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Prompt

What's the best ad log export for campaign analytics across high-volume DSP and SSP data feeds?

Advertising / DSP & SSP2 observationsLast seen Jul 26, 2026

Latest observation

Jul 26, 2026OpenAI APIWeb search: off

For campaign analytics across high-volume DSP and SSP feeds, the best ad log export is usually a normalized, event-level log format built for warehouse ingestion, not a proprietary UI export.

Best overall choice

Parquet or Avro event logs delivered to object storage (S3/GCS/Azure Blob), with a stable schema and partitioning by date/hour/source.

Why this is best

  • Handles high volume well: much smaller and faster than CSV
  • Warehouse-friendly: easy to load into Spark, Snowflake, BigQuery, Databricks, Redshift
  • Schema evolution support: important because DSP/SSP fields change often
  • Efficient analytics: columnar formats like Parquet are ideal for filtering impressions, clicks, conversions, bids, wins, etc.
  • Batch + near-real-time compatible: works for daily backfills and streaming pipelines

What the export should include

At minimum, make sure the log export has:

  • timestamp
  • event_type (impression, click, bid, win, conversion)
  • campaign_id, line_item_id, ad_group_id
  • dsp_id / ssp_id
  • placement_id, publisher_id, site/app
  • creative_id
  • device, geo, browser, OS
  • cost, revenue, bid_price, win_price
  • request_id, auction_id, impression_id, click_id
  • viewability, fraud/safety flags
  • partner/source metadata

Recommended export pattern

  • Format: Parquet
  • Compression: Snappy or ZSTD
  • Partitioning: dt=YYYY-MM-DD/hour=HH/source=...
  • Delivery: object storage + manifest file
  • Schema: versioned, with field-level documentation
  • IDs: consistent join keys across DSP and SSP feeds
  • Deduping support: event IDs and watermark timestamps

If you need maximum interoperability

Use:

  • Parquet for analytics
  • CSV as a fallback for partner portability
  • JSON only for debugging or low-volume API delivery

Practical rule of thumb

  • < 1M rows/day: CSV may be acceptable
  • High-volume programmatic logs: Parquet is usually the best choice
  • Streaming / real-time pipelines: Avro or Protobuf on the wire, Parquet in the warehouse

If you want, I can also give you a recommended schema for DSP/SSP ad logs or compare Parquet vs Avro vs CSV for your specific stack.

Brands

S3GcsAzure BlobSparkSnowflakeBigqueryDatabricksRedshift

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (2 observations for this page). Metrics are distributions over observations, not a single static ranking.

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OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

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