At its core, message architecture testing is about making sure your brand is saying the right things, in the right way, to the right people. It goes beyond testing individual phrases or taglines – instead, it looks at sets of messaging organized by theme, logic, or strategic importance, helping brands understand how messages work collectively rather than in isolation.

Why clarity and hierarchy matter in message testing

Consumers are exposed to dozens of messages each day, and often make decisions based on which messages they remember, trust, or connect with emotionally. Without a strong message hierarchy – the order in which messages are introduced and prioritized – it’s easy for important claims to get lost. Message architecture testing helps brands:

• Identify which messages are most compelling or believable
• Refine unclear or confusing claims
• Understand which themes (e.g., sustainability, affordability, performance) resonate most
• Build a logical flow of communication, from top-line messages to deeper proof points

How message architecture supports brand storytelling

When messages are tested in a multi-stage format, insights teams gain a clearer picture of what works and where gaps exist. Brands can then construct messaging that consistently reinforces core truths across marketing channels – whether it’s a homepage, a social campaign, or packaging copy.

For example, a fictional beauty brand might start with 25 potential claims around ingredients, results, sustainability, and pricing. Through message testing, they might discover that while sustainability claims are liked, results-driven claims ("see clearer skin in 3 days") are what truly drive consumer action. That insight allows the brand to prioritize performance messaging while using sustainability to reinforce credibility.

Why DIY tools need human skill

Tools like Toluna make building and launching surveys easy – but knowing the right way to group, phrase, and sequence messages takes professional expertise. Research judgment is essential in this process, especially when it comes to analyzing open-ended feedback, interpreting trade-offs, and spotting subtle insights that algorithms may miss.

This is where SIVO’s On Demand Talent becomes a valuable addition. These are experienced consumer insights experts who partner with your team to plan and execute research that stays on objective, leads to better decisions, and helps make the most of your DIY tools. No wasted surveys. No misread data. Just smarter message validation at every stage.

Getting started with multi-stage message testing in Toluna begins by setting clear goals and understanding how to structure the survey phases to efficiently narrow down your message set. Here’s a practical breakdown of how to move from a long list of ideas to a focused, insights-backed message architecture – all within a user-friendly DIY platform.

Step 1: Define your messaging pool and themes

Start by collecting all potential claims or messages you want to test. These might include product benefits, value propositions, taglines, proof points, or emotional hooks. Group them by theme – for example:

• Product performance
• Brand values or tone
• Social impact or sustainability
• Customer testimonials

This initial step helps you think about how consumers might mentally organize your messages, setting you up for smarter segmentation later on.

Step 2: Build your first-stage screening in Toluna

Next, launch an initial quantitative survey with a broader list of 20–40 claims. In this stage, the goal is to answer: Which messages rise to the top?

Best practice: Ask respondents to rate messages on clarity, believability, and appeal. Use max-diff or forced-ranking designs to surface relative preference and avoid rating fatigue. Remember, the goal is not just to look at individual message performance, but to see how claims perform within their categories.

Tip: This stage is often where DIY research can go off-track without the right framing. SIVO’s On Demand Talent can help clarify which metrics matter most and avoid misinterpreting early results.

Step 3: Refine and re-test top-tier messages

In the second stage, take your top-performing messages – let’s say the top 10–15 – and sequence them differently, test alternative wording, or place them in combinations. This helps you evaluate message hierarchy: which claims lead best, support others, or work best when paired.

In Toluna, this might involve creating multiple message paths to test with distinct consumer groups. For example, one group might see benefit-led messaging first, while another sees emotional benefit claims first. Results will show which structure leads to higher clarity, agreement, or brand impression.

Step 4: Analyze and finalize your messaging structure

Once both stages are complete, analyze how consumers are reacting not only to individual claims, but the sequence and framing. This is where expert research judgment becomes critical. It's not just about scores – it’s about interpretation.

For instance, if one claim consistently tests well across groups but loses impact when preceded by other messages, it may indicate messaging clash. Or, if emotional language outperforms technical copy, your brand voice might need realignment.

If your in-house team lacks capacity or confidence in evaluating these patterns, On Demand Talent offers flexible support to guide final decisions. These skilled professionals help you go beyond surface metrics to uncover the story behind the survey – ensuring your message architecture is both evidence-based and emotionally resonant.

Message testing is a powerful tool – but only when used with intention. With the right strategy and expert support, Toluna becomes much more than a survey tool. It becomes a launchpad for brand clarity that lasts.

Group similar ideas to reduce noise and uncover insights

When you're testing large sets of marketing claims in Toluna, clarity starts with organization. Grouping related claims into themes allows you to discover not only which individual messages resonate, but also what message categories carry the most weight with your target audience.

Why grouping matters in claim testing

Running unstructured message testing – where dozens of disjointed claims are tested in a single survey – often leads to cognitive overload and unclear results. Respondents lose focus, and your insights become muddled. By organizing messages into thoughtfully grouped themes, you create a cleaner, more intuitive experience that uncovers more meaningful preferences.

