Introduction
What Is a Feasibility Model in Market Research?
Understanding the Basics of Feasibility Models
A feasibility model in market research is a planning tool used to assess whether a study is possible and practical before it gets off the ground. It helps estimate how many qualified respondents are available, how likely you are to reach them, and what resources you’ll need to complete your research successfully. Feasibility models are about setting realistic expectations upfront. They guide decisions like:- How large your sample can realistically be
- What incidence rate your survey is likely to achieve
- Which markets or demographics are accessible
- How long fieldwork might take based on audience availability
- What it might cost to achieve your research goals
Why Feasibility Models Matter
Failing to plan feasibility correctly is one of the biggest – and costliest – mistakes in survey research. Without accurate forecasts, teams may: - Overestimate audience availability - Misset project timelines - Run out of budget mid-fieldwork - Or worse, gather data that isn’t representative or usable By building a feasibility model early, you avoid these pitfalls and reduce risk – making it easier to deliver actionable insights, faster.Key Components of a Feasibility Model
1. Audience Definition – Who exactly are you trying to reach? Is it general U.S. consumers, Gen Z gamers, oncology nurses, or pet-owning millennial dads? The more specific the audience, the more detailed your feasibility approach needs to be. 2. Incidence Rate – This is the percentage of people in a general sample who qualify for your study. For example, if only 15 out of every 100 random panelists qualify, your incidence rate is 15%. This drives sample cost and timing. 3. Sample Size Targets – How many completes are needed to achieve your analysis goals? This connects directly to feasibility – some targets may not be possible with hard-to-reach groups. 4. Panel Availability and Reach – Feasibility studies often use third-party panel data, like Dynata, to estimate audience reach and fill rates. Having current, reliable data is crucial.How Dynata Data Supports Feasibility Modeling
Dynata is one of the world’s largest first-party data providers, and a go-to source for feasibility forecasts. When used correctly, Dynata data allows researchers to: - Predict survey incidence rates across diverse segments - Estimate how long fielding will take - Determine whether their criteria are too narrow – or actually achievable These insights are especially valuable when planning more difficult or niche market research studies.When to Bring in On Demand Talent
Many research teams have access to market research tools but lack the time or experience to use them effectively. That’s where SIVO’s On Demand Talent comes in. Our experts can step in to assess whether your audience is feasible, help configure Dynata feasibility studies, and ensure your plan is aligned with both your goals and your budget. Think of a feasibility model as your survey’s roadmap – and On Demand Talent as the experienced driver who knows when to reroute and how to keep the trip running smoothly.Why Hard Categories Require Specialized Planning
The Challenge of Researching Hard-to-Reach Audiences
Some survey audiences are straightforward – they have broad appeal, high availability, and reliable data to back them up. Others fall into what researchers call "hard categories," meaning the audience is difficult to identify, reach, or engage. Examples might include:- Enterprise IT decision-makers
- Professionals in niche medical fields
- Consumers with rare buying behaviors
- Individuals with sensitive or stigmatized conditions
Why Hard Categories Pose Unique Risks
Without proper planning, hard categories can derail your project. Here’s why: - Lower Survey Incidence: Qualification rates are often below 10%, meaning more recruitment effort and higher cost. - Limited Panel Reach: Standard panels may not include enough qualified respondents. - More Complex Screeners: You may need longer, more detailed screening criteria to filter the right fit. - Faster Drop-Off: Respondents in niche categories may tire quickly or abandon surveys if they feel too generic. In short, what works in mainstream studies doesn’t always translate. You need a different lens – one grounded in category knowledge and data-driven decision-making.How Dynata Supports Hard Category Feasibility
Dynata is particularly useful in hard categories because it allows researchers to: - Run test counts using detailed incidence filters - Map feasibility across countries, industries, or roles - Compare different profiling variables before finalizing a screener - Review feasibility models with real-time data trends But while Dynata provides robust data, getting maximum value from it requires knowing how to filter, interpret, and act on the insights. That’s where On Demand Talent can step in as a high-impact extension of your team.Adding Value Through Expert Support
SIVO’s On Demand Talent are experienced professionals who specialize in feasibility modeling for hard-to-reach audiences. They bring real-world knowledge to the table, which can help: - Translate business questions into measurable audience profiles - Customize Dynata feasibility studies to capture relevant incidence rates - Adjust predictive models as early insights emerge from pilot testing - Guide decision-making when tradeoffs are needed between timeline, budget, and data quality For example, if you're launching a study of U.S. nutritionists specializing in adolescent health, an On Demand Talent professional can help you: - ID the best Dynata filters - Flag if quota sizes are unrealistic - Create a screener that invites engagement (not abandonment)Why Planning Matters More Than Ever
Amid growing reliance on DIY tools and AI-powered platforms, it’s easy to rush feasibility planning. But hard categories demand focus and flexibility. Investing upfront in accurate feasibility modeling often saves time, budget, and credibility down the line. Whether you’re launching a niche panel, evaluating an unmet need, or planning an international segmentation study, smart feasibility planning can be the difference between insight and oversight. With the help of Dynata and SIVO’s On Demand Talent, navigating hard categories can go from a guessing game to an informed, confident process.How Dynata Helps Predict Incidence and Refine Targeting
One of the most critical components of building feasibility models in market research is accurately predicting survey incidence rates – how many people in a population meet your target criteria. This is particularly important for hard-to-reach audiences, where overestimating feasibility can quickly derail timelines and budgets.
This is where using Dynata data becomes especially valuable. With one of the world’s largest first-party data sets, Dynata offers deep, real-time visibility into consumer attributes, behaviors, and demographics across hundreds of categories.
