Striving for quality: A privacy-compliant model

In our previous posts we shared our thoughts on how trust is a decisive factor in the research industry for successful quality behavioral studies. Because of its intrusive nature, participants need to experience behavioral research as being trustworthy and transparent regarding the use of their data. Recent data misuse cases by private companies and governments entail an extra effort for the market research industry to gain and maintain public trust.

Including behavioral data within the research design improves the research in various ways. Combined with surveys, it provides better insights into consumer behavior and makes the data collection more efficient. Next to that, behavioral data improves the overall research experience for the participant. Using passive metering as a targeting tool to select the survey sample has proven to result in a higher survey relevance and by that in a higher survey satisfaction rate.

However, potential participants may hesitate to install a data collection app on their devices. So, how can we build confidence?

Transparency and control for research participants

When inviting users to participate in a behavioral research, it is important to properly inform the user about the purpose of the research and what is done with the collected data.

Moreover, we believe in a model that empowers participants to take control of their data. The following measures can help to facilitate the recruitment and retention of participants for passively metered behavioral studies:

  • White list: the user can set a list of websites which won’t be recorded by the meter.
  • Pause function: the user can pause and resume the meter whenever she/he wants.
  • Ex-post removal function: the user can browse through the data and remove selected data, before he sends it
  • Easy uninstall process: the user should be able, in no more than a few clicks, to fully uninstall the meter.

When analysing the data, it should be taken into account if the user opted for any of the above mentioned measures, since it could affect the results of the study.

Besides being transparent with the data that is collected and enable users to decide what information they are willing to share, keeping confidential information secure is essential.

In the next post we will present two measures to preserve confidentiality even in the case of a security breach.

Written by Ezequiel Paura

Data enthusiast. BA in Political Science, currently writing MA Thesis on behavioral research. Joined the Netquest team as Panel Quality Manager in May 2016.

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