Tags can be created/applied by visiting the Feedback page of your campaign, clicking on a piece of feedback, and selecting the 'Add Tag' tab at the bottom.


Tags allow you to categorize individual feedback by specific themes that you define to help give you a clear picture of the hot spots (good and bad) with your customers. You can apply any number of tags to an individual feedback although most customers speak to 1-3 specific issues on average.

A suggestion I have is to only use nouns or subjects as tag name, not adjectives. We recommend using broader terms such as "usability" in contrast to more specific terms like “easy of use” because of the fact that you can have variation of opinions on the topic of “usability”. Let the sentiment on a tag depict the adjective instead of specifying it in the tag itself.

Additionally, you can apply sentiment to the tags based on the nature of the response (positive, neutral or negative). This helps you clearly define what trends are driving the majority of your Promoters, Passives and Detractors and can help you clearly identify what issues to address. When you create/apply a tag, the default sentiment will match the sentiment of the feedback (i.e. If tagging a detractor response, tags by default will be red or negative.)

Once you have added tags to your feedback, trends will be shown on the Trend Analysis view of the campaign.

Tags are not generated automatically. There are two very important reasons why we don't automate this process. We could enable this very easily using a variety of tools, but we have chosen not to because it simply doesn't benefit you as our customer.

  1. Automated text analysis tools have a miss-rate (error rate) of as high as 40% and this doesn't even account for sentiment behind that keyword tagging which is even more difficult. What ends up happening is you get either a lot of missed keywords or incorrect sentiment and this is dangerous when you go to make business critical decisions on that data. This either costs immensely more than the time to accurately tag the feedback the first time around, or you spend the same amount of time correcting these errors.

  2. Almost all the value in the NPS process is from the open-ended feedback we help pull from customers/clients. We want to make sure you are reading this in it's entirety and internalizing that feedback, and not just pre-defining customers. Automating trends makes it easier to brush off the verbatim feedback and not close the loop effectively, meaning you won't get the same value out of this process and therefore less ROI on the time and investment in any tool you're using.

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