Even in this multichannel world, customers still prefer to call in and hence voice channel is critical to a business. These days’ businesses are coming to a standstill when it comes to listening to conversations that flow through their voice channel as they are stuck on sampling and high cost manual monitoring. A recent survey showed that it is important to link online marketing to offline sales.
Mining for the truths and hidden meanings from these conversations is crucial. Previously automatic data mining of the voice channel was unattainable. But now with conversation analysis it is possible. Being in the century of customers, the ability for the company representatives to understand the customer, be empathic and deliver fast solution is essential.
Thanks to conversational analysis or text mining, it is now possible to extract data from conversations, to automate and process this data in real-time and at scale. Thus listening to and analyzing conversations helps the representatives to build better relationships and in turn provide customers with the experience they expect.
Sigmaway provides text mining solutions for businesses. Contact us at contact@gosigmaway.com for a proof of concept.
Read more at: http://smartdatacollective.com/calljourney/304151/are-you-listening-your-conversations

A computer technology company wanted an automatic solution to classify customer problems and complaints that were posted on the company's Tech Forums as well as agent transcripts associated with customer calls that were stored in databases. It wanted a "text mining and codification engine" to which Natural Language Processing could be applied to categorize conversations automatically and thus aid Microsoft in analyzing text data objectively and quantitatively. The solution provided had four major milestones: Data Access, Data Loading, Classification Design, Development Accuracy, and Validation Accuracy. The text mining framework provided was able to categorize the texts automatically into five stages of classification. Thus with the assurance of accurate results, the company was able to take quick informed decisions based on customer feedback. Read more at: http://analyticsindiamag.com/advanced-text-mining-by-extracting-insights-from-various-forums-helps-in-addressing-and-analyzing-customer-feedback/

Text mining, which is sometimes referred to "text analytics", is one way to make qualitative or "unstructured" data usable by a computer. Also known as text data mining, refers to the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning. Text mining usually involves the process of structuring the input text, deriving patterns within the structured data, and finally evaluation and interpretation of the output. 'High quality' in text mining usually refers to some combination of relevance, novelty, and interestingness. Typical text mining tasks include text categorization, text clustering, concept/entity extraction, sentiment analysis etc. Text analysis involves information retrieval, analysis to study word frequency distributions, pattern recognition, tagging, information extraction, data mining techniques including link and association analysis, visualization, and predictive analytics. The main goal is, essentially, to turn text into data for analysis, via application of natural language processing (NLP) and analytical methods. To read more about text mining: http://www.scientificcomputing.com/blogs/2014/01/text-mining-next-data-frontier.

Internet search engines like Google, Yahoo or Bing are like large knowledge repositories - they provide you with any information you want. But, there is a condition - you have to type right keywords. Everyone one of us knows this.

How many times have you got the right search results you expected? It can be never 100% correct, even though you thought of the keywords carefully. Here comes the accuracy of the search engines, and improving this accuracy between what you type and what results you get is of utmost importance to the search engine providers. Behind the wall, lots of text analytics are involved.  What you normally type in the search box is an unstructured content and the search engine's job is to analyze, extract meta data and index it to convert the content into a structured one. The query is made upon the indexed data, after which the results are shown to you. What makes search engines different is the ability to add context, extract meta data from unstructured content, and index them so that accurate search results are shown to the extent possible.

What text analytics are involved here? Know them here: http://www.business2community.com/big-data/text-analytics-important-search-0889955#!PueWW .