Abstract
A system is described for addressing challenges related to international trade tariffs in e-commerce. The system is configured to ingest global tariff schedules, including published future changes, and can use an artificial intelligence (AI) model to map retailer product stock-keeping units (SKUs) to Harmonized System (HS) codes to assist in determining applicable tariffs. The system may then calculate current and anticipated landed costs. This analysis can be used to generate pricing and advertising bid recommendations for retailers and to provide proactive alerts to consumers about potential upcoming tariff-driven price adjustments. Such features may support price and advertising efficiency for retailers and enhance transparency for shoppers.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Gaikar, Kshitij and Mittal, Pushkar, "Tariff Forecasting to Inform Dynamic Pricing and Advertising Bidding for Online Retail", Technical Disclosure Commons, (September 04, 2025)
https://www.tdcommons.org/dpubs_series/8550