Design an ads audience targeting system

## Problem Design an **ads audience targeting system** that allows advertisers to upload large user lists and then target (or exclude) those users when serving ads. ### Requirements - Advertiser can create **audiences** and upload membership data at large scale (e.g., millions to billions of identifiers). - Support common identifiers: email/phone (hashed), mobile ad IDs, internal user IDs. - Audience can be attached to ad groups/campaigns as **include** or **exclude** targeting. - During ad serving, given a user request, the system must quickly determine which audiences the user belongs to (or whether the user matches an audience) to filter eligible ads. - Handle incremental updates (add/remove users), audience expiration, and deletion. ### Non-functional requirements - Low latency in serving path (typically single-digit milliseconds budget). - High throughput for ingestion. - Privacy/security: encryption, access control, audit logs, retention. - Multi-tenant isolation across advertisers. ### Deliverables Explain: 1. APIs and data flow for upload → processing → storage. 2. Storage/indexing approach for membership lookup at serving time. 3. How you scale ingestion and serving, and how you monitor correctness. 4. Tradeoffs (Bloom filters vs key-value lookup vs inverted index, batch vs streaming).