US 12,469,059 B2
Electronic marketplace curve sales transaction system
Colin Smith, Palo Alto, CA (US); John Lagerling, Los Altos Hills, CA (US); and Carlo Besozzi, Palo Alto, CA (US)
Assigned to MERCARI, INC., Palo Alto, CA (US)
Filed by Mercari, Inc., Palo Alto, CA (US)
Filed on Aug. 19, 2022, as Appl. No. 17/891,520.
Prior Publication US 2024/0062261 A1, Feb. 22, 2024
Int. Cl. G06Q 30/00 (2023.01); G06Q 30/0601 (2023.01)
CPC G06Q 30/0609 (2013.01) 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving, from a seller, an indication to sell a for sale item through an electronic marketplace;
generating an item curve for the for sale item based on a history of sales through the electronic marketplace of sold items that are similar to the for sale item, the item curve indicating whether the for sale item is in high demand, low demand, or neutral demand;
generating a seller curve for the seller based on a sales history of the seller through the electronic marketplace, the sales history comprising a list of items offered for sale and dates of sales, cancellations, and price adjustments;
generating, by a machine learning system, a sales curve for the for sale item based on modifying the seller curve for the for sale item based on the item curve, wherein the modifying comprises one of:
based on the item curve indicating the for sale item is in high demand, increasing a list price indicated by the seller curve, and
based on the item curve indicating the for sale item is in low demand, decreasing the list price indicated by the seller curve;
providing, via a user interface, a display of the sales curve for the for sale item;
receiving, via the user interface, a response to the sales curve, wherein the response comprises one of an adjustment or an approval of the sales curve by the seller;
modifying the machine learning system based on the response to the sales curve, wherein the adjustment comprises negative feedback and the approval comprises positive feedback to the machine learning system, and where the negative feedback and the positive feedback are used by the machine learning system in generating subsequent sales curves;
monitoring the for sale item on the electronic marketplace, for the seller, based on the approval of the sales curve;
determining, based upon the monitoring, a correspondence between the list price of the seller curve and a bid price on the for sale item; and
selling the for sale item for the seller based on the correspondence between the list price of the for sale item and the bid price.