Putting together the Text Puzzle

Are you currently monitoring social media conversations for customer feedback about your products or services?  Maybe you want to predict or uncover fraud based on emails, online forums, or chat sessions.  Or, if you’re like many of our customers, you’re inundated with call center notes and surveys, both of which contain valuable information about your customers and the products/services that you provide.

No matter your goal, each customer touch-point enhances your view, providing you with additional puzzle pieces & insights that may help to drive business decisions.

As an example, consider the following customer review:

(Line #1)  "I placed an order on your website 3 weeks ago."
(Line #2)  "The price was cheap and to my surprise it arrived 2 days ahead of schedule."
(Line #3)  "However, the batteries were missing and the headphones didn’t work."
(Line #4)  "When I called, I was placed on hold for 30 minutes.
(Line #5)  "When I finally did get through, the rep was very rude and wasn’t helpful."
(Line #6)  "I am going to return the mp3 player, and will never shop here again."

This is a fairly standard customer review. It contains both positive and negative feedback, describes multiple issues, identifies the product and/or service, and has an outcome.

There are a few key things to point out:

Each line adds intelligence about the customer and their situation. Re-read the review, leaving out line #3. Without this sentence, the customer has no reason to call and complain. Even more important, you have no factual information to make your product or service better. You only have a dissatisfied customer, seemingly because they were put on hold for an excessive time and had an unfavorable conversation with the call center rep.

Line #2 contains positive feedback for the company. However, basic sentiment analysis solutions may look at the word “cheap” and classify it as a negative, as in “cheap quality.” There's also no real positive keyword to let us know that “2 days ahead of schedule” is something positive. Having the ability to analyze words within context reinforces their true meaning and enables your business to get maximum insight from your data.

If you were the company receiving this feedback, you’d also like to know that the review discussed these 5 key areas:

-  Distribution (which was perceived as positive because of the quick shipping of the order)
-  Price (perceived as a positive because it is cheap)
-  Quality (perceived as negative because of the missing batteries and malfunctioning headphones)
-  Customer Service (perceived as negative because of time on hold and the rude and unhelpful customer service rep, even though “customer service” was not explicitly mentioned)
-  Reputation (perceived as negative because they “will never shop here again”)

Why is this important to you? Because your results need to be accurate if you are going to make business decisions! The right software and technology enables intelligent extraction of relevant information. Ultimately, it doesn’t matter how much “big data” you have on your customers. If you cannot extract key information or if it's misclassified, you’re left with misinformed decisions, untapped value, and a puzzle that at best is yet to be finished – and at worst, is giving you the wrong picture. If content is king, then relevance is the kingdom.  Have you uncovered misnomers using Text Analytics on your data? If so, we’d love to hear about your experiences.

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