Method for categorizing a seller relative to a vendor
View Patent ↗Disclosed are methods for competitive pricing implemented in software for commerce in an electronic marketplace. A vendor may identify rivals: competitors against which the vendor most directly competes by dint of having similar reputation and market positioning. Using specified pricing models applied to filtered price data periodically gathered by spider-crawling competitors on the Internet, a vendor may adjust product prices to match rivals while accounting for overall marketplace price trends.
1. A computer-implemented method for categorizing a seller relative to a vendor comprising:
storing an overall pricing model for a vendor,
wherein an overall pricing model comprises a position within a ordinal range of pricing levels, and
wherein said overall pricing model relates to a composite representation of item pricing models for a set of on-sale items;
storing product-specific data for a first set of items,
wherein said first set comprises a plurality of items;
determining a product mix comprising a plurality of items from said first set;
storing said product mix;
reading said product mix data as a basis for search;
whereby finding, via network connection, for a first set of sellers, current prices for a result set of items,
wherein said first set of sellers comprises at least a first seller,
wherein said first set of sellers does not include said vendor,
as current prices for a plurality of on-sale items in said product mix by said vendor are available from a database without network search, and
wherein said result set comprises a plurality of items in said product mix;
storing said result set item prices;
statistically characterizing respective item price data by determining data representative of an item price curve for respective items in said result set;
storing said item price curve data;
deriving respective seller item pricing models for a plurality of items in said result set,
wherein a said item pricing model comprises a position within a relative range of pricing levels for a said item based upon said item price curve data;
determining an overall pricing model for said first seller using a plurality of said first seller item pricing models;
categorizing said first seller by at least in part comparing said first seller's overall pricing model to at least one threshold of similarity to said vendor's overall pricing model; and
storing said first seller categorization.
2. The method according to claim 1 , further comprising:
determining said first seller as a rival to said vendor based, at least in part, upon a plurality of factors calculated by computer and input by a computer user,
wherein a rival comprises the highest threshold of similarity to said vendor.
3. The method according to claim 1 , wherein determining said product mix, at least in part, upon at least one statistical measure of a said item's financial significance to said vendor.
4. The method according to claim 1 , wherein determining said product mix using a predetermined item categorization.
5. The method according to claim 1 , wherein said product mix comprises a representational cross-section of items offered on-sale by said vendor.
6. The method according to claim 1 , further comprising determining said first seller as a rival to said vendor using, at least in part, statistical analysis.
7. The method according to claim 1 , further comprising determining said first seller as a rival to said vendor using, at least in part, input received from at least one user interface device.
8. The method according to claim 1 , wherein determining at least a first item for said product mix, at least in part, based upon the category of said first item.
9. The method according to claim 1 , wherein said item price curve is at least partly characterized by an algebraic function.
10. The method according to claim 1 , wherein determining said product mix, at least in part, using comparative statistical analysis of items from said first set of items.
11. The method according to claim 1 , wherein determining said product mix, at least in part, using historical revenue of items from said first set of items.
12. The method according to claim 1 , further comprising:
storing a plurality of predetermined overall pricing models; and
determining said first seller as belonging to a said predetermined overall pricing model.
13. The method according to claim 1 , wherein determining said product mix, at least in part, by selecting items from a plurality of predetermined categories.
14. The method according to claim 1 , wherein categorizing said first seller, at least in part, by comparing the items on sale by said first seller to a plurality of items in said product mix.
15. The method according to claim 1 , further comprising setting the price of an on-sale vendor first item based upon an item pricing model for said first item derived from data from sellers in the category of said first seller.