We have witnessed amazing advances in Voice of the Customer (VoC) technology over the last two years. Indeed, our own SandSIV VoC Hub™ product has reached a level of feature maturity that far outstrips our expectations across the past 12 months.
The rapid maturity of Big Data tech has been both an empowering event, enabling us to deliver functional capability far beyond short-term expectations, and also driving force, opening up more possibilities as new tech innovations become mainstream.
However, it can sometimes be a good idea, when faced with such rapid tech growth, to take a step back and make sure we are not simply developing features due to the snowball effect. We need to make sure that the foundations, the main building blocks of our overall Voice of the Customer platform, are solid.
Text mining is one such building block. It is both a major user interface (such as our VoC Mine product), and also part of the underlying technology stack that provides real-time analytics of VoC data.
Step back just a handful of years, and text mining was a clumsy, difficult weapon to wield. Often requiring a major investment in resources to build massive keyword lists, and train usually inaccurate, automated classification/segmentation applications.
Fast forward to today, and things are far different. Our own text mining tool uses advanced Natural Language Processing (NLP) algorithms, such as lemmatization, to make large volumes of Big Data far simpler to mine, much more quickly, and with very high levels of accuracy. Our own text classification engine, VoC Classify, often achieves an accuracy of over 95% in live client environments.
This is the kind of text mining and classification technology we need as the underpinning foundation of the entire VoC technology stack. No matter how many pretty dashboards and clever reports we produce, without accurate, high performance text mining and analytics capability, we are failing to extract best value from the Voice of the Customer.
If you would like to learn more about how SandSIV developed SaaS based text mining and analytics applications work, than please contact us at email@example.com.