Response from OpenAI’s ChatGPT:
1. Audience Segmentation & Targeting
- High-cardinality fields (e.g., cookies, device IDs, hashed emails) are essential for precise targeting.
- Enables creation of highly specific audience segments, such as “people who visited a specific product page in the last 3 days.”
2. Frequency Capping & Reach Measurement
- Unique identifiers (high cardinality) help ensure users don’t see the same ad too often.
- Accurate reach and frequency metrics depend on being able to count distinct users.
3. Attribution Modeling
- Attribution requires tracking many unique events and users across touchpoints.
- High cardinality is necessary to follow a user’s journey from impression to conversion.
4. Performance Analytics
- Granular data (e.g., performance by creative ID or keyword) often has high cardinality.
- Systems must handle this complexity to enable meaningful insights and decision-making.
5. Data Infrastructure and Cost
- High cardinality increases storage and compute complexity.
- Systems like Snowflake or BigQuery must optimize queries to handle large cardinality fields efficiently.
- Cost control and performance tuning become essential.