Good Question Inputs, Better Outcomes

• Well-targeted to your research goal
• Focused on one clear idea or topic at a time
• Written in simple, neutral language
• Open-ended but not open-ended to the point of being limitless

A Critical Link in the DIY Research Chain

1. Too Broad or Vague

2. Double-Barreled Prompts

3. Leading or Biased Wording

4. Overly Technical Language or Jargon

5. No Context or Direction

Why These Mistakes Matter

When you type an open-ended question into a market research tool like Yabble, the goal is to get a wide range of useful, interpretable feedback. Why? Because the quality of responses directly impacts the accuracy of AI clustering – how the tool groups and analyzes the data. Poorly worded prompts can lead to generic answers, unclear clusters, and confusing results that require extra sorting or even rework.

To get cleaner clustering outcomes in Yabble, your open-ended questions need to be clear, specific, and aligned with what you're truly trying to learn from your audience.

Start with a Clear Objective

Every strong research question begins with a clear goal. Ask yourself: What insight am I hoping to uncover? Are you looking for opinions, behaviors, motivations, or preferences? Defining the end goal helps you frame a question that guides respondents in the right direction – and helps Yabble’s AI organize the responses effectively.

Keep the Wording Simple and Neutral

AI performs best when questions are easy to understand. Avoid jargon, double-barreled questions (asking two things at once), or language that suggests a “correct” answer. For example, instead of asking: “How do you think our new eco-conscious brand position reflects our values and impacts your purchase decisions?” try: “What do you think of our new brand direction?”

Make It Open, but Not Too Broad

Open-ended doesn’t mean vague. A question like “What do you think about our product?” can lead to a scattered set of replies. Be more specific: “What did you like or not like about your experience using our product for the first time?” This kind of prompt still allows range – but within useful boundaries that the AI can follow for clustering.

Example Prompt Rewrites for Better AI Clustering

• Poor: “Tell us your thoughts.”
• Better: “What motivated you to choose this product over others?”
• Poor: “How was your experience?”
• Better: “What worked well and what didn’t during your most recent purchase?”

The more structure you bring to your question, the more structured the response sets will be – which means cleaner, more actionable insight groupings from Yabble’s AI.

Getting good at this takes practice, and even experienced teams can struggle to frame effective open-ended prompts that strike the right balance of open vs. guided. That’s where expert support from flexible professionals can make a major difference – especially while your team is learning new research tools.

DIY research tools like Yabble offer incredible power and speed – but they still rely on human expertise to guide them. A well-intentioned but poorly written question can lead the tool down the wrong path, no matter how advanced the AI may be. That’s where On Demand Talent comes in: giving you access to experienced consumer insights professionals who know how to optimize tools like Yabble for impact, without needing to hire full-time staff.

While many companies turn to freelancers or task-specific agencies for short-term support, SIVO’s On Demand Talent solution gives you a better option – high-ranking professionals with proven track records in market research, ready to jump in, understand your business, and improve your outputs from day one.

What Makes On Demand Talent Effective for DIY Tools?

• Strategic Clarity: These experts help define clear research objectives, so your questions – and the AI’s results – stay aligned to business goals.
• Prompt Precision: They bring tested frameworks and writing techniques to craft open-ended questions the right way, avoiding common mistakes in Yabble.
• AI Fluency: On Demand Talent professionals often have hands-on experience with multiple AI research platforms. They know the quirks and strengths of tools like Yabble and can shape inputs that produce tighter clustering and more relevant insights.
• Fast Results: Because they’re experienced, they hit the ground running. Within days, they can start cleaning up question structures, designing research flows, and training your junior staff to use tools more effectively.

Let’s say your team is using Yabble to analyze customer feedback from a product launch. The raw responses are all over the place – some short, some off-topic, difficult for the AI to categorize. An On Demand Talent professional can reframe the original prompts for better focus, fine-tune the clustering settings in Yabble (if applicable), and even write a short-term playbook to help your team use the tool more strategically moving forward.

Rather than patching together inconsistent help from gig platforms, you can bring in someone who builds capability – not just deliverables.

Whether you’re just starting with DIY tools or are several projects in and seeing messy outputs, On Demand Talent can help clean up your process, teach better question writing, and ensure your team gets smarter with every project.

There’s no doubt AI is transforming the way market researchers work. Tools like Yabble streamline processes, speed up analysis, and create space for more experimentation – all essential in today’s budget-conscious and time-sensitive environment. Yet amid the push for automation, there’s a growing concern: Are we risking the human element that gives research its power?

It’s a valid question. AI clustering can organize thousands of open-ended responses in seconds, but it can’t always understand nuance, emotion, or cultural context. And those subtleties often hold the key to powerful consumer insights.

The Role of the Researcher Is Changing – Not Disappearing

Rather than replacing human roles, AI enhances them. Consider AI a co-pilot – it's there to process volume, flag patterns, and suggest themes. But you still need humans to interpret what matters, connect findings to business decisions, and add empathy to the process.

Here’s how market research teams can use AI like Yabble without losing their human edge:

1. Use AI for Speed, Keep Humans for Strategy

Let the AI do the initial lift – like clustering raw feedback or summarizing sentiment. Then have your team (or flexible experts) review results through the lens of your brand, your audience, and your objectives. This ensures the output stays relevant and actionable.

2. Combine Data with Empathy

Open-ended responses can carry emotional weight. An AI might label a comment as negative, but a researcher can recognize that it reflects deeper loyalty or concern. Human interpretation ensures insights go beyond the surface level.

3. Invest in Capability Building

As AI tools become a staple in consumer insight teams, don’t just adopt the tech – build the team’s ability to use it well. That’s where resources like On Demand Talent play a crucial role: transferring knowledge, modeling best practices, and helping teams adapt quickly without losing quality.

4. Focus on Hybrid Approaches

Instead of a purely AI-driven or purely manual workflow, the future of market research lies in hybrid ecosystems. Use automated tools to process and analyze, but bring in human expertise to shape the research questions, interpret tricky findings, and tell a cohesive story to stakeholders.

By embracing both AI and expert judgment, insight teams can deliver faster, more nuanced results – without sacrificing the depth that makes research valuable in the first place.