Sample feasibility is what ensures your multi-market research plan is possible – not just in theory, but in practice. It helps you answer key questions before you launch fieldwork, like:

• Can I find the right respondents across all target markets?
• How realistic are my sample size goals?
• Will I need to adjust targeting criteria to reach quotas?
• Is my budget aligned with what’s feasible?

Unlike single-market studies, multi-market research introduces complexity in the form of different languages, cultural norms, online penetration rates, and consumer behaviors. Conducting a feasibility check up front helps identify these challenges early – so you can adjust your plan, not your expectations, later on.

What is sample feasibility in market research?

In simple terms, sample feasibility refers to the ability to successfully recruit a targeted number of qualified respondents to a study. It’s a forecast that assesses whether the sampling goals are realistically achievable based on factors like population size, targeting criteria, and timeframes. In global projects, it often involves working with panel providers like Dynata to model what’s realistic based on their audience reach and targeting filters.

Why multi-market research raises the stakes

Each market is unique. A consumer group that’s easy to reach in the U.S. may be far less accessible in Germany, Brazil, or Indonesia due to differences in online behavior, language, or even legal regulations. Without accounting for this at the feasibility stage, your research could over-index in some markets and underrepresent others – reducing confidence in the findings.

Sample feasibility supports your research goals by:

• Preventing fieldwork delays caused by underestimated incidence rates
• Improving cost accuracy by aligning sample size to panel availability
• Ensuring data quality through balanced respondent targeting
• Reducing effort wasted on unattainable quotas or unrealistic sample targets

While sample modeling tools (like those offered by Dynata) are key to this process, tools alone can’t replace proper planning. That’s where experienced researchers come in. SIVO’s On Demand Talent can bring real-world expertise to help interpret feasibility data, identify creative respondent strategies, and pivot quickly when panel supply shifts – all while making the most of your budget.

In fast-paced projects where timelines are tight and companies are leaning into DIY research tools, feasibility planning – backed by real human insight – ensures your research stays on track, even across regions.

One of the most important concepts to understand when planning sample feasibility is incidence rate. It plays a central role in determining whether your research objectives are realistic – especially when targeting niche consumer groups or spanning multiple countries.

What is an incidence rate?

In market research sampling, incidence rate refers to the percentage of people in a general population who qualify for your study based on your predefined criteria. It's calculated by dividing the number of qualified respondents by the total number of people surveyed (or screened).

For example, if you screen 100 people but only 20 meet the criteria (such as owning an electric vehicle or drinking plant-based milk weekly), your incidence rate is 20%.

Why does incidence rate matter in sample planning?

Incidence rate impacts both cost and timing. Lower incidence means you’ll have to screen many more respondents to hit your sample targets, which adds to both budget and timeline pressures. In multi-country projects, incidence rates often vary by market – making feasibility modeling and audience balancing essential parts of the planning process.

Here’s how incidence rate affects key areas of your study:

• Feasibility: Rare audiences (e.g., new parents in rural regions) may not be reachable within reasonable timelines or budget.
• Respondent targeting: You may need to broaden certain criteria or consider proxy segments to hit adequate sample sizes.
• Sample forecasting: Accurately estimating completion rates and drop-outs helps set realistic quotas.

Using Dynata and other tools to project incidence

Panel providers like Dynata offer feasibility tools that help researchers estimate incidence rates by combining historical data and panel metrics. However, these tools often provide ranges or estimates – not guarantees. Realistic feasibility planning means knowing how to interpret this data and adjust your approach based on local market conditions.

This is where experienced professionals – like SIVO’s On Demand Talent – add immediate value. They can run early incidence checks, validate sample assumptions, and help you fine-tune your targeting parameters across markets. Especially when managing multiple stakeholders or timelines, having flexible research expertise on hand minimizes risk and drives smarter decision-making.

Ultimately, the better you understand incidence rate, the better you can design research that’s both representative and actionable across global audiences. Getting it right upfront ensures that your team doesn’t waste effort chasing unreachable quotas – and that the insights you collect are rooted in reality, not wishful thinking.

When conducting multi-market research, achieving the right balance of respondents across different countries or regions is critical. Audience balancing helps ensure that your sample reflects the populations you're studying, giving you more accurate, comparable insights. But with varying population sizes, internet access levels, and incidence rates, sample balancing can get complex quickly.

Start by Defining Clear Quotas

Before launching your study, determine how many completed surveys you need from each region. These quotas help define your market research sampling framework and ensure each market is appropriately represented in your total sample size. Quotas can be set based on equal sample distribution (e.g., 500 respondents per country) or proportional allocation (e.g., each country represents a share of the total based on population size or market priority).

Consider Incidence Rate Variance

Incidence rate – or the percentage of a population that qualifies for your study – can significantly impact your ability to meet quotas. For example, if you’re targeting parents of toddlers in the U.S. versus Brazil, the incidence rate might vary based on demographic trends and panel coverage. This variance affects sample feasibility and cost, and should be modeled before you begin fieldwork.

