Open-ended questions are a staple in brand tracking surveys. They give consumers space to explain how they feel in their own words – a format that can uncover emotions, motivations, and perceptions that closed-ended questions often miss. But while these responses offer valuable qualitative insights, many DIY research teams find them difficult to analyze at scale.

Why open-ended responses are powerful – but tricky

DIY platforms make it easy to include open text boxes in surveys, but much harder to extract consistent meanings from what people write. Comments can be vague, misinterpreted, or vary widely in quality. Some may be one-word answers like “meh”; others could be long, rambling paragraphs. With hundreds or thousands of responses across multiple trackers, this turns into an overwhelming amount of unstructured data.

Common challenges when analyzing open-text in brand health tracking:

• Volume: Manually reviewing and coding thousands of responses is time-consuming and often delayed.
• Lack of consistency: Different analysts may interpret themes differently, leading to bias or confusion.
• Surface-level reporting: To save time, teams may rely on word clouds or basic frequency counts – which lose the nuance and meaning behind the words.
• Missed early signals: Subtle shifts in brand perception can go unnoticed unless someone is digging deep.

Because of these challenges, many DIY platform users end up skipping open-ended analysis altogether or giving it minimal attention in reporting. This creates blind spots in understanding brand health and weakens the overall impact of the brand tracker.

Why AI alone isn’t always the answer

Many DIY tools now offer some form of automated text analysis – such as sentiment scoring or topic extraction. And while that’s a helpful start, automated outputs rarely explain *why* changes are happening. For example, a spike in positive sentiment may show up in the data, but without context, it’s unclear what caused it: Did consumers love a new ad, enjoy better customer service, or respond to a pricing promo?

Without guidance from experienced researchers, teams risk misinterpreting AI outputs or presenting shallow insights. That’s where SIVO’s approach – combining AI tools with flexible support from On Demand Talent – can dramatically enhance how organizations unlock value from unstructured survey data.

Yabble is an AI-driven insights platform specifically designed to tame the chaos of unstructured feedback. Its strength lies in automatically analyzing large volumes of open-ended responses and turning them into structured, digestible insights. For teams managing ongoing brand tracking studies, this opens the door to deeper understanding without the heavy lift of manual coding or interpretation.

What makes Yabble different from basic text analysis tools?

Yabble goes beyond keyword detection. Using generative AI and natural language processing (NLP), it identifies sentiment, emotions, topics, and even underlying motivations within consumer text. It can analyze thousands of comments in minutes, summarizing key themes and highlighting patterns that may otherwise take days or weeks to uncover by hand.

Examples of what Yabble can do:

• Cluster similar responses together to identify trends in how consumers describe your brand
• Distinguish emotional tone – are comments expressing confidence, confusion, frustration?
• Surface emerging themes that may be gaining traction (e.g. increased mentions of sustainability)
• Automatically build reports that link themes to demographic or behavioral segments

This automation doesn’t just save time – it empowers teams to get closer to the "why" behind brand perception shifts and make changes with confidence.

Turning Yabble insights into brand decisions

Despite the power of AI, many teams still struggle with how to act on automated insights. That’s where partnering with experienced researchers through On Demand Talent can elevate your use of tools like Yabble. These professionals know how to spot meaningful trends, refine AI outputs for clarity, and connect themes back to key business questions.

For example, if your latest brand tracker shows an unexpected dip in loyalty, Yabble might surface negative themes around price or product availability. But an insights expert can go deeper – slicing the data by region, identifying change over time, or merging it with quant data to validate assumptions. This kind of layered analysis bridges the gap between automated summaries and strategic storytelling.

The best of both worlds: DIY tools + expert talent

Using Yabble for open-text analysis gives your team speed and scale. Pairing it with SIVO's On Demand Talent ensures quality and insight. When experienced professionals guide the AI and align it to research goals, the result is stronger reporting, more actionable takeaways, and fewer blind spots in your brand health tracking.

In today’s market, where brands need to quickly interpret shifting consumer sentiment, this kind of support isn’t just nice to have – it’s becoming essential for decision-makers who want to lead with confidence.

Open-ended survey responses offer a goldmine of qualitative insights—but only if teams can extract meaningful trends from them. At scale, this becomes overwhelmingly complex. While tools like Yabble empower brands to conduct their own open-text analysis quickly, many still find themselves facing common hurdles when trying to interpret this kind of data for brand tracking purposes.

Volume vs. Depth: A Balancing Act

One of the biggest challenges is managing the sheer volume of responses. AI market research tools like Yabble can process large datasets rapidly, but interpreting the why behind trends often requires human context. Without this balance, data can feel surface-level or even misleading.

The Difficulty of Detecting Subtle Shifts

Another challenge lies in spotting nuanced changes in brand perception. For example, if customers slowly begin associating a brand with “cheap” instead of “affordable,” that slight wording shift carries significant implications—but it may be too subtle for AI alone to catch. Effective brand health tracking depends on identifying these micro-changes early.

