Text analytics is the automated process of extracting relevant insights from unstructured text data, uncovering important information quickly and accurately. We empower companies to be more confident and data-driven in their strategic decision making, helping them provide the best customer experiences possible.
Do you want to understand your customers on a deeper level?
Gain insight into the sentiment behind short forms and slang?
Decipher the true meaning behind hashtags when your customers use them?
With Repustate's text analytics, you can do all that and more. You can leverage the in depth voice of the customer analytics that you get from our text mining software for a thorough understanding of your customers. This includes what they are saying about you as well in their reference to your competitors. What’s more, you can also reach out to your customers regardless of their geography and language preference.
Repustate's Text Analytics API is a Natural Language Processing (NLP) technology that applies machine learning to find insights and relationships within your textual data. Our three-step process is simple:
Gather and prepare the data you aim to analyze whether it’s an internal or external data set. To prepare the data for text analysis, all that is needed is for you to put it into a CSV or XLS document format.
Applying Text Analysis API:
Run your input data through our Text Analytics API, and it quickly returns sentiment scores for each relevant topic, aspect, or entity ranging from: -1 for negative emotions, 0 for neutral feelings, and 1 for positive sentiment.
Once our Text Analytics API returns sentiment scorings, they are quickly turned into visual reports consisting of charts, graphs, and tables that make it easy for you to discover trends, patterns, and actionable insights in your data.
Learning to use sentiment analytics is easy! With over 3,000 organizations currently using Repustate’s Text Analysis solution, you’ll be in good company.
Choosing the right solution for conducting text analytics depends on whether you are a local business or international. The solution needs to be completely aligned with your industry and must keep up in speed and scalability. Here are the most important features that the best text analytics solution must have.
The engine should provide accurate results even as you scale.
Feature & aspect classification
So that the tool can unearth insights from any data source and format - web, audio, or video.
Language Detection & Analysis
So you get correct insights in the native language without translations.
The bigger the knowledge graph, the better the semantic context mapping.
So that the engine can process big data in whichever form it is - emails, webinars, product documentation, patient voice notes, VoE data, etc.
So that insights can be viewed in real-time as well as shared among departments and teammates.
Ease of use
So that you don’t need additional staff training to perform analytics tasks.
Ease of Installation
So the engine can seamlessly fit into your current platform without interfering with workflow.
Text analytics is important in many industries like healthcare, finance, insurance, etc. From detecting policy violations to predictive analysis through data pattern recognition, text mining is a key business intelligence tool. Here is a list of real-world text mining applications.
Electronic Health Records (EHR)
Healthcare providers can get key insights for improved patient experience.
You can get a better understanding of what your clients expect.
Companies can take proactive measures to maintain brand positioning and gain insights from VoC data.
Cyberbullying & Threat Detection
You can ensure that community standards are followed in social media comments, videos, and tweets.
Search Engine Optimization
Text analytics allows the engine to identify spam and keyword manipulation for ranking.
Social Media Listening
Brands can have direct engagement with customers, leading to more personalized interactions.
Scientists can find patterns in historical and current data to predict trends in weather forecasting, stock markets, or clinical trials.
Returns & Warranty
Retailers and dealer service professionals across locations use text analytics for returns and warranty processing.
Surveys & Reviews
You can understand complex data in open-ended responses in surveys through text analytics.
Voice of the employee & Recruitment
Companies can find the right candidate, and reduce employee attrition through social media listening and voice of the employee (VoE) data analysis.