What is text analytics?
Text analytics uses statistical and machine-learning techniques to derive quantitative insights and patterns from textual data. It is closely related to text analysis, which focuses more on qualitative analysis of text content.
Benefits of text analytics
Some key benefits of text analytics include:
- Scalability - It allows businesses to analyze vast amounts of unstructured text data quickly and efficiently, far beyond what would be possible manually.
- Real-time insights—Text analytics tools can process streaming data to provide immediate insights from sources such as social media and customer feedback.
- Consistency - Automated analysis applies consistent criteria across large datasets, avoiding human errors and biases.
- Actionable insights—It can reveal trends, patterns, and insights that would be difficult to detect manually, enabling data-driven decision-making.
- Cost and time savings - Automating text analysis saves significant time and resources compared to manual processing.
- Improved customer understanding—Companies can better understand customer needs and sentiments by analyzing customer feedback, reviews, support tickets, etc.
- Competitive intelligence - Analyzing competitors' content, reviews, etc., can provide strategic insights.
- Enhanced productivity - It frees up human resources from tedious manual text processing to focus on higher-value tasks.
- Fraud detection - Text analytics can help identify suspicious communication patterns, documents, etc.
- Product/service improvement - Analyzing feedback helps identify areas for improvement in offerings.
