IP Library Granted Patent US 11,315,145
Granted Patent B1
US 11,315,145 · App. 16/281,420 · Granted Apr 26, 2022

Systems and methods for increasing digital marketing campaign efficiency

Inventors: Daniel Knijnik (Old Greenwich, CT); Anibal Knijnik (Porto Alegre, BR); Eduardo Knijnik (Riverside, CT)
Assignee: Quartile Digital, Inc.
G06Q30/0249G06N20/00G06Q30/0201G06Q30/0202
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Quick Facts
Patent No.
US 11,315,145
App. No.
16/281,420
Granted
Apr 26, 2022
Kind
B1
Abstract

A method and associated system of managing advertising spending in an advertising campaign for an online marketplace seller, including, under control of one or more processors configured with executable instructions, defining a sales goal; setting a daily advertising budget and a bid value for an advertising campaign of the product; executing the advertising campaign; automatically collecting sales data relating to the product on the online marketplace; executing a machine learning component of an adaptive machine learning platform to generate a machine learning component output, at least in part based on the sales data; generating, based at least in part on the machine learning component output of the machine learning component, one or more sales milestones for the product on the online marketplace; comparing the sales data to the one or more sales milestones; and adjusting the daily advertising budget or the bid value to meet the sales goal.

Claims (39)

1. A method for improving the effectiveness of an adaptive machine learning platform in forecasting sales to determine whether a sales goal of an online marketplace seller is attainable, thereby discontinuing or modifying an advertising campaign generated by the online marketplace seller, the method performed by an application including one or more programs of instruction embodied in a non-transitory computer readable medium and executable by a processor to configure the application, comprising:

defining a sales goal relating to a number of sales of a product on an online marketplace;

setting a time period having a predetermined start and end;

executing one or more advertising campaigns on an online marketplace in connection with the product, wherein one or more bid values are associated with the one or more advertising campaigns;

generating an organic sales forecast of the product by executing a first machine learning component of the adaptive machine learning platform that is configured to generate the organic sales forecast via the input of organic sales data automatically retrieved from the online marketplace in connection with the product into the adaptive machine learning platform, the organic sales forecast being a forecast of total organic sales of the product before the end of the time period;

generating one or more sales milestones for the product by executing a second machine learning component of the adaptive machine learning platform that is configured to generate the one or more sales milestones via input of sales data automatically retrieved from the online marketplace in connection with the product into the adaptive machine learning platform, each of the one or more sales milestones designating a total sales threshold and a specific time within the time period, wherein a sales milestone is achieved when total sales of the product reach the total sales threshold at the specific time; and

determining automatically whether to discontinue one or more of the advertising campaigns or modify one or more of the advertising campaigns by decreasing the corresponding one or more bid values, while allowing the sales goal to be reached, the determination being based on at least one of the organic sales forecast or the sales milestones being achieved.

2. The method of claim 1 , wherein the sales goal is based at least in part on one or more inventory constraints.

3. The method of claim 1 , wherein the sales data is collected from one or more sales channels.

4. The method of claim 1 , wherein the sales data is repeatedly collected at a set time interval.

5. The method of claim 1 , wherein the advertising campaign is an automated advertising campaign or a keyword advertising campaign.

6. The method of claim 1 , further comprising modifying a sales price of the product on the online marketplace.

7. The method of claim 6 , further comprising:

executing a third machine learning component of an adaptive machine learning platform to generate a third machine learning component output, at least in part based on the sales data;

generating, based at least in part on the third machine learning component output of the third machine learning component, a sales price adjustment for the product; and

adjusting, based at least in part on the sales price adjustment and a status of the sales goal, the sales price of the product on the online marketplace.

8. The method of claim 1 , wherein the adaptive machine learning platform is additionally inputted with additional marketplace data automatically retrieved from the online marketplace in connection with the product to generate the organic sales forecast.

9. The method of claim 8 , wherein the additional marketplace data includes one or more of a marketplace ranking of the online marketplace seller for the product, a plurality of customer reviews of the online marketplace seller for the product, a rating of the online marketplace seller for the product based on the customer reviews, a number of total sales, a number of organic sales, a number of advertisement-generated sales, a conversion rate, a number of advertisement clicks relating to the advertising campaign, and a number of advertisement impressions relating to the advertising campaign.

