Predictive conversion systems and methods
In one embodiment, a system and method of predicting sale transaction conversion rate of an item operates through a search of information in response to a query over a network. The item can be included in a category of items. Information for other relevant items of the category is available through network query and historical data, among others. Respective information for the other items of the category is available. The system and method includes discovering available information of the item of interest, extracting certain of the available information of the item, analyzing the certain information by comparing the information to other item information, weighting the information for the item in comparison to other items of the category, calculating a predictive score for the item of interest, and presenting the information of the item of interest ranked according to the predictive score as compared to other items of the category.
1. A computer-implemented method of generating and presenting interactive search results for unique items, the method comprising:
providing, by a computer system, a user interface that comprises functionality that enables a user to search for and interact with unique items offered for sale;
maintaining, by the computer system, one or more electronic data stores that store information relating to a plurality of unique items each comprising a plurality of attributes and a category, wherein each unique item of the plurality of unique items corresponds to a specific unique item currently or previously offered for sale, the stored information comprising at least:
predicted conversion factors associated with the plurality of unique items, each of the predicted conversion factors being representative of a predicted likelihood of conversion of one of the plurality of unique items;
information associated with the plurality of attributes, wherein each unique item of the plurality of unique items comprises a unique combination of attribute values; and
information associated with historical conversion activity of at least a portion of the plurality of unique items;
analyzing, by the computer system, the information associated with the historical conversion activity and the information associated with the plurality of attributes for the at least a portion of the plurality of unique items, determining statistically how attributes affected conversion activity associated with the at least a portion of the plurality of unique items;
generating, based on the analysis, a regression formula capable of outputting the predicted conversion factors for the plurality of unique items having a same category but a different combination of attribute values than the at least a portion of the plurality of unique items for which the historical conversion activity information is stored;
generating, by the computer system, at least a portion of the predicted conversion factors by inputting metadata related to the plurality of attributes of the plurality of unique items into the regression formula, wherein the metadata is unique to each of the plurality of unique items;
receiving, by the computer system, a user search request generated via the user interface, the user search request comprising an item search criteria;
searching, by the computer system, the one or more electronic data stores for a plurality of unique items relating to the item search criteria; and
causing display via the user interface an interactive result set based on results of the searching, the interactive result set being prioritized based at least in part on the predicted conversion factors, wherein the computer system comprises one or more physical servers.
2. The computer-implemented method of claim 1 , wherein the plurality of unique items comprise vehicles.
3. The computer-implemented method of claim 1 , wherein the plurality of unique items comprise real estate.
4. The computer-implemented method of claim 1 , wherein the plurality of unique items are associated with sales listings currently or previously offered by one or more third party systems separate from the computer system.
5. The computer-implemented method of claim 1 , wherein maintaining the one or more electronic data stores comprises updating the regression formula on a periodic basis, and updating the predicted conversion factors.
6. The computer-implemented method of claim 1 , wherein maintaining the one or more electronic data stores comprises updating the regression formula on a real-time basis, and updating the predicted conversion factors.
7. The computer-implemented method of claim 1 , wherein maintaining the one or more electronic data stores comprises receiving via a network accessible feed data related to one or more new unique items offered for sale; and storing information relating to the one or more new unique items in the one or more electronic data stores.
8. The computer-implemented method of claim 1 , further comprising:
receiving, by the computer system, user response data indicative of a user interaction with the interactive result set; and
adapting the regression formula based on the user response data such that a future interactive result set will be prioritized based at least in part on different predicted conversion factors generated using the adapted regression formula.
9. The computer-implemented method of claim 8 , wherein the user interaction comprises a selection of an item represented in the interactive result set.
10. The computer-implemented method of claim 8 , wherein the regression formula is adapted and the predicted conversion factors are updated on a real-time basis.
11. The computer-implemented method of claim 1 , wherein the search criteria is associated with at least one of the plurality of attributes of the plurality of unique items.
12. The computer-implemented method of claim 1 , wherein the same category of the different unique items comprises a vehicle category.
13. A computer readable, non-transitory storage medium having a computer program stored thereon for causing a suitably programmed computer system to process by one or more processors computer-program code by performing a method of generating and presenting interactive search results for unique items when the computer program is executed on the suitably programmed computer system, the method comprising:
providing, by the computer system, a user interface that comprises functionality that enables a user to search for and interact with unique items offered for sale;
maintaining, by the computer system, one or more electronic data stores that store information relating to a plurality of unique items each comprising a plurality of attributes and a category, wherein each unique item of the plurality of unique items corresponds to a specific unique item currently or previously offered for sale, the stored information comprising at least:
predicted conversion factors associated with the plurality of unique items, each of the predicted conversion factors being representative of a predicted likelihood of conversion of one of the plurality of unique items;
information associated with the plurality of attributes, wherein each unique item of the plurality of unique items comprises a unique combination of attribute values; and information associated with historical conversion activity of at least a portion of the plurality of unique items;
analyzing, by the computer system, the information associated with the historical conversion activity and the information associated with the plurality of attributes for the at least a portion of the plurality of unique items, determining statistically how attributes affected conversion activity associated with the at least a portion of the plurality of unique items;
generating, based on the analysis, a regression formula capable of outputting the predicted conversion factors for the plurality of unique items having a same category but a different combination of attribute values than the at least a portion of the plurality of unique items for which the historical conversion activity information is stored;
generating, by the computer system, at least a portion of the predicted conversion factors by inputting metadata related to the plurality of attributes of the plurality of unique items into the regression formula, wherein the metadata is unique to each of the plurality of unique items;
receiving, by the computer system, a user search request generated via the user interface, the user search request comprising an item search criteria;
searching, by the computer system, the one or more electronic data stores for a plurality of unique items relating to the item search criteria; and
causing display via the user interface an interactive result set based on results of the searching, the interactive result set being prioritized based at least in part on the predicted conversion factors, wherein the computer system comprises one or more physical servers.
14. The computer readable, non-transitory storage medium of claim 13 , wherein the plurality of unique items comprise vehicles.
15. The computer readable, non-transitory storage medium of claim 13 , wherein maintaining the one or more electronic data stores comprises updating the regression formula on a periodic basis, and updating the predicted conversion factors.
16. The computer readable, non-transitory storage medium of claim 13 , wherein maintaining the one or more electronic data stores comprises updating the regression formula on a real-time basis, and updating the predicted conversion factors.
17. The computer readable, non-transitory storage medium of claim 13 , wherein maintaining the one or more electronic data stores comprises receiving via a network accessible feed data related to one or more new unique items offered for sale; and storing information relating to the one or more new unique items in the one or more electronic data stores.
18. The computer readable, non-transitory storage medium of claim 13 , wherein the method further comprises:
receiving, by the computer system, user response data indicative of a user interaction with the interactive result set; and
adapting the regression formula based on the user response data such that a future interactive result set will be prioritized based at least in part on different predicted conversion factors generated using the adapted regression formula.
19. The computer readable, non-transitory storage medium of claim 18 , wherein the regression formula is adapted and the predicted conversion factors are updated on a real-time basis.
20. The computer readable, non-transitory storage medium of claim 13 , wherein the search criteria is associated with at least one of the plurality of attributes of the plurality of unique items.