Research integrity at scale
Trustworthy online research starts before the first response.
KDP combines marketing-research experience with BEE Bot Detector to protect data quality, respond to suspicious traffic and run online projects at a scale that fits each client’s needs.
The challenge
Sample quality under pressure from scale.
In online research, every automated response, repeated entry or unnatural behavioural pattern can reduce the value of the data. For KDP, this created a need to protect fieldwork without adding barriers for respondents.
The priority was to combine traffic-level quality control with infrastructure that can flex for a growing number of projects and respondents, while preserving operational visibility and security.
The approach
BEE and AWS: control without friction.
Lightweight measurement on the research page
The BEE pixel records device and behavioural signals during fieldwork without changing the respondent journey.
Real-time risk assessment
Detection mechanisms help identify automation, duplicates and suspicious patterns before they reduce the quality of the dataset.
Scale that follows the rhythm of fieldwork
The AWS architecture supports variable project traffic, monitoring and repeatable managed-service operating processes.
The outcome
Research that is easier to trust.
of suspicious sessions or low-quality records identified.
peak traffic handled versus normal project load.
saved per project by the quality team.
“In online research, data quality cannot be treated as a final check. With BEE, we can identify suspicious patterns while fieldwork is in progress, protect the respondent experience and give the team a stronger basis for deciding which data to trust.”Piotr Sztabiński · Owner, KDP
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