SAMPLE Digital Advertiser Insights | 4,000+ Advertisers / 57K+ Parent Companies / 123K+ Brands / ...

Key Data Elements

• Advertiser and brand identifier
• Parent company mapping (57,000+ parent companies, 123,000+ brands)
• Platform attribution (Amazon, Google, Meta, Reddit, Snap, X, Netflix, Disney, The Trade Desk, The New York Times)
• Weekly spend estimate (modeled, CPM-based)
• Ad format coverage (display, native, mobile, video, audio, TV, radio, print)
• Time series with 2 to 7 years of history depending on platform

Coverage

• 4,000+ advertisers tracked at the brand and parent company level
• Platforms include Amazon, Google, Meta, Reddit, Snap, X (Twitter), Netflix, Disney, The Trade Desk, and The New York Times
• U.S.-dominant coverage with some international advertiser visibility
• 2 to 7 years of history depending on platform
• Data sources include Ad Intelligence (impression-based panel), Ad Agency Panel, Web Scraping, and Receipt Panel Data

Delivery

• Weekly delivery, updated every Wednesday end of business day UK time
• AWS S3 and platform dashboard access
• Compatible with systematic, quantitative, and fundamental research workflows

Primary Use Cases

• Tracking advertiser spend trends and platform mix shifts ahead of earnings
• Benchmarking brand-level ad activity against sector peers
• Modeling ad revenue for digital platforms including Meta, Google, and Amazon
• Identifying acceleration or deceleration in advertiser budgets as an early signal for platform revenue
• Quantitative signal generation and cross-sectional research on advertising activity

Oxford Data Plan's Advertiser Insights product delivers weekly, brand-level digital advertising spend estimates across 4,000+ advertisers, 57,000+ parent companies, and 123,000+ brands, spanning all major digital platforms. Built from exclusive commercial agreements with large-scale digital advertising data providers, this dataset gives equity investors and quantitative teams a proprietary view into advertiser-level spend activity not available through traditional vendors or commoditized data sources.

Data is collected via a U.S.-centric panel of consented users whose anonymized browsing activity is monitored to identify ads actively served across publisher properties. All observations are impression-based, reflecting ads actually seen by users rather than declared or inferred placements. Observed ads are programmatically detected, mapped to advertisers and brands, and attributed to platforms across display, native, mobile, video, and audio formats.

Spend is modeled using CPM-based estimation methodologies and aggregated at the advertiser, brand, platform, and weekly levels. The dataset also incorporates broadcast stream detection for TV and radio, and digitized print publications, making it one of the few datasets to cover digital, TV, radio, and print advertising activity in a single feed.

Each brand's observed spend share is used to allocate platform-level ad revenue estimates at the advertiser level. Advertising agency modeling is handled separately using aggregated agency client spend data combined with publicly available CPM data, and does not draw on panel data as an MNPI safeguard. The dataset is U.S.-weighted and best suited for trend analysis, relative spend comparisons, and quantitative signal generation rather than invoice-level precision.