3 Tricks (and 1 Treat) for Choosing Text Analytics Tools

By: Lisa Sigler

October 30, 2015

Customer Feedback
social listening
text analytics

Scared of unread customer feedback? Creeped out by the Tweets that go bump in the night? Lost in the dark forest of customer experience solutions?

Well, you’ve rung the right doorbell. Just like your neighbor who gives out full-sized candy bars, this Halloween we’re giving out the good stuff: three solid tricks for picking out the right text analytics tools (plus an extra treat, because you look so cute in your costume).

Look for the best NLP. Natural language processing (NLP) is the technical witchcraft at the heart of all great text analytics tools. You want technology that processes language the way the human brain does, understanding the impact that grammar, context, and word placement has on the meaning of a sentence. It’s about more than seeing how often a certain keyword shows up in your feedback, or identifying specific combinations of words that appear together—both of these approaches leave too much feedback unaccounted for. Your text analytics tools must combine the best algorithms with machine learning capabilities to conjure up real customer insights.

Seek out omni-source capabilities. Customer insights are lurking everywhere. Your text analytics tools need to be able to handle data from every source, across every channel, at every touchpoint along the customer’s journey. Whether it is solicited data from customer surveys or unsolicited data collected from emails and online reviews, you must account for the specific characteristics of different sources of data in order to see all of your text-based feedback as a unified whole.

Search for flexibility. Every organization and every industry is menaced by a different set of monsters; slaying them is easier when your text analytics tools fit your specific business needs. From industry-specific model templates to customization features, you should insist on being able to adapt your solution to account for the specific vocabulary your customers use, in the global languages they speak. For example, Clarabridge recently added native Romanian support (so if you or your customers need to know the scoop in Transylvania this Halloween, we’ve got you covered).

If you follow these tricks, you will end up with a solution that meets all your text analytics needs. And your sweet treat? Actionable customer insights that will improve the overall customer experience. It sure beats bobbing for apples!

Wait, you wanted actual candy? Sorry—but here’s something that isn’t bad for your teeth: our whitepaper “The Truth about Text Analytics and Sentiment Analysis” contains so much information about text analytics tools, it’s scary.

Lisa Sigler is Sr. Manager of Content Marketing at Clarabridge. For over 16 years, Lisa has used her writing and editorial skills to bring the value and benefits of technology to life. In her current role, she works to demonstrate Clarabridge’s position as thought leader and trailblazer in the Customer Experience Management market. Lisa holds a B.A. of English from Kent State University. Read more from Lisa on Twitter @siglerLis.