As technology advances, organisations are driving all their energies into leveraging the most modern capabilities in order to boost their revenues. As data becomes an indispensable part of businesses, very often organisations struggle with gaining insights into the massive pool of unstructured data. However, with text mining, you don’t have to search too hard to discover relevant and important insights that would otherwise remain buried. Forward-thinking companies today are making the most of text mining and analytics that is enabling them to uncover trends and patterns and use them to improve products, enhance customer experiences and business revenue.
What is Text Mining?
With the popularity of big data platforms and deep learning algorithms that can analyze humongous amounts of data, text mining has become extremely important in deriving high-quality information and insights from unstructured text data. Using several statistical techniques, text mining structures input text, derives patterns from it and evaluates and interprets it to unearth patterns and trends. Text mining can enable organisations to discover critical insights in vendor documents, customer communications, call center logs, customer surveys, social media posts and other sources of text-based data. Today, text mining is also being used to train AI chatbots and virtual agents to enable quick, automated responses for improved customer experiences.
How does it work?
The purpose of text mining is to process unstructured textual data, extract meaningful information and make it accessible to the various statistical algorithms such as natural language processing, association analysis, visualisation and other analytical methods. Text mining involves a series of sequential steps in order to unearth important insights from huge amounts of text:
- Data organisation to structure the data for better qualitative and quantitative analysis
- Information retrieval to get information relevant to need from a collection of resources
- Lexical analysis to study word frequency distributions and uncover the meaning
- Pattern recognition to recognise patterns and regularities in data
- Information extraction to extract useful information from unstructured or semi-structured data
The Power of Text Mining
In an age of information overload, text mining enables organisations to either extract information to derive summaries for the words contained in the documents or compute summaries for the documents based on the words contained in them. By examining words or clusters used in documents, they can determine similarities and understand how they are related to other variables of interest. Here’s how companies can use text mining as a powerful tool:
- Analyse survey responses: In survey research, marketers often include various open-ended questions to enable respondents to express their views without constraining them to a particular response format. Text mining can yield insights into customers’ views and opinions that might otherwise not be discovered. You may discover a certain set of words or terms that are commonly used by respondents that can enable you to get a better understanding of their opinion and perception about your product or service.
- Understand customer sentiment: Text mining is also popularly used to track customer sentiment about a company. Common threads that point to positive or negative feelings can be identified from online reviews, social networks, customer service interactions, company emails, and other data sources. Such information can be used to detect and fix product and business problems, identify new features that customers desire, strengthen product offering, improve customer service and plan new marketing campaigns, among other things.
- Screen job candidates: With companies receiving hundreds and thousands of resumes every day, it becomes increasingly challenging for them to identify relevant ones from the mess. Text mining can be used to screen job candidates based on the words used in their resumes, assess their relevance, and even capture conversations and forward them to hiring managers before setting up interviews. Text mining can also be used to send prospective candidates automated responses to queries about job profile or company culture.
- Equip chatbots: With chatbots gaining popularity across various sectors, text mining can be used as a great tool to equip chatbots and train them to answer questions about products and handle basic customer service tasks. By using natural language understanding (NLU) technology, chatbots can achieve reading comprehension and understand concepts, identify objects, extract sentiment and respond appropriately.
- Automatically process emails and messages: Text mining can also be used for automatic classification of texts. Based on certain terms or words that are not likely to appear in legitimate messages, organisations can identify undesirable messages, filter out junk email and automatically discard them. Such processing can help route relevant messages to the most appropriate department or agency for further processing.
Improve Business Outcomes
The power of text mining in today’s highly competitive world is irrefutable. From analysing survey responses to understanding customer sentiment, screening job candidates to equipping chatbots – the application of text mining is widespread. In addition, text mining can also be used to block spam emails, classify website content, detect fraud, predict customer churn, enable risk management, etc. By categorising and clustering text, text mining helps in interpreting large data sets and extracting crucial information about things that matter. The findings can help companies drive strategies and actions for improved business outcomes.
