: This involves finding out how the customers’ emotions are changing and helping the agents to address such changes instantly.


Solution:

CESTS is a system created with the aid of artificial intelligence, which takes into consideration voice, language comprehension, and pattern matching for the provision of customer sentiment analysis. Below is the procedure

  • Call Recording and Transcription: The device records a user 's speech and the corresponding text is generated through the speech recognition.
  • Sentiment Analysis: The approach examines diction and intonation in order to categorize customer sentiment as positive, neutral or negative.
  • Real-Time Feedback: As would be expected, this aspect of the system presents real time useful comments to the agents, expected to enhance their communication skills.
  • Dynamic Interaction Tracking: This involves finding out how the customers’ emotions are changing and helping the agents to address such changes instantly.





Key Features:

  1. Automated Feedback Generation: Creates comprehensive feedback using LSTM model, so that nothing is left out.
  2. Targeted Agent Enhancements: Provides specific communication strategies to resolve customer issues.
  3. Scalability: Churned call center has the advantage of being based on a cloud platform which alleviates any worries on the ability of the center to cope with high and low volumes calls.
  4. Data Privacy Compliance: The system follows the provision of GDPR as well as the CCPA so as to safeguard any confidential data belonging to clients.

Advantages:

  • Customer Satisfaction Exceeds: With insight on the emotions of the customers in real time, it is possible to react appropriately and with a lot of empathy.
  • Agent Performance Improved: Actions are provided to the agents so that they can improve on their communication skills.
  • Improved Record Keeping: Provides a precis of the major mentions of key issues made in calls.

Challenges and Solutions:

  1. LSTM
  2. Speech-to-Text Accuracy: Fine-tuning of a number of advanced NLP models for the ability to process language.
  3. Real-time Processing: Achieving scalability using a cloud-computing infrastructure.

Future Scope:

  • Multilingual Support: Extend languages and regional dialect support.
  • Video Sentiment Analysis: Incorporate facial recognition for analysis of emotions from video calls.
  • Predictive Analytics: Use sentiment data for forecasting customer wants and issues.
  • Integration Across Platforms: Extend into email and chat channels primarily regarded as text-based.

Conclusion

The Customer Engagement Sentiment Tracking System (CESTS) is more than just a feedback tool it’s a step toward revolutionizing customer service. By combining advanced technologies with real-time insights, CESTS ensures a deeper understanding of customer emotions, empowering businesses to deliver personalized, empathetic, and effective service. The future of customer engagement lies in understanding what customers truly feel and CESTS makes it possible.



FAQ:

1. What is the Customer Engagement Sentiment Tracking System (CESTS)?

CESTS: A sophisticated AI-powered solution for real-time customer sentiment analysis during support calls It records the voice commands, converts them to text format and uses Natural Language Processing (NLP) and ML algorithms(LSTM) to classify customer sentiments into positive, negative, or neutral.



2.How does CESTS enhance customer support engagements?

By analyzing customers' words and intonation, CESTS gives real-time feedback to agents. This enables agents to modify their communication style, provide sympathetic responses, and address issues more efficiently during the call.



3. What technologies power CESTS?

CESTS employs a combination of the following:

Speech Recognition: It converts spoken words inputs into text.

Natural Language Processing(NLP) : Analyzes textual data, providing insight into sentiment.

Now, using machine learning: It uses models like LSTM for classifying and scoring sentiment.

Cloud Computing : Brings elasticity and sub second processing.


4.How does CESTS safeguard data privacy?

Through specific mechanisms, CESTS adheres to the data privacy regulations such as GDPR and the California Consumer Privacy Act (CCPA) in the following ways:

Controlling customer data using encryption.

Get explicit consent of processing data.

Restricting access to data only to those with authority to use it.


5. Is CESTS multi-linguistic supportable?

Currently No, CESTS does not support multiple languages. However, in the future, we plan to implement multilingual support to cater to a broader international audience.


6. What are CESTS' core capabilities?

Real-Time Sentiment Analysis: Classify the sentiment in real-time during the call.

Active Feedback: It gives actionable suggestions to the agent in real-time.

HOLISTIC DOCUMENTATION : Summarizes the call with robust automated highlights.

Scalability: High call volume is easy to manage as cloud infrastructure has been utilized.


7. In what ways is CESTS different from traditional systems of feedback?

CESTS differs from the classical systems like Google Forms or IVR ratings as it operates in real-time and gives rich emotional insights while permitting agents to alter their behavior on the same call. In this manner, delay and poor response rates characterize post-call feedback systems that CESTS avoids.


8. Which business streams would be interested in using CESTS?

The solutions of CESTS have a range of applications in multiple industries, such as services in the following domains:

Customer Support: To improve the experience of call centers

Healthcare: To measure the patient satisfaction during remote consultation.

Education: To measure the engagement of students in online learning .

Retail: To measure the emotional responses of the customers after sales.

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