Abstract
A traffic predictor system can be used to predict customer traffic to physical stores. The system receives data describing search queries from a population of users. The system identifies intents of the population of users based on the search queries from the population of users. The intents may include local intent, i.e., intent to visit a physical store, and/or a product intent, i.e., intent to obtain a product. The system determines probabilities that the identified intents will lead to customers visiting the store. Subsequently, the system can generate traffic predictions for stores based on the determined probabilities for the identified intents.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Peddinti, Raghava Viswa Mani Kiran and Dabbiru, Lakshmi Kumar, "REAL TIME TRAFFIC PREDICTION FOR PHYSICAL STORES", Technical Disclosure Commons, (January 25, 2016)
https://www.tdcommons.org/dpubs_series/123