Guide to using Explori’s verbatim coding AI

Explori’s AI powered open-end verbatim coding is a new tool, which automatically classifies with the responses to the following open questions. 

The tool automates the process of analysing responses to open ended questions, saving time and effort. By using this AI, you can efficiently analyse your survey data and gain a deeper understanding of your visitor or exhibitors’ thoughts and opinions, and allow actionable insight to be taken as a result. 

How it works? 

The tool can be used in both visitor and exhibitor surveys across trade and consumer events. It automates the classification of responses to key open-ended questions found in the Explori question library, as detailed below: 

Improvements – How would you improve [eventname]? 

Net promoter verbatim - Please tell us why you gave that score? i.e. recommending the event to a friend or colleague 

Detractors verbatim - rated NPS 0-6 - What are the reasons for your rating? 

Passives verbatim - rated NPS 7 or 8 - What would it take for you to give a 9 or 10 rating? 

Promoters verbatim - rated NPS 9 or 10 - What specifically would you tell a business colleague or friend when recommending [eventname]? 

These questions can be found in the Explori question library: 

One or more of these questions should be included in the survey 

These open-ended questions, known as the “parent questions” must be included in your survey. The next step is to add in the AI questions. These are closed questions, named: 

Improvements (coded) – Beta 

NPS Verbatim (coded) - Beta 

These questions are also found in the questions library and should be added after the open-ended verbatim questions detailed above. 

The next step is to hide the Beta question so that it is not visible to respondents. This is done by clicking on the Disable Question button, highlighted below:

Once completed, the process will run automatically and any open responses will be automatically categorised in near real-time. 

Learn more with the AI Verbatim Analysis Tool

Note:

There is a limit on the size of each comment. This limit is 1024 tokens (which is approximately 4000 characters). If a comment exceeds this threshold, only the first 1024 tokens of data (approximately 4000 characters) would be included in the classification.