Computer-implemented method, non-transitory computer readable storage medium, and system for enhancing listings in an e-commerce site
Embodiments described herein include modeling of seller profiles and behaviors on an e-commerce site to induce more listings and sales within the e-commerce site. For every seller and potential seller on the e-commerce site, their behaviors is to be understood and modeled in order to draw out more listings and completed sales per seller. An example embodiment of the present disclosure includes receiving a first information listing. At least one classification of the information listing may be generated performing at least one machine-learning (ML) process based at least in part on at least one ML model and the first information listing. A recommendation based on the classification of the first information listing may be generated. The recommendation may be recommending. A second information listing may be created.
1 . A computer-implemented method for enhancing listings in an e-commerce site, the computer-implemented method comprising:
receiving, via at least one computer processor, a first information listing;
receiving, via the at least one computer processor, at least one predictive feature data of the first information listing from a data warehouse;
generating at least one recommendation for a second information listing via the at least one computer processor performing at least one machine-learning (ML) process based at least in part on at least one ML model and the at least one predictive feature data of the first information listing;
caching, via the at least one computer processor, the at least one recommendation in an online cloud database;
transmitting, via the at least one computer processor, a notification comprising the at least one recommendation;
redirecting, upon receiving an input indicating an interaction with the notification, to a web page displaying the at least one recommendation, wherein the displaying provides online access of the at least one recommendation from the online cloud database; and
subsequent to the redirecting, creating the second information listing.
2 . The computer-implemented method of claim 1 , wherein the at least one predictive feature data comprises a brand or a category.
3 . The computer-implemented method of claim 1 , wherein the second information listing is complementary to the first information listing based on the at least one recommendation.
4 . The computer-implemented method of claim 1 , wherein the at least one recommendation occurs in a predetermined amount of time.
5 . The computer-implemented method of claim 1 , wherein the at least one recommendation comprises outputs of the at least one ML model.
6 . The computer-implemented method of claim 5 , wherein the outputs of the at least one ML model comprise predictive features, wherein the predictive features comprise at least one of a lifetime value, a churn score, or communication.
7 . The computer-implemented method of claim 5 , wherein the outputs of the at least one ML model comprise factual features, wherein the factual features comprise at least one of total gross merchandise value (GMV), days since last purchase, or days since last listing.
8 . A non-transitory computer readable storage medium storing instructions that, when executed by at least one computer processor, cause the at least one computer processor to perform operations comprising:
receiving a first information listing;
receiving at least one predictive feature data of the first information listing from a data warehouse;
generating at least one recommendation for a second information listing by performing at least one machine-learning (ML) process based at least in part on at least one ML model and the at least one predictive feature data of the first information listing;
caching the at least one recommendation in an online cloud database;
transmitting a notification comprising the at least one recommendation;
redirecting, upon receiving an input indicating an interaction with the notification, to a web page displaying the at least one recommendation, wherein the displaying provides online access of the at least one recommendation from the online cloud database; and
subsequent to the redirecting, creating the second information listing.
9 . The non-transitory computer readable storage medium of claim 8 , wherein the at least one predictive feature data comprises a brand or a category.
10 . The non-transitory computer readable storage medium of claim 8 , wherein the second information listing is complementary to the first information listing based on the at least one recommendation.
11 . The non-transitory computer readable storage medium of claim 8 , wherein the at least one recommendation occurs in a predetermined amount of time.
12 . The non-transitory computer readable storage medium of claim 8 , wherein the at least one recommendation comprises outputs of the at least one ML model.
13 . The non-transitory computer readable storage medium of claim 12 , wherein the outputs of the at least one ML model comprise predictive features, wherein the predictive features comprise at least one of a lifetime value, a churn score, or communication.
14 . The non-transitory computer readable storage medium of claim 12 , wherein the outputs of the at least one ML model comprise factual features, wherein the factual features comprises at least one of total gross merchandise value (GMV), days since last purchase, or days since last listing.
15 . A system, comprising:
a memory; and
at least one computer processor coupled to the memory and configured to perform operations comprising:
receiving a first information listing;
receiving at least one predictive feature data of the first information listing from a data warehouse;
generating at least one recommendation for a second information listing by performing at least one machine-learning (ML) process based at least in part on at least one ML model and the at least one predictive feature data of the first information listing;
caching the at least one recommendation in an online cloud database;
transmitting a notification comprising the at least one recommendation;
redirecting, upon receiving an input indicating an interaction with the notification, to a web page displaying the at least one recommendation, wherein the displaying provides online access of the at least one recommendation from the online cloud database; and
subsequent to the redirecting, creating the second information listing.
16 . The system of claim 15 , wherein the at least one predictive feature data comprises a brand or a category.
17 . The system of claim 15 , wherein the second information listing is complementary to the first information listing based on the at least one recommendation.
18 . The system of claim 15 , wherein the at least one recommendation occurs in a predetermined amount of time.
19 . The system of claim 15 , wherein the at least one recommendation comprises outputs of the at least one ML model.
20 . The system of claim 19 , wherein the outputs of the at least one ML model comprise predictive features, wherein the predictive features comprise at least one of a lifetime value, a churn score, or communication.