What is Qualitative AI?

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The new and emerging field of using artificial intelligence to engage with people at scale using qualitative techniques.

It involves a survey, administered online, that includes one or more qualitative questions asked and probed by AI-powered technology.

It’s not just how we go about getting the data, it’s also the skill behind setting up the AI to resemble a real conversation and probe the right things in the right way.  It’s then about what we do with all that data.

We work with Human Listening using their unique and powerful technology specifically developed for AI and text analytics.

When applied correctly, you will be surprised at how much people are willing to share, even on confronting topics.

How does it work?

The AI is designed in the same way that we would create a qualitative discussion.  Think of it like briefing a moderator on what to talk about and probe in an interview.  The difference is, instead of talking to 6 people in a focus group, we’re talking to hundreds. 

When in field, the AI agent, which we call EVE (Evolved Verbatim Engine), will autonomously engage with respondents in a real and meaningful conversation about the topic of interest.  We train the AI how to probe like a pro and keep the conversation going.  This allows the AI to elicit deeper insight that goes way beyond the short and rational statements that open-ended questions usually achieve. 

It also means we end up with a huge body of richly detailed text, similar to a group transcript only there’s hundreds or thousands of them.  We then apply speech text analytics powered by AI to explore this body of insight and distil it into relevant and useful learnings about your category, brand and target audience.  New and unexpected insights usually also emerge.

The end-result is a combination of qualitative insight and quantitative measurement – it really is qual-at-scale.

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Why Qualitative AI

  • Large samples
  • Qualified quantitative insights
  • Faster turnaround
  • Cost effective
  • Explore responses by different cohorts and customer segments
  • Include other important survey measures such as brand awareness, usage and attitudes

A few examples of applications:

  • Brand exploration – brand image, consumer experiences and attitudes
  • Consumer needs, motivations and feelings
  • Problem-solving
  • Concept development and screening
  • Ad and copy testing
  • Pack testing
  • Understand consumer choice
  • Find new space in the market, e.g. unmet needs
  • Explore retail and service experiences
  • Customer journey mapping

Any question you have, or topic to explore, Eve can handle it!

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