From The Leaders in Applied Text Analytics
for Researchers by Researchers
Founder Tom H. C. Anderson discovered natural language processing in graduate school in 2004. Subsequently as a consultant managing Starwood Hotels guest satisfaction program (comprising of over 1.2 million guest feedback records per year) Tom founded Anderson Analytics, the first marketing research firm to leverage natural language processing in applied consumer insights research. The firm informally partnered with and used early text analytics software from various analytics software firms.
The focus was very much on answering the “So What” question Fortune 500 clients were asking. During these early years the firm received several industry awards for their best practices and innovative methodology. As a result, their work
has been published in several decision Science text books, and presented at over a hundred of industry events.
In 2011 seeing the gap between what business intelligence software firms were providing, and what businesses actually needed, Anderson began development on a new unique approach to text analytics (OdinText) that is superior to the three
traditional approaches that focus on sentence level understanding.
Until now, the three approaches to text analytics had been some combination of either lingusitcics, Baysian Statistics or Machine learning. All three of these approaches suffer from a combination of constraints including requiring significant training data and customization, as well as the fact that they are completely focused on the individual comment level, excluding critical contextual information.
In 2015 OdinText, Inc. was formed, and the software is now being used across a wide variety of industries, firms and data sets.
While the OdinText team has more experience in applied text analytics than any other software firm, the next chapter in the story will be written by you.
We are looking for curious analysts with interesting data. While OdinText is the
best tool for understanding text and mixed (structured and unstructured data), the next chapter in analytics will be written by analysts who won’t have to worry about complicated to use and expensive software, but instead will be able to focus on what really matters – their data and the insights within it!