View source for Walmart Apollo, LLC (20240338721). SYSTEM AND METHOD FOR DYNAMICALLY AND AUTOMATICALLY UPDATING ITEM PRICES ON E-COMMERCE PLATFORM simplified abstract

=SYSTEM AND METHOD FOR DYNAMICALLY AND AUTOMATICALLY UPDATING ITEM PRICES ON E-COMMERCE PLATFORM=


==Organization Name==

[[:Category:Walmart Apollo, LLC|Walmart Apollo, LLC]]


[[Category:Walmart Apollo, LLC]]

==Inventor(s)==

[[:Category:Huidong Zhang of Cupertino CA (US)|Huidong Zhang of Cupertino CA (US)]][[Category:Huidong Zhang of Cupertino CA (US)]]

[[:Category:Akshit Sarpal of Santa Clara CA (US)|Akshit Sarpal of Santa Clara CA (US)]][[Category:Akshit Sarpal of Santa Clara CA (US)]]

[[:Category:Elliot Grenn Silva of New York NY (US)|Elliot Grenn Silva of New York NY (US)]][[Category:Elliot Grenn Silva of New York NY (US)]]

[[:Category:Fangjing Fu of Bentonville AR (US)|Fangjing Fu of Bentonville AR (US)]][[Category:Fangjing Fu of Bentonville AR (US)]]

[[:Category:Fangping Huang of Sunnyvale CA (US)|Fangping Huang of Sunnyvale CA (US)]][[Category:Fangping Huang of Sunnyvale CA (US)]]

[[:Category:Yang Song of San Bruno CA (US)|Yang Song of San Bruno CA (US)]][[Category:Yang Song of San Bruno CA (US)]]

[[:Category:Weihang Ren of Foster City CA (US)|Weihang Ren of Foster City CA (US)]][[Category:Weihang Ren of Foster City CA (US)]]

[[:Category:Lijie Wan of Mountain View CA (US)|Lijie Wan of Mountain View CA (US)]][[Category:Lijie Wan of Mountain View CA (US)]]

==SYSTEM AND METHOD FOR DYNAMICALLY AND AUTOMATICALLY UPDATING ITEM PRICES ON E-COMMERCE PLATFORM - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240338721 titled 'SYSTEM AND METHOD FOR DYNAMICALLY AND AUTOMATICALLY UPDATING ITEM PRICES ON E-COMMERCE PLATFORM

==Simplified Explanation==
The patent application describes systems and methods for automatically updating item prices on e-commerce platforms. It involves generating markdown prices based on price elasticity and predicted demand data, then applying upper and lower bounds to determine the final price.

* Price elasticity and predicted demand data used to generate markdown prices
* Upper and lower bounds applied to finalize the price
* Automatic updating of item prices on e-commerce platforms

==Key Features and Innovation==
* Utilizes price elasticity and predicted demand data for pricing decisions
* Offers dynamic pricing based on availability of data
* Ensures automatic updating of item prices on e-commerce platforms

==Potential Applications==
The technology can be applied in various industries such as retail, e-commerce, and online marketplaces to optimize pricing strategies and maximize profits.

==Problems Solved==
* Efficiently updates item prices based on data-driven insights
* Helps in setting competitive prices in real-time
* Streamlines pricing processes on e-commerce platforms

==Benefits==
* Maximizes revenue by adjusting prices according to demand
* Enhances customer satisfaction with competitive pricing
* Improves operational efficiency by automating price updates

==Commercial Applications==
Dynamic Pricing Technology for E-Commerce Platforms: Enhancing pricing strategies and revenue optimization in online retail environments.

==Prior Art==
Readers can explore prior art related to dynamic pricing algorithms, machine learning in pricing strategies, and e-commerce pricing optimization techniques.

==Frequently Updated Research==
Stay updated on the latest advancements in dynamic pricing algorithms, machine learning applications in pricing, and e-commerce pricing strategies.

==Questions about Dynamic Pricing Technology==
===How does dynamic pricing benefit e-commerce businesses?===
Dynamic pricing helps e-commerce businesses stay competitive by adjusting prices in real-time based on demand and market conditions. This strategy can lead to increased sales and revenue.

===What are the key factors considered in dynamic pricing algorithms?===
Dynamic pricing algorithms consider factors such as price elasticity, predicted demand, current price, and availability of data to generate optimal pricing strategies.


==Original Abstract Submitted==

systems and methods for dynamically and automatically updating item prices on e-commerce platform are disclosed. in some embodiments, an item is offered for purchase with a current price on a website. when price elasticity data and predicted demand data for the item are both available, a first markdown price is generated for the item using a first model based on: the price elasticity data, the predicted demand data, and the current price. when the price elasticity data and the predicted demand data are not both available, a second markdown price is generated for the item using a second model based on: a decay rate, the current price, and availability of the predicted demand data. a bounded price is generated by applying an upper bound and a lower bound to either the first markdown price or the second markdown price; and transmitted to a computing device for updating the current price of the item on the website.



[[Category:G06Q30/0201]]
[[Category:CPC_G06Q30/0206]]