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Fireside chat: Solving media and advertising challenges

Panelat Big Data & AI Toronto 2021 · 2021-10-13..10-14· [privacy-and-compliance]
links:none on file
name:Noel Geer
links:none on file
slides:none on file

Predicts three audience paths: 30% identified IDs and the rest via contextual plus cohorts (roughly 70%), urges immediate work on first‑party collection, modeling and consent. Recommends CMPs, clean rooms, private marketplaces and IAB Tech Lab’s new unique‑ID standard (out for comment), cites ~30% iOS opt‑in and ~200M suspicious Canadian device records as reasons to act. Notes simple anti‑fraud tools like ads.txt and micro‑geo (850,000 Canadian postal codes) as practical, deployable levers.

AI-written summary · about

  1. 0:00Welcome and introductions
  2. 2:52Future of measurement and data
  3. 12:31First-party data and clean rooms
  4. 23:19Future-proofing strategies
  5. 30:04Fraud prevention and verification
  6. 39:30Geographical data insights
  7. 42:40Closing remarks and resources
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