Attribution Modeling & Bidding Logs

This dataset represents a sample of 30 days of Criteo live traffic data. Each line corresponds to one impression (a banner) that was displayed to a user. For each banner we have detailed information about the context, if it was clicked, if it led to a conversion and if it led to a conversion that was attributed to Criteo or not. Data has been sub-sampled and anonymized so as not to disclose proprietary elements.

Use case
RL Agent for Real-Time Pacing and Bidding in a Demand-Side Platform

Example observationsUser & context
uid_hash, timestamp, device_type, country, browser

Inventory
site_domain, site_cat, publisher_id, banner_size, placement

Campaign
campaign_id, ad_id, cost_type, payout_type

History features (derived)
#impr, #clicks, spend_so_far, budget_left(day), hour-of-day
Example actionsbid_price_bin
pacing_factor
(if budget control is included)
Example rewardrevenue – cost, where revenue = conversion_value