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Customer Sentiment Analysis

Care interaction sentiment — from chat transcripts, email content and survey responses — is not systematically analysed, making it impossible to detect deteriorating customer experience signals at scale.

Sentiment AnalysisNLPTrend Detection
LowBusiness priority
Customer experienceDomain
4Main data sources

The problem

Care interaction sentiment — from chat transcripts, email content and survey responses — is not systematically analysed, making it impossible to detect deteriorating customer experience signals at scale.

The AI approach

NLP sentiment analysis applied to all care interactions. Aggregate sentiment scores tracked per subscriber segment, care team, product and time period. Negative sentiment spikes trigger proactive outreach and operational review.

How it works

  1. 1
    Capture

    Collect calls, chats, emails, surveys and social posts.

  2. 2
    Analyse

    Score sentiment and detect topics and emotions.

  3. 3
    Aggregate

    Track sentiment by journey, product and region.

  4. 4
    Act

    Alert teams to falling sentiment and urgent cases.

Data it uses

Care Interaction TranscriptsSurvey ResponsesComplaint DataCRM

How to measure value

Practical tips

Standards & references

Data governanceUse governed, consented data only
Responsible AIExplainable, monitored, human-in-the-loop

Related pages

This page describes generic industry practice and public standards. It is not based on, and does not describe, any particular vendor's product or operator's systems.