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Exposing the myth of ‘perfect data’ with Piotr Prędkiewicz (FORMEL SKIN)

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Manage episode 501325220 series 3587809
Content provided by Remerge. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Remerge or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Questions Piotr addresses in this episode:

  • What is FORMEL SKIN, and how does it solve dermatology’s bottleneck in Germany?
  • How did Piotr’s career in analytics develop across multiple verticals?
  • Why is ‘perfect data’ a myth in mobile marketing?
  • How do you responsibly track and aggregate users before registration?
    What’s the difference between front-end and back-end behavioral data?
  • How do device/user mismatches and changes create analytics headaches?
  • What are the new challenges and gray areas in privacy (GDPR, CCPA, device fingerprinting)?
  • Where does fraud hide in aggregated data, and how do you find it?
  • Why does fraud persist, and what incentives make it so durable?
  • How could success in mobile marketing be measured differently to promote collaboration and integrity?

Timestamps
(0:00) – Introducing FORMEL SKIN, Piotr’s role, and Germany’s digital dermatology
(1:18) – Marketing analytics in dating, fintech, health
(2:50) – Why ‘perfect data’ is a myth
(5:00) – Assigning pseudo-user IDs, device-based tracking
(6:00) – Aggregated data, ‘chasing ghosts,’ and its pitfalls
(8:00) – Combining front-end and back-end data; challenges in stitching
(9:36) – Device vs. user: confusion, mismatches, and noise
(11:13) – Balancing privacy vs. marketing needs; legal and business conflicts
(12:30) – Device fingerprinting: what’s legal, what’s risky, and why
(14:22) – The end of one-to-one attribution; rise of aggregated, top-level analysis
(16:05) – Marketing fraud: what’s changed, sneaky affiliate/network tricks
(19:08) – Incentives, alignment failures, and why fraud persists
(21:40) – Filtering fraud: long onboarding, compliance, and technical vigilance
(23:38) – ‘Success’ in mobile marketing and why responsibility must be shared
(32:08) – Wrap up

Quotes
(2:50) “Don’t expect perfect data – especially in marketing where different data sources are being combined.”
(5:10) “You try to anchor it to the device…within all the data security and the privacy setup and anchor it to this entity and create one entity.”
(15:26) “We can use aggregated data for strategic decisions, like how to shift budgets from channel A to B.”

Mentioned in This Episode

  continue reading

222 episodes

Artwork
iconShare
 
Manage episode 501325220 series 3587809
Content provided by Remerge. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Remerge or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Questions Piotr addresses in this episode:

  • What is FORMEL SKIN, and how does it solve dermatology’s bottleneck in Germany?
  • How did Piotr’s career in analytics develop across multiple verticals?
  • Why is ‘perfect data’ a myth in mobile marketing?
  • How do you responsibly track and aggregate users before registration?
    What’s the difference between front-end and back-end behavioral data?
  • How do device/user mismatches and changes create analytics headaches?
  • What are the new challenges and gray areas in privacy (GDPR, CCPA, device fingerprinting)?
  • Where does fraud hide in aggregated data, and how do you find it?
  • Why does fraud persist, and what incentives make it so durable?
  • How could success in mobile marketing be measured differently to promote collaboration and integrity?

Timestamps
(0:00) – Introducing FORMEL SKIN, Piotr’s role, and Germany’s digital dermatology
(1:18) – Marketing analytics in dating, fintech, health
(2:50) – Why ‘perfect data’ is a myth
(5:00) – Assigning pseudo-user IDs, device-based tracking
(6:00) – Aggregated data, ‘chasing ghosts,’ and its pitfalls
(8:00) – Combining front-end and back-end data; challenges in stitching
(9:36) – Device vs. user: confusion, mismatches, and noise
(11:13) – Balancing privacy vs. marketing needs; legal and business conflicts
(12:30) – Device fingerprinting: what’s legal, what’s risky, and why
(14:22) – The end of one-to-one attribution; rise of aggregated, top-level analysis
(16:05) – Marketing fraud: what’s changed, sneaky affiliate/network tricks
(19:08) – Incentives, alignment failures, and why fraud persists
(21:40) – Filtering fraud: long onboarding, compliance, and technical vigilance
(23:38) – ‘Success’ in mobile marketing and why responsibility must be shared
(32:08) – Wrap up

Quotes
(2:50) “Don’t expect perfect data – especially in marketing where different data sources are being combined.”
(5:10) “You try to anchor it to the device…within all the data security and the privacy setup and anchor it to this entity and create one entity.”
(15:26) “We can use aggregated data for strategic decisions, like how to shift budgets from channel A to B.”

Mentioned in This Episode

  continue reading

222 episodes

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