Fast Research, Verified Data
Panel verification, in-research quality control, ESOMAR standards, and data security. Explore how fast research is possible without compromising data quality, how the panel is verified, and why results are reliable.
Data quality in research consists of the respondent truly being in the target audience, answers being given thoughtfully, and results being produced with a verifiable methodology. At Sorbunu, data quality is ensured through 4-layer panel verification, in-research automatic quality control, and ESOMAR-standard methodology. This structure keeps results reliable while maintaining the speed of self-serve infrastructure.
Speed and Quality Are Possible Simultaneously
For a long time in consumer research, a trade-off was accepted as inevitable. Either fast and cheap but with uncertain data quality, or quality and reliable but slow and expensive.
On the fast side, there are DIY survey tools. You can set up and send a survey quickly, but whether respondents are actually your target audience and whether answers are given thoughtfully remains uncertain. Unverified panels, bot responses, and low-quality participation are common issues.
On the quality side, there are traditional research firms. Methodology is solid, panel quality is high, but the process takes weeks and costs are high.
Sorbunu combines the strengths of both approaches. The panel goes through a 4-layer verification system, automatic quality control runs in every research, and methodology follows ESOMAR standards. The process moves in hours with self-serve infrastructure. Speed comes not from compromising data quality, but from removing unnecessary steps (brief, proposal, field coordination).
4-Layer Panel Verification
The foundation of research is that the person responding is truly who they should be. Sorbunu's panel is fed from the Denebunu ecosystem and goes through a 4-stage verification.
Layer 1: Identity verification
Panelists go through phone and identity verification during registration. Multiple account detection is performed, preventing the same person from entering the panel with multiple profiles.
Layer 2: Profile verification
Demographic information (age, gender, region, income, education) is regularly updated and goes through consistency checks. Panelists with detected profile inconsistencies are flagged.
Layer 3: Behavioral cross-check
Panelists' answers are cross-checked over time. If a panelist says "I never drive" in one research but "I drive 2 hours daily" in another, this inconsistency is caught.
Layer 4: Real-time attention scoring
Response quality is evaluated in real-time in every research. Response time, attention check questions, and answer patterns are analyzed, removing low-quality participants from results.
These four layers work together to ensure every person in the panel is a real, consistent, and attentive participant. Inactive, inconsistent, or low-quality profiles are regularly cleaned from the panel.
In-Research Quality Control
Beyond panel verification, quality control mechanisms kick in within each research itself. These mechanisms work automatically during research and require no intervention.
Response time analysis
Every question has a reasonable response time. Alongside those who fill in too quickly (skipping without reading), "straight-line" participants who give all answers in the same time are also caught and removed from results.
Attention check questions
Control questions placed in the research flow verify that the participant is actually reading and thinking. Direct controls like "Please select disagree for this question" and more sophisticated logic checks are used.
Consistency check
Contradicting answers within the research are detected. A participant who says "I never used the product" but then says "I use it 3 times a week" is filtered out.
Open-ended response quality
Those giving meaningless, repetitive, or copy-paste responses to open-ended questions are detected. Responses that don't contain genuine thought are removed from results.
ESOMAR Standards and Research Ethics
Sorbunu is an ESOMAR corporate member. Panel management, sampling methodology, data processing, and reporting processes are conducted in alignment with ESOMAR research guidelines.
What this alignment means in practice:
In panel management
Panel registration, verification, and management processes compliant with the ESOMAR 28 guideline. Participant rights, compensation, and participation frequency are managed according to standards.
In data processing
Anonymized data processing. Participants' personal information is not reflected in research results. Data is processed separated from identity information.
In reporting
Research results are presented with sample profile, quality control indicators, statistical significance levels, and confidence intervals. Methodological transparency is the default standard in every report.
In research ethics
Participants are informed about the purpose of the research, the voluntary participation principle is applied, and additional protection mechanisms are activated for sensitive topics.
Statistical Significance and Sample Quality
Data quality is not measured only by panel reliability — the correct sample structure is equally determinative. Too small a sample produces risky results in terms of confidence, too large a sample creates unnecessary cost.
Especially in segment-based breakdowns, if too few people remain in a cell, even a single answer can shift the result.
Sample size
For most research, 600 participants is a good starting point. If you plan segment-based breakdowns, you need to increase the sample to ensure each segment is adequately represented. The platform shows the recommended sample size based on your research structure.
Quota management
You can control the demographic or behavioral distribution of your target audience with quota structure. Quotas like "equal gender distribution, balanced age groups" ensure the field is representative.
Data Privacy and Security
Research data is sensitive. Participant information, client data, and research content must be processed securely.
KVKK and GDPR compliance
All participant data is processed through KVKK and GDPR compliant processes. Personal information is anonymized and not reflected in research results.
Data separation
Participants' identity information and research responses are kept separate. The researcher doesn't see who the participant is, only accessing profile and response data.
Secure infrastructure
Data storage and transfer processes are conducted over secure infrastructure. Research data is protected against unauthorized access.
Client data confidentiality
Research content (question texts, visuals, concept cards) is client-specific and not shared with third parties.
Frequently Asked Questions
With a 4-layer verification system: identity verification, profile consistency check, behavioral cross-check, and real-time attention scoring. Each layer controls a different quality dimension.
Low-quality responses are automatically detected and removed from results through response time analysis, attention check questions, consistency checks, and open-ended response quality assessment. The quality control report can be viewed on the dashboard.
ESOMAR is the international professional organization of the research industry. It sets standards for panel management, sampling methodology, data ethics, and reporting. Sorbunu is an ESOMAR corporate member and works in accordance with these standards.
Panel verification processes (identity verification, multiple account detection), behavioral analysis, and in-research quality control mechanisms prevent bot responses from entering results.
Yes. All participant data is processed in KVKK and GDPR compliant manner. Personal information is anonymized and not reflected in research results. Identity information and response data are kept separate.
The platform shows the recommended sample size based on your research structure and number of segments. For most research, 600 participants is a good starting point. If segment-based breakdowns are planned, the sample needs to be increased.
For every research, sample profile, quality control indicators (number of filtered participants, valid response rate), and confidence intervals are part of the report.
See data quality for yourself.
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