DYNAMIC PRICE ELASTICITY IN UNSTRUCTURED MARKETPLACE DATA

• US 20150161635A1
• Filed: 12/10/2013
• Published: 06/11/2015
• Est. Priority Date: 12/10/2013
• Status: Abandoned Application

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Yuan, Ted Tao, Chen, Zhaohui, Fain, Daniel
• Application Number:
  US14/101,491
• Publication Number:
  US 20150161635A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors

Abstract

In an example embodiment, a pseudo product group for an item to be listed in an online marketplace having unstructured data is determined. Then, a fair market price for the item is determined using past data from listings in the pseudo product group. The fair market price may be used as a reference price in a curve of price elasticity versus price to obtain a price elasticity value. A price range may then be recommended to a user for the listing based upon the fair market price and the price elasticity value.

Claims

1. An apparatus comprising:

a memory; and

a seller tool executable by a processor and configured to;

determine a pseudo product group for an item to be listed in an online marketplace having unstructured data;

derive a fair market price for the item using past data from listings in the pseudo product group;

use the fair market price as a reference price in a curve of price elasticity versus price to obtain a price elasticity value; and

recommend a price range to a user for the listing based upon the fair market price and the price elasticity value.

2. The apparatus of claim 1, wherein the unstructured data is historical data that lacks demand information for the item.

3. The apparatus of claim 1, wherein the pseudo product group is one of a plurality of mutually exclusive product categories.

4. The apparatus of claim 1, wherein the user is a seller of the item to be listed.

5. A method comprising:

determining a pseudo product group for an item to be listed in an online marketplace having unstructured data;

deriving a fair market price for the item using past data from listings in the pseudo product group;

using the fair market price as a reference price in a curve of price elasticity versus price to obtain a price elasticity value; and

recommending a price range to a user for the listing based upon the fair market price and the price elasticity value.

6. The method of claim 5, wherein the price range is recommended to the user in a seller tool that is utilized when the user lists the item for sale in the online marketplace.

7. The method of claim 6, wherein the price range is presented to the user in the seller tool next to an input box where the user enters a price at which to sell the item.

8. The method of claim 5, wherein the unstructured data is historical data that lacks demand information for the item.

9. The method of claim 5, wherein the pseudo product group is one of a plurality of mutually exclusive product categories.

10. A non-transitory machine-readable storage medium having embodied thereon instructions executable by one or more machines to perform operations comprising:

determining a plurality of pseudo product groups in an online marketplace;

determining dynamic price elasticity in each of the pseudo product groups;

receiving a proposed change to a search ranking algorithm;

determining, based on the dynamic price elasticity in each pseudo product group affected by the proposed change to the search ranking algorithm, an estimated total revenue impact of the proposed change; and

determining whether or not to implement the proposed change based on the estimated total revenue impact.

11. The non-transitory machine-readable storage medium of claim 10, wherein the operations further comprise:

summing up revenue in each of the pseudo product groups;

computing a revenue weight for each pseudo product group from the revenue; and

deriving a set of queries affected by the proposed change in a search ranking algorithm.

12. The non-transitory machine-readable storage medium of claim 11, wherein the operations further comprise:

for each of the derived set of queries;

determining pseudo product groups that a first preset number of search results from an old search rank algorithm belong to;

determining average sale prices of the top preset number of listings in the determined pseudo product groups for the old search rank algorithm;

determining pseudo product groups that a first preset number of search results from a new search rank algorithm belong to; and

determining average sale prices of the top preset number of listings in the determined pseudo product groups for the new search rank algorithm.

13. The non-transitory machine-readable storage medium of claim 11, wherein the determining an estimated total revenue impact of the proposed change includes:

computing an average sale price and price change across all queries in the derived set of queries;

computing a revenue change in each pseudo product group from the average sale price and price change; and

computing a total revenue impact with revenue weights based on the revenue change.

14. The non-transitory machine-readable storage medium of claim 13, wherein the computing a revenue change uses the formula (1+e_v)*(dP_v/P_v), wherein e_v is a dynamic price elasticity, dP_v is the price change and P_v is the average sale price.

15. The non-transitory machine-readable storage medium of claim 13, wherein the computing a total revenue impact with revenue weights uses the formula Σ

v(1+e)*W_v*dP_v/P_v, wherein W_v is the revenue weight for each pseudo product group.

16. The non-transitory machine-readable storage medium of claim 10, wherein the dynamic price elasticity is determined by deriving a fair market price for an item using past data from listings in a pseudo product group and using the fair market price as a reference price in a curve of price elasticity versus price to obtain a price elasticity value.

17. The non-transitory machine-readable storage medium of claim 16, wherein the dynamic price elasticity is determined using unstructured data.

18. The non-transitory machine-readable storage medium of claim 17, wherein the unstructured data is historical data that lacks demand information for an item.

19. The non-transitory machine-readable storage medium of claim 10, wherein the pseudo product groups are a plurality of mutually exclusive product categories.

20. The non-transitory machine-readable storage medium of claim 10, wherein estimated total revenue impact is an estimate of effect on the entire online marketplace.