Sentiment Score

How It Is Calculated:

• Scoring Algorithms: Uses algorithms to assign scores based on the detected sentiment in the text. For instance, a score might range from -1 (very negative) to +1 (very positive), with 0 indicating a neutral sentiment.
• Aggregation: Aggregates sentiment scores from multiple interactions to provide an overall view of customer sentiment. This can be done at the level of individual interactions or aggregated over a period for broader analysis.
• Integration with CX Metrics: Combines sentiment scores with other customer experience metrics, such as Net Promoter Score (NPS) or Customer Satisfaction (CSAT) scores, to provide a comprehensive view of customer sentiment and satisfaction.

Benefits:

• Quantitative Measurement: Provides a clear and objective measure of customer sentiment, making it easier to track changes and trends over time.
• Actionable Insights: Helps in identifying areas where customer experience can be improved by highlighting specific aspects of interactions that are perceived negatively or positively.
• Performance Evaluation: Assists in evaluating the effectiveness of customer service strategies and initiatives based on sentiment trends and scores.

Challenges:

• Context Sensitivity: Sentiment scores can be affected by the context in which feedback is given, making it important to consider the broader context when interpreting scores.
• Data Quality: The accuracy of sentiment scores depends on the quality and completeness of the data analyzed. Inaccurate or incomplete data can lead to misleading scores.

Other Terms: