Text Analytics Tips

December 31st, 2015

Text Analytics Tips, with your Hosts Tom & Gosia: Introductory Post

Today, we’re blogging to let you know about a new series of posts starting in January 2016 called ‘Text Analytics Tips’. This will be an ongoing series and our main goal is to help marketers understand text analytics better.

We realize Text Analytics is a subject with incredibly high awareness, yet sadly also a subject with many misconceptions.

The first generation of text analytics vendors over hyped the importance of sentiment as a tool, as well as ‘social media’ as a data source, often preferring to use the even vaguer term ‘Big Data’ (usually just referring to tweets). They offered no evidence of the value of either, and have usually ignored the much richer techniques and sources of data for text analysis. Little to no information or training is offered on how to actually gain useful insights via text analytics.

What are some of the biggest misconceptions in text analytics?

  1. “Text Analytics is Qualitative Research”

FALSE – Text Analytics IS NOT qualitative.
Text Analytics = Text Mining = Data Mining = Pattern Recognition = Math/Stats/Quant Research

  1. It’s Automatic (artificial intelligence), you just press a button and look at the report / wordcloud

FALSE – Text Analytics is a powerful technique made possible thanks to tremendous processing power. It can be easy if using the right tool, but just like any other powerful analytical tools, it is limited by the quality of your data and the resourcefulness and skill of the analyst.

  1. Text Analytics is a Luxury
    (i.e. structured data analysis is of primary importance and unstructured data is an extra)

FALSE – Nothing could be further from the truth. In our experience, usually when there is text data available, it almost always outperforms standard available quant data in terms of explaining and/or predicting the outcome of interest!

There are several other text analytics misconceptions of course and we hope to cover many of them as well.

While various OdinText employees and clients may be posting in the ‘Text Analytics Tips’ series over time, Senior Data Scientist, Gosia, and our Founder, Tom, have volunteered to post on a more regular basis…well, not so much volunteered as drawing the shortest straw (our developers made it clear that “Engineers don’t do blog posts!”).

Kidding aside, we really value education at OdinText, and it is our goal to make sure OdinText users become proficient in text analytics.

Though Text Analytics, and OdinText in particular, are very powerful tools, we will aim to keep these posts light, fun yet interesting and insightful. If you’ve just started using OdinText or are interested in applied text analytics in general, these posts are certainly a good start for you.

During this long running series we’ll be posting tips, interviews, and various fun short analysis. Please come back in January for our first post which will deal with analysis of a very simple unstructured survey question.

Of course, if you’re interested in more info on OdinText, no need to wait, just fill out our short Request Info form.

Happy New Year!

Your friends @OdinText

Text Analytiics Tips T G

[NOTE: Tom is Founder and CEO of OdinText Inc.. A long time champion of text mining, in 2005 he founded Anderson Analytics LLC, the first consumer insights/marketing research consultancy focused on text analytics. He is a frequent speaker and data science guest lecturer at university and research industry events.

Gosia is a Senior Data Scientist at OdinText Inc.. A PhD. with extensive experience in content analytics, especially psychological content analysis (i.e. sentiment analysis and emotion in text), as well as predictive analytics using unstructured data, she is fluent in German, Polish and Spanish.]


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