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134 - Unpacking Programmatic Sampling with JD Deitch: Challenges, Innovation, and the Future of Research

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Contenuto fornito da Greenbook. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Greenbook o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

In this episode, JD Deitch, veteran market researcher and advisor, joins us to dive deep into the complexities of programmatic sampling, data quality, and the evolving role of AI in research. We discuss how the "enshittification" of sampling has impacted the participant experience and what innovative solutions are emerging to address these challenges.

JD shares his thoughts on the engagement crisis, polling representivity, and the critical importance of collective action in the research industry. Whether you're a seasoned researcher or exploring new methodologies, this conversation provides actionable insights to navigate the future of market research with confidence.

In this episode, we’ll explore:

  • The Enshittification of Sampling: JD explains the term coined by Cory Doctorow and its relevance to the state of programmatic sampling.
  • Polling Challenges: Why representivity and engagement issues in surveys can lead to significant errors in public polling and beyond.
  • The Role of AI in Research: How technology is reshaping qualitative and quantitative methods while exposing new risks.
  • Client Expectations and Data Quality: The delicate balance of price, speed, and quality in client demands—and why that needs to change.
  • Future Outlook: Why scalable qualitative methods, synthetic data, and innovative panels are reshaping research—and what’s next for the industry.

Resources/Links:


You can reach out to JD on LinkedIn.

Many thanks to JD Deitch for joining the show. Thanks also to our production team and our editor at Big Bad Audio.

  continue reading

134 episodi

Artwork
iconCondividi
 
Manage episode 453137859 series 3120303
Contenuto fornito da Greenbook. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Greenbook o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

In this episode, JD Deitch, veteran market researcher and advisor, joins us to dive deep into the complexities of programmatic sampling, data quality, and the evolving role of AI in research. We discuss how the "enshittification" of sampling has impacted the participant experience and what innovative solutions are emerging to address these challenges.

JD shares his thoughts on the engagement crisis, polling representivity, and the critical importance of collective action in the research industry. Whether you're a seasoned researcher or exploring new methodologies, this conversation provides actionable insights to navigate the future of market research with confidence.

In this episode, we’ll explore:

  • The Enshittification of Sampling: JD explains the term coined by Cory Doctorow and its relevance to the state of programmatic sampling.
  • Polling Challenges: Why representivity and engagement issues in surveys can lead to significant errors in public polling and beyond.
  • The Role of AI in Research: How technology is reshaping qualitative and quantitative methods while exposing new risks.
  • Client Expectations and Data Quality: The delicate balance of price, speed, and quality in client demands—and why that needs to change.
  • Future Outlook: Why scalable qualitative methods, synthetic data, and innovative panels are reshaping research—and what’s next for the industry.

Resources/Links:


You can reach out to JD on LinkedIn.

Many thanks to JD Deitch for joining the show. Thanks also to our production team and our editor at Big Bad Audio.

  continue reading

134 episodi

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