10. A system for improving the effectiveness of an adaptive machine learning platform in forecasting sales to determine whether a sales goal of an online marketplace seller is attainable, thereby discontinuing or modifying an advertising campaign generated by the online marketplace seller, the system comprising:

one or more processors;

one or more computer-readable media; and

one or more modules maintained on the one or more computer-readable media that, when executed by the one or more processors, cause the one or more processors to perform operations including:

defining a sales goal relating to a number of sales of a product on an online marketplace;

setting a time period having a predetermined start and end;

executing one or more advertising campaigns on an online marketplace in connection with the product, wherein one or more bid values are associated with the one or more advertising campaigns;

generating an organic sales forecast of the product by executing a first machine learning component of an adaptive machine learning platform that is configured to generate the organic sales forecast via input of organic sales data automatically retrieved from the online marketplace in connection with the product into the adaptive machine learning platform, the organic sales forecast being a forecast of total organic sales of the product before the end of the time period;

generating one or more sales milestones for the product by executing a second machine learning component of the adaptive machine learning platform that is configured to generate the one or more sales milestones via input of sales data automatically retrieved from the online marketplace in connection with the product into the adaptive machine learning platform, each of the one or more sales milestones designating a total sales threshold and a specific time within the time period, wherein a sales milestone is achieved when total sales of the product reach the total sales threshold at the specific time; and

determining automatically whether to discontinue one or more of the advertising campaigns or modify one or more of the advertising campaigns by decreasing the corresponding one or more bid values, while allowing the sales goal to be reached, the determination being based on at least one of the organic sales forecast or the sales milestones being achieved.

11. The system of claim 10 , wherein the sales goal is based at least in part on one or more inventory constraints.

12. The system of claim 10 , wherein the sales data is collected from one or more sales channels.

13. The system of claim 10 , wherein the sales data is repeatedly collected at a set time interval.

14. The system of claim 10 , wherein the advertising campaign is an automated advertising campaign or a keyword advertising campaign.

15. The system of claim 10 , further comprising an additional operation of modifying a sales price of the product on the online marketplace.

16. The system of claim 15 , further comprising additional operations of:

executing a third machine learning component of an adaptive machine learning platform to generate a third machine learning component output, at least in part based on the sales data;

generating, based at least in part on the third machine learning component output of the third machine learning component, a sales price adjustment for the product; and

adjusting, based at least in part on the sales price adjustment and a status of the sales goal, the sales price of the product on the online marketplace.

17. The system of claim 10 , wherein the adaptive machine learning platform is additionally inputted with additional marketplace data automatically retrieved from the online marketplace in connection with the product to generate the organic sales forecast.

18. The system of claim 17 , wherein the additional marketplace data includes one or more of a marketplace ranking of the online marketplace seller for the product, a plurality of customer reviews of the online marketplace seller for the product, a rating of the online marketplace seller for the product based on the customer reviews, a number of total sales, a number of organic sales, a number of advertisement-generated sales, a conversion rate, a number of advertisement clicks relating to the advertising campaign, and a number of advertisement impressions relating to the advertising campaign.

Assignments (7)
SECURITY INTEREST Recorded Feb 3, 2025
From: PROSTEEL SECURITY PRODUCTS, INC.
To: CELTIC BANK CORPORATION
Reel/Frame 070085/0290 →
SECURITY INTEREST Recorded Nov 27, 2024
From: QUARTILE DIGITAL, INC.
To: CELTIC BANK CORPORATION
Reel/Frame 069422/0288 →
SECURITY INTEREST Recorded Sep 19, 2024
From: QUARTILE DIGITAL, INC.
To: CELTIC BANK CORPORATION
Reel/Frame 068637/0687 →
RELEASE OF SECURITY INTEREST Recorded Dec 28, 2023
From: WESTERN ALLIANCE BANK
To: QUARTILE DIGITAL, INC.
Reel/Frame 065974/0532 →
SECURITY INTEREST Recorded Sep 13, 2022
From: QUARTILE DIGITAL, INC.
To: WESTERN ALLIANCE BANK
Reel/Frame 061080/0012 →
CHANGE OF NAME Recorded Mar 1, 2021
From: HEADCLICKS, INC.
To: QUARTILE DIGITAL, INC.
Reel/Frame 055486/0697 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 10, 2019
From: KNIJNIK, DANIEL; KNIJNIK, EDUARDO; KNIJNIK, ANIBAL
To: HEADCLICKS, INC.
Reel/Frame 048842/0580 →
Continuity (1)
Provisional Application 62633449 · Feb 21, 2018
Cited By (3)
US 12,243,075 US 12,254,508 US 12,469,048