Consistency in Interpretation

Open-ended text can be subjective. Without standardized coding or clear themes, different analysts—or even different AI models—might tag responses differently. This inconsistency can affect how brands evaluate shifts in consumer sentiment over time and complicate longitudinal tracking.

When Insights Get Lost in the Noise

Not every mention of the brand is meaningful to brand health. Because open-text analysis captures everything from off-topic comments to sarcasm, separating signal from noise can be time-consuming. It’s not just about analyzing what people say—it’s about identifying what matters most to your brand tracking goals.

Common problems with open-ended survey analysis include:

• Difficulty quantifying qualitative insights at scale
• Overreliance on automation with limited human review
• Lack of actionable next steps from raw data
• Gaps in emotional or contextual interpretation

While AI tools like Yabble help automate much of the labor-intensive work, human insight remains essential. This is especially true when interpreting the tone, sentiment shifts, and cultural nuances that influence brand loyalty and perception. That’s where pairing these tools with expert insights professionals makes a measurable impact.

As DIY research tools like Yabble become more advanced – and more accessible – many brands are embracing self-serve platforms for faster, more cost-effective consumer insights. Yet, while these tools offer impressive AI capabilities, they can’t fully replace what human experts bring to the table. This is especially true when it comes to deep, strategic interpretation in brand tracking research.

The Limits of Automation

AI tools excel at identifying patterns in text and summarizing themes quickly. But machines can’t always interpret subtle shifts in brand perception, cultural context, or emotional tone. For example, understanding why customers are shifting from “trusting” to “skeptical” about a brand may require understanding the broader market environment, competitive actions, or underlying customer emotions – all of which are hard to detect through automation alone.

Staying Objective and On-Strategy

One of the growing concerns with DIY research is the risk of bias or tunnel vision. If internal teams analyze their own data without outside perspective, they may unintentionally misinterpret results or miss emerging insights. On Demand Talent acts as a strategic thought partner, grounding AI-generated data in broader consumer, cultural, or category context – ensuring your research stays focused and aligned to business strategy.

Filling Skill Gaps Without the Hiring Headache

Many insights teams lack the bandwidth or specific expertise needed to get the most out of DIY platforms. Whether it’s structuring questions for better open-text responses or navigating advanced features for automated text analysis, On Demand Talent offers flexible, experienced support without long hiring timelines. They hit the ground running, helping teams bridge the gap between tool capability and user ability.

When to Bring in On Demand Talent

Here are a few moments where adding On Demand Talent can upgrade your DIY brand tracking efforts:

• You’re unsure how to structure open-ended questions for measurable outputs
• You’ve run surveys but insights feel superficial or repetitive
• You need help interpreting sentiment themes or shifts in consumer tone
• You want to train your team to maximize existing tools like Yabble
• You need scalable support without adding permanent headcount

At SIVO, our On Demand Talent are senior-level consumer insights professionals who are familiar with both traditional research methods and modern DIY tools. They offer flexibility, speed, and strategic focus – helping clients unlock the full value of their AI market research investments.

When you combine the speed and automation of Yabble with the strategic mindset of experienced researchers, brand tracking becomes both smarter and more actionable. This hybrid model enables brands to not only identify what consumers are saying in open-text responses, but also understand why it matters and how to respond.

The Best of Both Worlds

Yabble accelerates data processing, extracts themes using natural language processing, and can even generate summaries of sentiment and customer language. But interpretation – especially for high-impact business decisions – still needs a human lens. With On Demand Talent supporting your team, you can:

• Validate AI-generated themes with real-world context
• Go beyond the “what” to uncover the “why” behind brand sentiment
• Connect brand tracking data to broader business strategies
• Develop more nuanced, insight-driven reporting

For example, say Yabble identifies an uptick in terms like “inconsistent” or “unreliable” from a recent quarterly tracker. An On Demand professional could explore whether those mentions are linked to specific regions, product lines, or service touchpoints – turning a vague red flag into clear opportunities for improvement.

Real-Time, Flexible Support

SIVO's On Demand professionals don’t need onboarding or training. They’re experienced in market research tools and methodology, so when your insight team is stretched thin or you need urgent help mid-project, support is available in days or weeks – not months. That’s ideal for short-term analysis sprints, quarterly reports, or rapid response to evolving brand perception.

Building Internal Capability for the Long Term

Beyond delivering immediate impact, On Demand experts can help upskill internal insights or brand teams. They can demonstrate more effective approaches to survey design, open-text setup, or even coach teams on how to enhance brand tracking with Yabble. This capability-building ensures your investment in DIY tools is maximized for long-term growth.

Ultimately, pairing Yabble with On Demand Talent transforms brand health tracking from reactive to proactive. Rather than simply reporting on what consumers said, you gain a strategic partner who can help you decide what to do next. That’s the kind of insight that drives real brand momentum.