From queries to conversations: Unlocking AI’s true potential in Consumer Insight

Move beyond treating AI as advanced search engines and gain fresh perspectives and deeper insights through collaborative exploration.

Nadine Vávra

19 June 2024

6 min read

 

Do you recognize this? You start your day with a cup of coffee, open your laptop and find your inbox overflowing with requests to understand the consumer better. Time and budgets are tight, and the promises of AI seem endless. So, you open ChatGPT and type in the first question of the day: “What are the main pain points for Gen Z when shopping for household appliances?”

I observe many insights professionals, myself included, using generative AI services (like ChatGPT or MS Copilot) as advanced search engines. We query them with prompts to create personas, identify pain points, review ideas, or (most often) simply summarize large amounts of text and video input, for example from insight communities. There is so much insight out there already, so we hit ‘go’ and get an immediate response. But how much do we truly understand? And how do we translate this information into actionable insights?

Those who have delved deeper into AI services have discovered that the key to unlocking its potential lies in our ability to improve and contextualize our questions. Writing better prompts is a step forward, but it’s not the end of the story.

To truly make the most of generative AI, we need a shift in mindset, behaviour, and investment in new approaches. If we keep using as a question-and-answer systems, reducing them to transactional tools, we will miss their true potential to generate new ideas, unfold fresh perspectives, and advance our insights journey.

 

AI as a collaborative partner

I argue that dialogue is needed to maximize AI’s full potential. We have to stop impulsively firing our questions into a ‘search window’. Instead, let’s pause and design real, meaningful conversations that can reveal deeper insights and new perspectives beyond existing knowledge.

But how do you have a meaningful conversation that goes beyond a simple Q&A interrogation? Real conversations with AI try to go beyond extracting specific information quickly and efficiently on a predetermined path with little room for deviation. They involve open-ended questions, contextual understanding, and adaptive responses, creating an engaging and dynamic interaction.

This is where prompt engineering comes in. It is not about engineering the perfect prompt in one go or ticking off a list of questions one after the other. Prompt engineering is an iterative approach. It’s the process of iterating a generative AI prompt to improve its accuracy and effectiveness. Imagine you want to find the perfect gift for your friend. You could get a voucher so she can get what she wants, but this would not lead to the moment of ‘aha’ and surprise that touches her heart. So, you keep thinking, browsing different shops and locations, trying to remember meaningful moments, and asking family and friends. Step by step, you move closer to the puzzle’s solution, finding something new and unexpected that shows you know her even better than she does herself. This is how prompt engineering works. By taking a simple prompt and continuing to adjust it for an AI generator, you’ll receive results that better suit your needs. You’re engineering your request to create a specific output.

But, it’s not a fast and easy process. It takes time and effort.

 

From search to create: transitioning into a new mindset

The initial allure of AI is its efficiency. We fire off questions, expecting instant answers. But, unlike in our ‘finding the perfect gift’ example, many people feel they are done once they have an AI response. They stop there, neglecting to delve deeper and ask critical questions. This is a missed opportunity.  We need to move beyond simply searching for information and shift our focus to prompting AI to generate new content and insights. AI’s true power lies not just in finding existing knowledge, but in helping us create something entirely new.

But transitioning to a ‘create’ mindset isn’t easy. Here’s why:

  • The art of asking: Crafting good questions and embedding them into meaningful conversations with AI is a challenge. How we ask questions determines the quality of the answers. In the future, our ability to ask insightful questions will be a greater differentiator than our knowledge base. We need to embrace continuous questioning and cultivate intellectual diversity within our teams.
  • Questions as instructions: Formulating our questions as actionable instructions for AI can be difficult. Imagine AI less as a magic box holding all existing knowledge and more like a friendly robot who understands human language. This robot has a ‘magic pen’ that can turn your ideas and visions into reality, but it needs clear instructions to work its magic. The challenge lies in  knowing exactly what we want from the outset, even when our vision is still evolving.

Shifting away from the ‘get the answer fast’ mentality is crucial. Unlocking AI’s true potential requires us to invest time and effort. We need to focus on the bigger picture: the specific business problems we’re trying to solve and the decisions that hinge on these insights.  By clearly defining our goals and fostering a culture of critical thinking, we can transform AI from a simple answer machine to a powerful tool for generating fresh perspectives and driving innovation.

 

Deep qual expertise and AI

Deep qual expertise can empower you to better prompt engineering. It’s about designing meaningful conversations between humans and AI services that can lead to deeper and unique insights. Here are my top three ingredients for more effective conversations with AI services:

  1. Be curious and open-minded. Qualitative interviews and AI conversations share a common thread: they’re journeys into the unknown. Approaching this journey with an open mind is crucial. It requires you to be courageous enough to continuously challenge your perspective, assumptions, and (existing) ideas on how to move forward. The best starting point for a qualitative exploration is a place of wonder where you don’t know what will happen. Embrace the discomfort of uncertainty.
  2. Use a sound framework. In-depth interviews thrive on a strong structure rather than a long, detailed, to-do list of predefined questions. A long list only carries the risk of getting lost and missing the essentials. In the end, you’ll have seen and heard a lot but not had any experiences that leave lasting impressions. So, choose carefully where you can delve deeper into particular topics. Know your audience (who is saying what in which context) and be clear on the objectives (what you want to know and why).
  3. Show up as a human. When you want meaningful dialogue with AI, care about being in the moment and lingering around its different responses (no matter how long they are). I like to prompt AI to keep it short in the beginning or output things as a table to make it easier to detect where I want to probe deeper. Before you move on to the next question, wonder (and paraphrase): what is it actually saying? Read between the lines and make connections to earlier threads of the conversation. Explore why instead of asking it. Help it to go places it has never been before. Invite AI to define terms and illuminate them from different perspectives. Get involved and refine the context gradually. This will bring you closer to what you want to do together.

Approaching AI in a conversation like this will make you realize: “The more I learn, the less I realize I know.” (Socrates). This can feel like a blessing or a gift. You are never really done, but continuous learning enables you to write better and more focused research briefs that let you stay ahead of the insights game and discover how to conquer your business challenges best.

 

While generative AI offers a powerful search tool, its true potential lies in collaborative exploration. We can unlock deeper insights and spark groundbreaking ideas by embracing curiosity, crafting thoughtful prompts, and fostering open-ended dialogue. This shift requires a mindset change – from simply seeking answers to actively co-creating knowledge with AI as a partner. Ultimately, qualitative expertise combined with generative AI empowers us to move beyond understanding our audience to shape a better future for them and our brands.

 

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