At one of the sessions at the Text Analytics Summit 09, moderated by Katey Wood of 451 Group, several panelists engaged in a lively discussion about accuracy in text and sentiment analysis software. The most colorful comment came from Chris Bowman, former Superintendant at Lafourche Parish School Board when he noted, "If someone gave you an 85% chance you'd hit the lottery tonight, you'd take it." His point was well taken. There are several industries where 85% may not be good enough, but there are several more where that accuracy could significantly reduce the time and resources it takes to extract, apply sentiment and analyze text-based content. Quantitative data is all about the numbers and the absolute. Qualitative data is all about the words, tones, grammar and language and we are pretty confident in being able to extract valuable information from the text. And while entity extraction and applying sentiment to those entities helps the process along, it certainly doesn't end with that information. Further analysis through systems for predictive modeling, or reporting software, help to paint the full picture. Ask us for a proof of concept - can't hurt. And we know all data is different. If you are even *thinking* of using text analytics, you should know that there are pretty good odds you'll like what you get for results.