Have you ever had one of those ‘why’ conversations with children that usually goes something like this?
Child: Why do we have to go to bed?
Adult: So, we can get enough sleep.
Child: Why do we need sleep?
Adult: Sleep helps our bodies and minds rest and recover.
Child: Why do we need to rest and recover?
Adult: So, we can have energy for the next day.
Some might find these conversations annoying, but we researchers admire children’s relentless pursuit for details! And it is exactly this sort of probing that is used in in-depth interviews to dig down beneath surface-level responses to unearth hidden, nuanced insights.
However, not all projects allow for such in-depth qualitative analysis, and often an online survey is more suitable to achieve the research aims. Qualitative data can be collected in online surveys, but unlike in-depth interviews, further details and clarification cannot be sought; the respondent simply gives their answer and moves on to the next question.
However, thanks to AI, we are now able to delve deeper during online surveys. The way this works is that an AI model analyses open text box responses and then develops a suitable follow-up question that seeks further clarification or details.
Question 1: What could we do to improve your customer experience?
Answer: Increase the product range.
AI: Thank you for your suggestion! Could you please specify which types of products or categories you feel are missing from the current range?
Answer: I would like to see more high-performance models available.
Another benefit of using AI in surveys is its reactivity. When designing an online survey, researchers must, to some degree, anticipate what sort of things are important to interviewees. However, it can be difficult to anticipate exactly what is important to the respondent and, as a result, the right questions to include in the survey.
The advantage of AI here is that it responds directly to what the respondent is speaking about in their answers. In this way, AI molds the survey around what the respondent thinks is important and allows the survey to evolve, exploring new lines of inquiry that may not have been anticipated in the initial survey design.
In the example above, the initial survey might not have contained any questions asking about product range. If many respondents highlight this as a pain point, we’ll gather substantial data on the topic without even having written a specific question about it!
There is nothing worse than finishing a research project and thinking, ‘If only I’d asked that one question’. Utilizing AI allows online surveys to uncover deeper insights by dynamically adapting to respondents’ answers, ensuring no critical question goes unasked.
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