Talking Insights

The Future of Data Quality in Research with Stefan Boom

ESOMAR Season 3 Episode 13

In this episode of ESOMAR’s Talking Insights, Andrea D'Agostino engages with industry expert Stefan Boom (Dynata) to discuss the critical topic of data quality in research. They explore the evolution of data quality concerns over the years, particularly in light of increasing fraudulent behaviour and the challenges of engaging respondents. The conversation delves into strategies for ensuring data quality, including sourcing respondents, survey design, and the implementation of AI and machine learning technologies. Finally, they discuss the importance of choosing the right data provider and the ongoing challenges faced by the industry in maintaining high standards of data integrity.

Key takeaways
- Data quality has become a significant concern in recent years.
- Fraudulent behavior, such as click farms, has increased.
- Engagement in surveys has decreased over time.
- Sourcing a diverse range of respondents is crucial.
- Survey design impacts the quality of data collected.
- AI and machine learning can enhance data quality checks.
- Education for clients is essential to improve data quality standards.
- Panel companies face challenges in maintaining data integrity.
- Quality Score helps identify good and bad respondents.
- The industry must balance client demands with data quality. 

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Talking Insights is a Research World and Esomar production.

Hosted by Antonio Almeida

Music by FreeMusicForVideo from Pixabay

Graphics by Brandon Heim

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If you’d like to be featured in a future episode or share your story, send us an email at podcast@esomar.org.

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