Toluna's platform is widely recognized for democratizing access to survey research, offering companies a versatile way to collect consumer data insights quickly. But one of its most valuable features often goes underutilized: profile-based targeting.

Toluna profiling data refers to a wide set of pre-collected characteristics about its panel respondents. This includes demographic details (such as age, gender, income) and behavioral or attitudinal data, like shopping habits, healthcare usage, parenting status, technology use, and much more. Panelists opt in to share this information, which allows survey creators to filter and target respondents based on highly specific criteria – all before the survey even begins.

Why profiling data matters in market research sampling

Survey success depends on reaching the right people. Too often, companies rely on lengthy screeners to weed out unqualified respondents, wasting time and budget in the process. Using profiling data removes guesswork and streamlines your sample-building process by narrowing in on people who are already known to meet your criteria.

Here’s why that matters:

• Reduces over-screening: Saves time and fielding costs by lowering the number of disqualified completes.
• Boosts feasibility: Better targeting means better incidence rates, making your study more realistic to complete within scope.
• Speeds up launch: With a more accurate starting pool, surveys get into the field faster with fewer revisions.
• Improves precision: You’re getting input from the right audience – reducing noise in your findings.

For those looking to scale their research or build frequent studies, using profiling data is an essential step toward sampling efficiency and decision-making confidence. Rather than treating every project from scratch, it builds on known, structured information that helps refine every campaign moving forward.

Who benefits from this approach?

From startups exploring market fit to enterprise brands launching in new categories, profiling data supports a range of survey needs. But while it’s available to everyone using Toluna, not everyone uses it effectively. That’s where the support of insights professionals – like SIVO’s On Demand Talent – can be a game changer. These experts know how to filter profile databases thoughtfully, avoid false assumptions, and align audiences to business objectives.

In an era of increased dependence on DIY research tools, having someone who can navigate these platforms strategically is key. Whether you work on a lean team or simply need to scale high-impact surveys, tapping into profiling insights is a smart, cost-efficient foundation for data success.

Building a quality sample is one of the most critical – and time-consuming – parts of marketing research. Often, insights teams spend too much time screening for basic traits like age or product usage, only to find low incidence rates and slow sample delivery. Pre-profiled audience data solves this problem by starting with known traits upfront, supercharging both targeting and feasibility.

What are pre-profiled traits?

Pre-profiled traits are participant characteristics already documented by the platform (like Toluna) before any new study is run. Instead of collecting this information via survey screening questions, the data is sitting in the panelist profile. These profiles may include:

• Demographics like age, gender, marital status
• Lifestyle traits such as pet ownership, dietary choices, or hobbies
• Purchase behavior or brand preferences
• Media usage, device ownership, or travel habits

Instead of casting a wide net and hoping to qualify respondents along the way, researchers can use these traits to create higher-precision samples from the beginning. For example, if you're targeting frequent coffee drinkers who shop at premium grocery stores, Toluna's profiling lets you identify those segments instantly – avoiding wasted time and screenouts.

How this improves incidence rates and feasibility

One of the major challenges in market research sampling is incidence – the rate at which qualified participants appear in the general population. Studies with narrow criteria (e.g., parents of toddlers with brand loyalty to a specific toothpaste) can quickly run into feasibility issues if screening begins from a general audience. By using profiled data, you're no longer starting from zero.

This reduces the number of screened-out respondents, increases your chance of reaching quota, and shortens time in field. And better yet, it means your data is based on the right people – not close proxies.

Real-world example (fictional)

Consider a brand testing a new meat substitute product. Without pre-profiled data, they might need to screen hundreds of respondents just to identify vegetarians who’ve purchased meat alternatives in the past 3 months. But with Toluna profiling, they can target that group before launching the survey, improving fielding speed and data quality, while keeping costs predictable.

Why expertise still matters

While Toluna’s interface makes targeting accessible, expert oversight enhances results. Many internal teams aren’t familiar with the full range of attributes available or how to sequence screeners and profile filters effectively. That’s where On Demand Talent – seasoned professionals who understand sampling logic, audience targeting, and platform capabilities – make a difference.

With their help, teams can avoid pitfalls like overly narrow screeners or unclear logic chains that compromise survey feasibility. They help translate business questions into precise sampling strategies, ensuring your research remains both on-objective and on-budget.

In a world where research needs to be fast, flexible, and focused, precise sampling through profiling is no longer optional – it’s essential. And when guided by a skilled human lens, the data you gather becomes a true asset for decision-making.

One of the biggest challenges in market research sampling is over-screening – asking too many qualifying questions in a survey to find the right respondents. While some screening is necessary, excessive filtering wastes budget, drives up time-to-field, and frustrates participants. The good news? Using Toluna's pre-profiled audience data can significantly reduce the need for excessive screening upfront.

