Not all insight comes from mathematical computations and statistical algorithms. Online conversations about how your brand or latest product offerings are viewed by your customers can greatly influence the purchase demand of many more customers. Capturing the sentiment feelings of call center conversations can lead to better customer service, or identify new cross-sell / up-sell opportunities with your consumers. Understanding what your customers are saying about your brand, and why, is made easier with KnowledgeREADER. Improve interaction with your customers and discover how terms and phrases used in relation to each other to identify the context surrounding trending themes and topics. Augment net promoter scores or customer satisfaction surveys with a better view of the “sentiment” of your brand.
Identify important changes within sentiment data about how your customers view you and isolate areas to target for improving your customers’ experience, reducing costs or increasing revenue streams.
How It Works
Easy-to-use, detailed and visual document extraction and analysis
Enrich your text discovery process with robust text mining functionality that provides you with access to Natural Language Processing (NLP), sentiment analysis, text discovery dashboard, association discovery maps, document exploration/sentiment markup, classification, and entity and theme extraction.
Best-in-class Natural Language Processing provides you with the most meaningful data insights by breaking down pieces of text into grammatical elements to interpret the vagueness of customer speech.Comparison analysis enables users to compare sentiment to detect similarities and differences in sentiment distribution across datasets, data sources or text analysis conducted at different points in time. Native language packs greatly enhance the accuracy of sentiment analysis and catch many nuances that are usually lost in translation.
- Visual Text Discovery Dashboard
- Sentiment Analysis and Sentiment Categorization
- Extraction of Topics, Themes, Entities, and Sentiment-bearing phrases
- Comparison Analysis
- Trend Analysis
- Syntax Matrix technology
- Association Discovery
- Document Summarization and Sentiment Markup
- Automated creation of a dataset for predictive modeling and association analysis based on text analysis results
- Best-in-class Natural Language Processing (NLP), Sentiment Analysis, Classification, and Entity and Theme Extraction
- Predictive analytics allows you to perform data mining and predictive analysis on merged text and structured data
- Angoss best-in-class Decision Trees and patent-pending Strategy Trees to design and deploy predictive strategies
- Text acquisition using the In-Database connector or data import drivers (from text, Excel, SAS, SPSS, and R data files, and databases)
- Multiple language support for English, French, Spanish, Portuguese, German, Chinese (Mandarin), Korean, Italian, Dutch, Japanese, Malay and Singlish languages
Download the Brochure
Read about best-practices when using Text Analytics to derive insight.