AI & Technical question

Replit wants optimization based on trustworthy conversion signals, not noisy platform defaults. Define the event taxonomy, identity and attribution approach, and client-side/server-side instrumentation you’d require from signup through retained activation. How would you handle latency, deduplication, audience exclusions, and warehouse reconciliation so bidding systems can optimize in near real time?

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What this question tests

Tests technical instrumentation design for trustworthy conversion signal that ad platforms can optimize against in near real time.

How to approach it

  1. Define an event taxonomy anchored on true conversion milestones, signup, first project run, and retained activation at a set day threshold, not vanity events.
  2. Design identity resolution that stitches anonymous ad click through to authenticated user, using a durable identifier that survives across sessions and devices where possible.
  3. Combine client side events for fast signal with server side events for accuracy and resilience to ad blockers, sending both to the ad platforms.
  4. Handle latency by sending early proxy events, like signup, quickly while backfilling the platform with the stronger retained activation signal once available.
  5. Deduplicate events between client and server pipelines using a shared event ID, and apply audience exclusions to suppress users who already converted from further spend.
  6. Reconcile warehouse truth against what was sent to ad platforms on a regular cadence, catching drift before it silently corrupts bidding decisions.

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