This technique is especially helpful in early rounds of multi-stage message architecture research, where the goal is to evaluate a broad universe of claims before refining the top-performing ones.

Effective ways to group message claims

Start by reviewing all the claims your team has brainstormed. Look for:

• Shared functional benefits (e.g., “longer battery life” vs. “charges faster”)
• Emotional positioning (e.g., “feel confident all day” vs. “embrace your bold side”)
• Category-specific themes such as sustainability, innovation, or value

Once themes are identified, structure your Toluna survey to test each claim within its respective theme. You can also test reactions to grouped sets to evaluate the strength of an overall message territory.

Example (fictional): skincare brand testing

Imagine a skincare brand has 20 potential copy points. Instead of testing all 20 at once, their insights team groups claims into themes like anti-aging, clean ingredients, skin confidence, and dermatology-backed. Each group is tested independently in the first stage to identify which territories generate the strongest response. From there, the top-performing individual claims are advanced to secondary testing.

Balance structure with flexibility

It’s important to remember that while grouping improves signal quality, being too rigid can mask unique claim appeal. Allow room to mix and retest across stages to fine-tune your final message architecture and optimize the clarity of results.

Distilling what matters most to consumers

After organizing your message claims into groups, the next step in multi-stage message architecture testing in Toluna is to evaluate message hierarchy – or, understanding which messages rise to the top in terms of consumer relevance and appeal.

What is message hierarchy testing?

Message hierarchy refers to the relative importance and resonance of each message. In testing, it's about identifying:

• Which messages grab attention first (primary messaging)
• Which reinforce the primary idea (support or proof points)
• Which add little or confusing value (noise or distractions)

By establishing this hierarchy early, you prevent misalignment later in the marketing mix. In Toluna surveys, this can be explored using methods like ranking exercises, MaxDiff, or forced-choice screens to assess perceived importance and relevance to consumer needs.

Clarity is just as critical as preference

Even if a claim ranks highly in preference, it must be understood clearly. A message perceived as ‘important’ but confusing won't perform in the real world. That's why message clarity testing should be built into every stage. Ask respondents:

• What does this message mean to you?
• How believable or trustworthy is this message?
• How clear or confusing do you find this statement?

Use open-ended responses and scaled clarity ratings to identify messages that may sound strong in theory but are too vague or misleading in execution.

Refining across multiple stages

Multi-stage message testing allows you to iterate. For example, after stage one surfaces top-performing claims by theme, stage two might focus on refining wording for clarity and stage three may test combinations ordered by perceived importance. This progression builds a clearer message architecture that you can confidently bring to market.

Survey best practices also suggest keeping each testing round focused – don’t overcomplicate. Fewer claims per round allow for deeper feedback and cleaner prioritization.

Test, learn, reframe

Remember: message testing is not about finding a single winner. It’s about testing, learning, and reframing messages that are almost there. Keep clarity and hierarchy front and center, and you’ll finish with marketing messages that not only test well but work hard in-market.

Bridging the gap between DIY tools and expert-level outcomes

Platforms like Toluna have made it easier than ever to conduct quantitative message testing fast and affordably. But while DIY research tools streamline execution, they don’t replace the judgment, experience, and problem-solving required to turn results into strategy. That’s where SIVO’s On Demand Talent comes in.

Why research expertise still matters

Even the best tools need the right hands at the controls. Without a skilled insights professional guiding the setup and interpretation of message architecture testing, teams risk:

• Collecting data that doesn’t answer the business question
• Using poor survey design that leads to misleading results
• Missing subtle cues in open-ends or diagnostics

In message testing, research judgment is critical – from how to group message themes to when to pivot claims based on feedback. DIY doesn’t mean “do it alone.”

The advantage of On Demand Talent

SIVO’s On Demand Talent gives teams immediate access to insights professionals who’ve run hundreds of studies – across industries, tools, and research scopes. Whether you need help fine-tuning a single Toluna survey or designing a full multi-stage research strategy, these experts bring:

• Deep knowledge of survey best practices
• Experience in interpreting consumer response across qualitative and quantitative methodologies
• Strategic thinking to connect findings to larger brand goals

Unlike hiring freelancers or short-term contractors, On Demand Talent is a flexible, high-caliber extension of your team. Our insights professionals are vetted, experienced, and ready to contribute right away – no upskilling or onboarding delay required.

Helping your team grow, too

Beyond filling temporary gaps, On Demand Talent helps upskill your internal team. When paired with your researchers, they provide coaching and guidance on how to get the most out of your investment in research tools like Toluna. This builds long-term capability, so your team becomes more confident and efficient in running future tests.

More agility, less compromise

As DIY tools and AI-enabled platforms continue to evolve, blending technology with strategic expertise ensures you get the best of both worlds – speed and quality, autonomy and support. On Demand Talent makes that possible without committing to a full-time hire or hefty agency retainer.

If reaching the right message faster matters to your business, partnering with the right talent can make all the difference.