Artificial Intelligence, Mixed Data Analytics and Passive Listening Capture Minds - 2016 Insight Innovation Exchange
I’m just back from the IIEX conference in Atlanta, where OdinText competed in the Insight Innovation Competition. Although I was disappointed that we didn’t win, I’m pleased to report that the judges told me we placed a very close second.
Attending conferences like this affords me the opportunity to get a pulse on the industry, and I was struck by the fact that text analytics are no longer viewed as a shiny new toy in market research. In fact, as someone who has been working in the natural language processing field for so long, it’s actually somewhat remarkable to see how perceptions of text analytics have matured over just the last year. Text analytics have become a must-have, and the market has a new wave of healthy competition as a result, which I think is further evidence of a healthy market.
Since OdinText goes beyond just text data and incorporates mixed data—text and quantitative—in our competition pitch we highlighted OdinText’s ability to essentially enable market researchers to do data science.
I strongly believe making data science more accessible is a huge opportunity that OdinText is uniquely positioned to solve, and it’s an area where market researchers can step up to meet a desperate need as we currently have a shortage of about 200,000 data scientists in the US alone.
(Check out this 5-minute video of my IIEX competition pitch and let me know what YOU think!)
You are also most welcome to download a PDF of the PPT presentation >>>
“Machine learning” appears to be the new buzz phrase in research circles, and at IIEX I was hard pressed to find a single vendor not claiming to use machine learning in some respect, no matter where on the service chain they fit. Honestly, though, I got the sense that many use the term without entirely understanding what it means.
We continue to leverage machine learning where it makes sense at OdinText, and there are a few other vendors out there who also clearly have an excellent grasp of the technique.
One such company—which took first place in the competition, in fact—was Remesh. They’re actually using machine learning in a very unique and novel way, by automating the role of an online moderator almost akin to a chat bot. They’ve positioned this as AI, and to replace humans completely with a computer is a holy grail for almost any industry.
I’m optimistic on AI in my field of data and text mining as well, but we’re still a ways off in terms of taking the human out of the mix, and so our goal at OdinText is to use the human as efficiently as possible.
While totally automating what a data scientist does is appealing, in the short term we’re happy with being able to allow a market researcher to do in a few hours what would take a typical data scientist with skills in advanced statistics, NLP, Python, R and C++ days or weeks to do.
Still I admit the prospect of AI replacing researchers completely is an interesting one—albeit not necessarily a popular one among the people who would be replaced—and it’s an area that I’m certainly thinking about.
Third place in the competition I understand was Beatgrid Media, which leverages smart phones (without using almost any battery life) to passively listen to audio streams from radio and TV and overlaying geo demographics with these panelists’ data to better predict advertising reach and efficacy. This is admittedly going to be a very hard field to break into by a start-up as there are many big players in the space who want to own their own measurement. And so this may have been one of the reasons Beatgrid had trouble taking more than third, even though they admittedly have some very interesting technology that could perhaps also be applied in other ways.
Let me know what you think!
(And if you’re interested in a demo of OdinText, please contact us here!)
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[NOTE: Tom H. C. Anderson is Founder of Next Generation Text Analytics software firm OdinText Inc. Click here for more Text Analytics Tips]