Toluna’s profiling data includes detailed, verified attributes about respondents – from demographics and buying habits to media preferences and brand usage. When tapping into these pre-existing traits, researchers can target the most relevant audience segments with greater precision before the first survey question is asked.

Why Over-Screening Happens

Over-screening typically occurs when researchers can't confidently locate qualified respondents from the start. For example, a team looking to reach parents of toddlers in urban areas who buy organic snacks may blanket-screen a generalized panel to find them. This approach is costly, not only financially but also in terms of feasibility and completion rates.

With Toluna profiling, that same team can start with a filtered sample that already matches key traits, minimizing the need for additional gatekeeping questions.

Benefits of Reducing Screening Questions

• Improved incidence rates – better matches mean fewer dropouts and screen-outs
• Shorter surveys – creates a better respondent experience
• Faster fieldwork – more qualified participants, faster responses
• Optimized resources – more budget goes to analysis, not recruitment

Let’s consider a fictional case: a new beverage brand wants feedback from Gen Z consumers who favor plant-based alternatives. Rather than screening hundreds of participants with multiple qualifying questions, they use Toluna profiling data to pre-select individuals aged 18–25 with a history of plant-based consumption. The survey reaches the right audience faster, leading to better insights and less waste.

Reducing unnecessary screeners isn’t only about cost – it’s about protecting the integrity and efficiency of your entire study. With fewer barriers to participation and more direct targeting, your data becomes cleaner, faster, and easier to interpret – setting the stage for impactful decision-making.

While DIY research platforms like Toluna offer powerful tools for targeting and sampling, using them effectively still requires expertise. Having access to consumer data insights is only half the equation – making the right decisions with that data is what drives successful outcomes. That’s where experienced researchers come in.

Expert insights professionals understand how to navigate trade-offs between sample precision, screening criteria, and survey feasibility. They know which profiling attributes matter most for a given research goal, and how to structure sampling plans that are both cost-efficient and data-rich.

Feasibility Isn’t Just Technical – It’s Strategic

Feasibility refers to how practical it is to reach your desired audience within your project’s time and budget. A study may be technically possible on a platform like Toluna, but without clear strategic planning around targeting and incidence rates, feasibility issues can surface quickly. For example:

• Overly narrow targeting leads to delays or inflated costs
• Misaligned screening criteria lower participation rates
• Unrealistic sample sizes force trade-offs mid-field

Expert researchers help proactively avoid these pitfalls. They ask: Is the sample feasible? Are we optimizing the profiling variables? Is there a better way to structure this for success?

Even the smartest DIY tools don’t replace strategic thinking. Professionals spot where profiling data may be incomplete or inconsistent, suggest alternatives when incidence is low, and weigh sample quality against speed and cost. This level of discernment ensures research doesn't just stay on track – it stays on purpose.

Without this guidance, teams risk running DIY studies that either underperform or require costly rework later. That’s why leading research teams often pair tools like Toluna with flexible access to expert guidance – enhancing both productivity and data integrity.

As more organizations adopt DIY research tools, they often discover that technology alone isn’t enough. Getting meaningful results still depends on the people behind the tools – and that’s exactly where SIVO’s On Demand Talent makes a difference.

On Demand Talent connects you with seasoned consumer insights professionals who know how to get the most out of platforms like Toluna. These aren’t freelancers or junior hires. They’re flexible, high-caliber experts who quickly plug into your team and elevate your research execution without slowing you down.

Turning Tools into Capabilities

DIY platforms make it easy to build and launch surveys, but how confident are you in the decisions that guide them? Our On Demand Talent helps you:

• Translate business needs into effective sampling plans using Toluna profiling
• Determine which pre-profiled traits drive the most valuable audience targeting
• Optimize screening efficiency and improve incidence rates
• Quality-check data streams to ensure consistent, credible outputs

Put simply, our experts make sure your research not only runs smoothly, but stays true to your objectives. They help reduce guesswork, avoid common mistakes, and build internal confidence in your insights efforts.

Consider a fictional example: a startup in the food delivery space wants agile insights on shifting customer behaviors. They’ve invested in Toluna for speed, but their small team lacks deep sampling expertise. By bringing in an On Demand Talent expert for a 6-week sprint, they develop a smarter use of profiling data, increase survey completion rates, and uncover high-impact insights without adding permanent headcount.

Whether you need short-term help launching a study, or a partner to build internal capability with your existing tools, On Demand Talent gives you the flexibility and expertise to drive results. It’s how leading brands balance speed, quality, and strategy – all while maximizing their investments in DIY research technology.