Data Collection
Sampling That Reflects Reality, Not Randomness
Our sampling engine uses AI to manage hundreds of nested quota permutations in real time - ensuring sample stability not just in aggregate, but within every key segment. The result: cleaner data, steadier trendlines, and true signal across waves.
Access to over 100 million B2C and B2B respondents in over 50 global markets
We partner with hundreds of high-quality, global sample sources that tailor incentives to recruit a variety of audiences. The scale provided by many suppliers allows us to employ rigorous data quality thresholds without sacrificing speed, sample size, or representativeness.
Industry-leading Quality
Every survey is subject to four stages of AI and human quality control. Responses that fail a single check are automatically replaced
Unmatched Speed and Scale
Surveys are programmatically administered to multiple sample sources simultaneously, dramatically expediting data collection
Flexible Collection Cadences
Collect data on a weekly basis, for continuous view or field periodically on a monthly, quarterly, or annual basis.
Reach B2C or B2B Audiences
Use a combination of targeting and screening criteria to access niche consumer segments or specialized B2B and healthcare audiences
Dynamic Sampling
Sample can be modified at any point on a national or postal code specific level to measure impact of targeted or market-specific campaigns
Passive Behavioral Tagging
Target respondents using innovative passive tagging methodologies such as geofencing, pixel-tracking, and receipt capture
Maximum Diversity
Every survey is taken by respondents from a wide variety of curated sample sources. We understand that people aren’t all motivated by the same incentives, so we choose suppliers who tailor rewards to specific audiences. Incentives include cash, gift cards, redeemable points, donations to charities, and more. Incentive rates are variable (i.e., harder to reach audiences are given larger incentives).
Negligable Panel Bias
Through a combination of sampling efficiency, audience diversity, and rigorous quality thresholds, our data is effectively controlled for panel-bias. Because our methodology is panel-agnostic, our data sets can be trended over time with minimal panel-specific risk (e.g. panel suddenly goes out of business or drops in quality).
Minimal Panel Exhaustion
A large, diverse sample pool helps us manage against panel fatigue and avoid repeaters. Minimizing panel fatigue is particularly important to prevent fraud and survey gaming in longitudinal tracking studies (e.g. respondents who are too familiar with the design of a brand health tracking study may fraudulently claim they are unaware of a brand to avoid answering further questions, respondents may fraudulently take the tracking survey too often to earn incentives, etc.)
Smarter Sampling, Less Weighting
Unrivaled sampling efficiency
Our sampling engine uses AI to dynamically allocate completes across nested quotas - preserving natural subpopulation balance and reducing deviation from census benchmarks. This improves sampling efficiency, reduces reliance on post-weighting, and increases the effective base size for more robust statistical testing.
A truly representative general population
We sample nationally representative audiences using census-based quotas - covering age, region, race/ethnicity, and nested combinations of gender and income. Nested quotas reduce the need for post-field weighting and improve data stability, even when analyzing niche subgroups.
“Outward Intelligence was able to hit our highly specialized healthcare audience - targeting for intricate firmographic details like practice size, role, decision making ability, and revenue - and deliver high quality results in days.”
Gaby Snyder
Head of Insights, Simple Practice