Communicate Local Fieldwork Nuances

Some countries may have different restrictions, consumer behaviors, or survey fatigue levels. These factors adjust how quickly – or inexpensively – you can collect respondents. Flexibility in timing or budget allocation by region can help accommodate these differences without compromising your research planning goals overall.

Use Balancing Techniques, Not Just Targets

Balancing is not only about quotas – it’s about good representation. You can stratify respondents by age, gender, language, or behavior to strengthen response quality and reach specific audience segments. This improves your chances of achieving a representative and consistent dataset, especially when comparing markets.

• Equal quotas: Equal number of respondents per country (useful for comparisons)
• Proportional quotas: Adjusting sample sizes based on population size or market relevance
• Stratified sampling: Adding sub-quotas (by gender, age band, etc.) within markets

Ultimately, multi-country sample balancing strategies must be adaptive. Partnering with experts who can re-calculate sample feasibility if field conditions change – for example, lower-than-expected incidence in one market – is essential for success.

Dynata is one of the most widely-used platforms for sample feasibility and respondent targeting in consumer research. It offers real-time access to global panels, making it easier to estimate how many qualified respondents you can reach in each market and how long your project might take. But while robust, tools like Dynata only get you so far – their accuracy depends on how you use them.

Understanding What Dynata Feasibility Tells You

When using Dynata for sample feasibility, you’ll typically input criteria such as demographics, behaviors, or screening questions. The platform then provides an estimate of available sample and feasibility scores per market. For instance, targeting urban millennial pet owners in four countries might yield high feasibility in the U.S., but much lower in others.

This estimate informs your initial research planning, including:

• How to estimate sample size for multi-market research
• Whether your target audience exists at scale in each region
• How long fieldwork may take across countries

Combining Tools for Smarter Forecasting

While tools like Dynata, Lucid, or Toluna help run basic feasibility checks, smart researchers go a step further. By testing screening criteria and recalculating incidence rates during soft launches or pilots, teams can improve accuracy over time. Some researchers also simulate multiple respondent profiles to model feasibility under different targeting strategies.

Limitations and Considerations

No platform is perfect – feasibility tools may overestimate sample availability if targeting is too broad, or underestimate if the platform’s data is outdated. Additionally, unexpected respondent behavior or survey drop-off rates can influence actual field performance.

Practical Tip:

Use Dynata to model multiple versions of your screening criteria before fielding. For example, compare feasibility when using broad versus narrow age ranges, or when including/excluding certain behaviors. This adjustment in early planning often prevents delays later.

Also, consider layering third-party tools or engaging a research partner to triangulate the insights. While Dynata sample planning is efficient, combining expert perspective with feasibility data dramatically improves the reliability of your final sample plan.

Even with access to powerful tools like Dynata and clear insights into incidence rates, navigating sample feasibility in global studies can be overwhelming. That’s where On Demand Talent makes a measurable impact. These insights professionals bring hands-on experience with market research sampling, feasibility modeling, and platform optimization – all without needing long-term staffing commitments.

Expertise That Prevents Costly Missteps

Misjudging feasibility can derail timelines and inflate costs. On Demand Talent can model complex scenarios before fieldwork begins, helping to answer questions like:

• What is the best way to check Dynata sample feasibility?
• How should we estimate sample size for 5 distinctly different markets?
• Which targeting criteria are driving our low feasibility percentages?

These experts help clients avoid common pitfalls by aligning targeting with realistic respondent availability, often before a single survey is fielded.

Flexibility When Conditions Change

Market conditions shift. Incidence rates fluctuate. Sometimes a key audience doesn’t respond as expected. On Demand Talent excels at adapting quickly. Need to re-forecast respondent needs across markets halfway through fieldwork? They can step in and re-balance samples or adjust survey logic, keeping research on track and on budget.

Amplifying DIY and Tech Investments

Many brands are investing in DIY survey tools and research platforms, hoping to speed up cycles and reduce costs. But these systems still require expertise to use correctly. On Demand Talent can help your team maximize these platforms — whether it’s making sense of Dynata sample forecasting or setting up smarter audience balancing rules — transforming tools into tactical advantages.

Filling Skill Gaps Without Long-Term Hiring

Hiring a full-time sampling strategist or global feasibility analyst isn’t always practical – especially for tight-budget projects or transitional periods. SIVO’s On Demand Talent provides flexible access to professionals who’ve already handled complex studies at global scale across industries. They can join for a few weeks or a few months, bring clarity where needed, and seamlessly integrate into your workflow.

Whether you're launching a new market or refining your existing research planning, tapping into On Demand Talent ensures smarter, more agile feasibility modeling — without compromising your insights quality or overstretching your team.