How Dynata Supports Better Incidence Planning
Dynata can help inform and refine your feasibility model in a few key ways:
- Pre-screening analytics: Dynata can run quick test screens to gauge incidence among your target audience before a full launch.
- Historical benchmark data: Access to similar past studies helps you estimate likely success rates and adjust expectations accordingly.
- Detailed audience profiling: Dynata offers enhanced segmentation tools that go beyond typical demographics, allowing you to pinpoint more nuanced qualifiers like behaviors, shopping habits, or lifestyle preferences.
For instance, let’s say you're targeting environmentally conscious tech buyers for a new product concept test. Rather than estimating sample sizes based on a wide target like “tech users aged 18–35,” Dynata allows you to zero in on respondents who follow sustainability influencers, purchase eco-friendly electronics, and have shown interest in emerging tech trends. This refinement increases precision, raises incidence rates, and optimizes sample size planning.
By leveraging Dynata for survey feasibility modeling, teams reduce guesswork and better understand constraints up front, enabling smarter design and smoother fieldwork. But even with these tools, turning raw data into confident decisions often requires complementary human expertise – which brings us to the next piece of the puzzle.
The Role of On Demand Talent in Feasibility Modeling
While tools like Dynata provide the foundation for strong feasibility models, their value grows exponentially when paired with experienced human insight. That’s where On Demand Talent from SIVO comes in.
Our network of seasoned consumer insights experts helps bridge the gap between raw data and strategic action – bringing deep category knowledge, research expertise, and fluency with leading market research tools.
Why Experts Matter in Hard-to-Reach Categories
Feasibility modeling in complex categories – like B2B segments, emerging tech buyers, or niche healthcare groups – demands an advanced grasp of not just the data, but also the audience dynamics, feasibility levers, and field realities. A skilled On Demand professional can:
- Assess real-world feasibility: Use a combination of platform data, past research experience, and broader market signals to create a realistic projection.
- Optimize screening and quotas: Prevent overly narrow qualifiers from sinking response rates, while still ensuring relevant respondent quality.
- Spot red flags early: Identify PII, routing, or survey design issues that could lead to poor recruitment or respondent drop-off.
- Coach internal teams: Teach your team how to make the most of your investments in Dynata and other platforms, building internal capability while solving immediate needs.
Unlike hiring a consultant or freelancer who might need ramp-up time or support, SIVO’s On Demand Talent plug into your workflow and get started quickly – often within days. Whether you need a quant lead to build your feasibility study or a seasoned field manager to streamline screeners, we match you with the right expertise at the right time.
This model gives your organization scalable, expert-led support without the overhead of permanent hiring or the uncertainty of solo freelancers. It’s flexible research staffing for today’s fast-moving insights environment.
Tips to Improve Survey Success in Complex Categories
Even the best feasibility models can't guarantee flawless execution – especially in hard categories. But by applying a few smart research strategies early on, you can tip the odds in your favor and ensure surveys meet both quality and timeline goals.
Start with focused, flexible targeting
Resist overly tight screeners – if your initial criteria are too specific, you’ll burn through panelists quickly or fail to meet quotas. Use data from Dynata feasibility studies to identify realistic trade-offs before finalizing qualifications. Prioritize must-have traits and tag nice-to-haves that can be deprioritized if incidence is lower than expected.
Test assumptions with a pilot
Before full launch, run a small soft launch or test phase. This helps verify your survey incidence rate assumptions, identify dropout patterns, and fix technical or design issues. It’s a research insurance policy – especially important when working with hard-to-reach audiences.
Partner with the right experts
In tricky categories, experience matters. A seasoned insights partner, like SIVO’s On Demand Talent, can guide your team on best practices, refine your outreach plan, and rapidly identify friction points. They also ensure alignment with business strategy while keeping respondent experience high.
Keep the survey experience respondent-friendly
Many feasibility issues stem not from targeting, but from poor survey design. Long, repetitive, or overly technical surveys can lead to abandonments even among well-qualified panelists. Use clear language, logical flow, and mobile-friendly formatting to reduce friction and improve completion rates.
Stay flexible during fieldwork
Despite the best planning, field conditions can shift. Whether it’s lower-than-expected incidence or changing team priorities, you’ll often need to adjust in real time. Build in checkpoints to monitor progress and consider fallback options like quota adjustments or phase extensions.
With the right mix of foresight, agility, and expert support, even complex audiences become accessible. Survey success in hard categories is possible – but it’s rarely accidental.
Summary
Building effective feasibility models in market research starts with understanding your audience and choosing the right tools. In this post, we covered what a feasibility model is, why hard categories need more specialized planning, and how Dynata data can help predict audience fit and increase sampling accuracy. We also explored the critical role On Demand Talent plays in refining and executing these strategies – offering expert guidance, flexible support, and stronger outcomes. Finally, we offered practical tips for managing feasibility studies and driving survey success, even in complex or niche research categories. Together, these steps form a roadmap to informed, optimized research planning that drives true business value.
Summary
Building effective feasibility models in market research starts with understanding your audience and choosing the right tools. In this post, we covered what a feasibility model is, why hard categories need more specialized planning, and how Dynata data can help predict audience fit and increase sampling accuracy. We also explored the critical role On Demand Talent plays in refining and executing these strategies – offering expert guidance, flexible support, and stronger outcomes. Finally, we offered practical tips for managing feasibility studies and driving survey success, even in complex or niche research categories. Together, these steps form a roadmap to informed, optimized research planning that drives true business value.
