Criteo Attribution Modeling for Display Advertising Bidding

Criteo Research released this dataset for attribution modeling in display advertising. It supports research on increasing bidding efficiency, as presented at the 2017 AdKDD & TargetAd Workshop. The dataset is associated with a peer-reviewed KDD conference paper.

Use Cases

• Train models to predict conversion attribution based on user journey and impression data.
• Analyze the impact of different attribution models on bidding strategy performance.
• Build simulations to optimize campaign spend allocation using attribution signals.

Strengths

• Dataset is directly linked to a peer-reviewed research paper from KDD 2017.
• Focuses on a specific, high-value domain: attribution modeling for display advertising.

Limitations

• Specific data volume, features, and temporal coverage are not provided in the input.
• The dataset's age (from 2017) may not reflect current advertising ecosystems and user privacy regulations.

Provenance

Source

Criteo Research

Collection Method

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Freshness

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