New Feature (AI Probing): Delving Deeper into Respondents' Thoughts

Previously, we introduced AI Coding, a tool that swiftly encodes open-ended responses. However, apart from enhancing analysis efficiency, improving data quality remains a challenge. Due to various factors, respondents' answers often lack depth, and sometimes they may be ambiguous or off-topic, leading to data loss or insufficient insights.

To address this, we have developed the AI Probing feature. It conducts targeted follow-up questions based on respondents' previous open-ended responses, aiming to uncover deeper insights into their thoughts.

When AI Probing is activated, there will be no apparent changes to the respondents' answering interface. There's no need to navigate to another page; instead, a tailored open-ended question will be added within the current survey.


What are the advantages of AI Probing?

Deeper Insights: AI Probing can analyze respondents' open-ended answers and propose more insightful, deeper-level questions. Through this approach, researchers can obtain more valuable information about respondents' viewpoints and opinions, aiding in a more comprehensive understanding of their thoughts and experiences.

Personalized Responses and Care: Through AI Probing, respondents can feel that their thoughts are genuinely being acknowledged and valued. This personalized response can enhance respondents' sense of involvement and willingness to share genuine, in-depth viewpoints, thereby improving the effectiveness and credibility of the survey.

Quality Control: AI Probing not only intelligently comprehends and analyzes answers to open-ended questions but also evaluates their quality. It can flag inadequate answers or respondents, identify potential issues promptly, adjust the direction of questioning, and thereby enhance the quality and accuracy of survey data.


How effective is AI Probing?

To validate the effectiveness of AI Probing, we recruited 300 respondents from our own panel for a product concept test. AI Probing was activated when asking about reasons for liking and disliking the concept.

Research results indicate that when asked about reasons for liking the concept, 69% of respondents provided additional answers after AI Probing, with an average increase of 1.2 answers per respondent. When asked about reasons for disliking the concept, the proportions of respondents providing additional answers after probing and the average increase in answers were 21% and 0.3, respectively.


In the near future, we will also introduce AI Summary, utilizing AI technology to analyze the results of open-ended and closed-ended questions, summarizing the entire research project's findings to enhance report writing efficiency. Stay tuned for updates.

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