Text mining software for Business Intelligence
Text mining software has become the foremost tool in the field of business intelligence based upon predictive analytics. This is because the most actionable data is found within unstructured text such as customer feedback forms or internal company documents. One of the first tasks that text mining software perfoms is to add structure in the form of topic grouping and/or sector sorting by similar characteristics or context.
It’s not enough anymore to catalog historical data on sales or marketing habits, no matter how recent. It has become necessary to be able to predict customer trends and to be able to target marketing strategies toward those aspects. This means it is necessary to keep demogrphic data such as age, and location relative to sales outlet. Then, keeping track of behaviors such as buying habits like type, amount spent and timing of purchases, where customers buy, and even where they click on sales web pages. None of these characteristics are static. They are continually changing and that makes them predictive.
The key is to analyze customer models based upon the habits and characteristics mentioned above. This can be done in many ways, but a growing number of client inputs hve been found by exploiting social media, such as customer interaction with companies’ Facebook and Twitter sites. Marketing experts have found this to be an excellent way of gauging sentiment about products and even company policies.
Since tens of thousands of Twitter users can simulatenously participate in the same major event (television specials, web events, concerts, etc.) and, at the same have the capability to enter real-time comments and opinions, social media has become an excellent means for gauging public sentiment. This massive accumulation of customer data requires analytic software that can discover business value in the attitudes of social media participants. The results are creating accurate estimates in the feelings–positively or negatively–about a certain company, team, political candidate, or event. Measuring public opinion is not an easy target, but Twitter and the people using predictive software give a real-time view into the aggregate participants.