Abstract
An inefficiency in digital advertising may arise when campaigns do not cover a range of products on an advertiser's digital properties (e.g., a website or mobile application), a discrepancy that can be challenging to identify manually. Systems and methods are described that may act as an orchestration engine to programmatically address such discrepancies. A system can programmatically harvest inventory from an advertiser's digital property, retrieve active campaign data from an advertising account, and map both data sets to a common taxonomy to identify potential coverage gaps. The system may also enrich these findings with external market data and suggest semantically related expansion categories. This process can provide a prioritized list of opportunities to assist advertisers in improving advertising coverage and campaign expansion efforts based on the synthesized data.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
N/A, "Automated Analysis of Advertising Coverage Gaps and Taxonomic Expansion Opportunities", Technical Disclosure Commons, (August 26, 2026)
https://www.tdcommons.org/dpubs_series/11498