Dynata is one of the largest providers of first-party data, offering access to millions of survey respondents around the world. For businesses looking to segment their consumers, this means gaining quick, broad, and customizable reach across multiple audience types – often in days, not weeks.

But the value of Dynata goes well beyond sheer panel size. It offers a suite of tools designed for DIY segmentation research, giving brands the ability to launch surveys and gather insights without running an entire study through an outside agency. For teams with internal research capacity – or those supported by expert On Demand Talent – Dynata can be a powerful solution to scale segmentation efforts cost-effectively.

Key advantages of using Dynata for segmentation:

• Fast access to respondents: Reach your ideal consumer segments quickly, whether they’re based on demographics, behaviors, or attitudes.
• DIY-friendly tools: Dynata’s platform supports independent survey programming, fielding, and sampling – a great option for agile teams.
• Global coverage: Need to understand how different regions view your category? Dynata supports global research in dozens of markets.
• Integrated support options: For more complex research, teams can work with expert resources – like SIVO’s On Demand Talent – to enhance quality and execution.

Importantly, Dynata makes segmentation easier to execute, but not necessarily easier to get right. That’s where many teams need additional support. Even the best tools can’t make decisions around sampling design, screener creation, or variable definition for you – and missteps in any of those areas can lead to flawed or unusable data.

If your team has limited segmentation experience, supplementing Dynata’s capabilities with an experienced research expert can make all the difference. On Demand Talent professionals from SIVO step into these exact kinds of roles – guiding teams through the process so that the segmentation work is not only on time and on budget, but also aligned with the business goals behind the research.

With this combination of DIY tools and experienced oversight, many brands are boosting the speed and quality of their segmentation insights – without needing to expand full-time teams or outsource full studies to an agency. It’s about using the right tools, at the right time, with the right expertise in the room.

One of the earliest – and most critical – steps in conducting consumer segmentation is deciding which variables you’ll use to group your consumers. These research variables form the core of how you’ll identify different audience segments, so they need to be thoughtfully selected and aligned with your business goals.

In segmentation research, variables commonly fall into one of the following categories:

• Demographics: Age, income, gender, location
• Behaviors: Purchase frequency, brand usage, online habits
• Attitudes and motivations: Values, needs, product preferences

While demographics can be useful, many experts recommend focusing on behavioral and attitudinal variables for segmentation research. These uncover the 'why' behind consumer decisions – not just the 'who.' For example, two buyers in the same age range may purchase a product for entirely different reasons. A segmentation based only on age may overlook those important differences.

How to choose segmentation variables:

There is no one-size-fits-all approach, but here are a few tips to guide beginners when determining what to include:

1. Align with business decisions: Start by asking, “What do we need this segmentation to tell us?” The answer might relate to identifying high-value customer profiles, pinpointing growth areas, or guiding product innovation. Your variables should be able to answer the specific business question at hand.

2. Avoid redundancy: Including too many overlapping variables (like similar attitudinal statements) can muddy your analysis. Focus on variables that are distinct and measurable.

3. Think about actionability: A segmentation is only useful if you can act on it. Variables should lead to behaviors or mindsets that your team can target through communications, product offerings, or services.

4. Simplify when possible: Beginners often over-complicate segmentation by including dozens of variables. Start small, and rely on expert guidance if needed to validate your selections.

A common issue for research beginners is trying to mimic past templates or overstuff surveys with too many questions. In reality, the goal is clarity – not complexity. Partnering with a professional (like SIVO’s On Demand Talent experts) during this phase can help ensure your study is driven by insight-worthy questions, rather than data overload.

In DIY research platforms like Dynata, you have control over the variables you include. But with that control comes responsibility: if those variables are poorly chosen or improperly designed, the resulting segments may offer little business value. On Demand Talent can join your team flexibly during planning stages to help identify the variables that truly matter – making sure your segmentation starts on solid ground.

In the next section of this guide, we’ll explore how to align your screener questions with your segmentation goals – and why a mismatched screener can derail your study before it even begins.

A solid consumer segmentation study begins with defining the right audience – and this is where your screener plays a critical role. In market research, a screener is the set of initial questions used to qualify respondents before they enter your main survey. Aligning your screener correctly ensures that only the most relevant participants – those who truly represent your target segments – make it through to the core of your segmentation research.

What Makes a Good Screener?

An effective research screener filters participants based on behaviors, demographics, attitudes, or product usage relevant to your segmentation goals. With DIY research tools like Dynata, it's easy to launch quickly – but without proper screener design, you risk collecting data from the wrong audience, which can skew your results or invalidate your segments entirely.

Here are a few best practices for crafting Dynata screeners that perform well:

• Be clear and specific: Broad or vague questions can lead to unclear responses. Prioritize precision.
• Cut unnecessary qualifiers: Avoid overly restrictive filters that dramatically limit your potential sample size.
• Differentiate screener vs. survey: Your screener should focus solely on qualification – save attitudinal, behavioral, or rating-based questions for the survey itself.
• Test your logic: Use skip logic and screening conditions to avoid overlap or missed respondents.

Example: Screener Alignment in Action

Let’s say a fictional personal care brand wants to segment skincare users based on their approach to product selection: ingredient-conscious, trend-driven, or value-seeking. A vague screener question like “Do you buy skincare products?” wouldn’t be enough. Instead, you would screen for frequency of purchase, decision-making factors (e.g., ingredient transparency), and even brand awareness – refining the frame of who enters the segmentation survey.

Dynata’s platform allows you to set up these kinds of screeners easily, but expertise is still key. Even small misalignments – like including those who only buy skincare for others – can distort your segmentation validation later.

When paired with professional input from insight experts, your screener can be optimized to pull in high-quality, actionable data. That’s essential whether you’re targeting niche personas or building broader consumer clusters.

Even the most well-segmented research can fall short without a carefully considered sample structure. Your sample – the actual group of respondents who complete your survey – is the foundation upon which your consumer segmentation results are built. With tools like Dynata, managing sample design is accessible, but the challenge lies in doing it right.

Why Sample Structure Matters

Sample structure refers to how you organize your respondent pool across various key criteria: age, gender, income, region, product usage, and more. The structure needs to reflect the total population you're studying, while also allowing you to compare groups meaningfully and generate statistically valid insights.

When thinking through market research sample structuring, consider questions like:

• Am I representing the full target population, or just a slice of it?
• What's my minimum base size per segment to ensure I can identify differences?
• Do I need quotas to balance demographics or behaviors within the sample?

Sample Design with Dynata

Dynata offers vast access to consumer panels, making it possible to target specific profiles quickly. However, knowing who to target – and how many of each group to include – is critical. For segmentation research, a balanced and sufficiently large sample allows for cluster differences to emerge naturally, rather than being skewed by overrepresentation or gaps.

For example, if you're conducting segmentation for a fictional snack brand focused on millennial and Gen Z consumers, and 80% of your sample turns out to be over age 40, your clusters won’t reflect your strategic priorities. This is where careful quota implementation and sampling frameworks come in – both made significantly easier with expertise guiding the setup.

Avoiding Common Pitfalls

Many DIY consumer segmentation tools make it tempting to default to “general population,” but tailoring based on your business needs is key. Make sure your sampling design considers:

• Primary usage or buying behaviors
• Demographic and attitudinal balance
• Enough scale per target subgroup to allow for cluster differentiation

Smart sample planning upfront – supported by professionals – helps ensure your segments are meaningful, actionable, and trustworthy.

As DIY research tools like Dynata become increasingly popular, many insights teams are looking to boost efficiency and reduce costs. But DIY doesn’t have to mean “do it alone.” In fact, pairing self-serve tools with expert input can be the difference between a good segmentation study and a business-changing one.

Why Expertise Still Matters

DIY platforms empower teams to launch faster – but only if the foundational research elements are solid. That’s where SIVO’s On Demand Talent comes in. Our experienced professionals help design, align, and execute consumer segmentation with precision, using tools like Dynata to their full potential.

From variable selection to screener alignment and sample development, these experts bring direct, hands-on knowledge to strengthen your research without overextending your internal team.

Flexible Help, Exactly When You Need It

Need to get a segmentation launched but lack the bandwidth or specific skillset on your team? On Demand Talent fills those gaps. Whether you're a Fortune 500 company testing a new product line or a startup exploring initial consumer personas, our professionals can step in for:

• Survey design and optimization within Dynata
• Correct screener-question alignment to business goals
• Defensible sampling structures that balance speed with representativeness
• Data analysis, cluster modeling, and storytelling upon completion

Better Than Freelancers or Consultants

Unlike hiring freelancers or navigating slow consultant engagements, On Demand Talent brings you vetted insights professionals who are ready to plug into your team’s workflow within days – not months. These aren’t junior hires; they’re seasoned researchers who offer guidance while also building long-term capabilities on your team.

If your business is already investing in DIY consumer segmentation tools, getting expert guidance on how to use them effectively is one of the smartest steps you can take. With On Demand Talent by your side, you get flexibility without sacrificing quality – ensuring you get more from every research dollar.