IP Library Granted Patent US 11,556,952
Granted Patent B2
US 11,556,952 · App. 16/874,815 · Granted Jan 17, 2023

Determining transaction-related user intentions using artificial intelligence techniques

Inventors: Ripunjay Sharma (Uttar Pradesh, IN); Partha Sarathi Nayak (Odisha, IN)
Assignee: Dell Products L.P.
G06Q30/0222G06N5/04G06N20/00G06Q30/0239G06Q30/0631
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Quick Facts
Patent No.
US 11,556,952
App. No.
16/874,815
Granted
Jan 17, 2023
Kind
B2
Abstract

Methods, apparatus, and processor-readable storage media for determining transaction-related user intentions using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining data pertaining to digital behavior of a user during a transaction-related session on one or more electronic commerce websites; classifying the user into one of multiple categories by processing the obtained data pertaining to the digital behavior of the user using artificial intelligence techniques, wherein the multiple categories correspond to multiple predicted levels of user intention to complete a transaction; determining, based on the classification of the user and the obtained data pertaining to the digital behavior of the user, at least one reason why the user may not complete a transaction during the transaction-related session; and performing one or more automated actions based at least in part on the at least one determined reason.

Claims (41)

1. A computer-implemented method comprising:

obtaining data pertaining to digital behavior of a user during a transaction-related session on one or more electronic commerce websites;

classifying the user into one of multiple categories by processing at least a portion of the obtained data pertaining to the digital behavior of the user using a supervised artificial intelligence classification model, wherein the multiple categories correspond to multiple predicted levels of user intention to complete a transaction;

determining, based at least in part on the classification of the user and the obtained data pertaining to the digital behavior of the user, at least one reason why the user may not complete a transaction during the transaction-related session on the one or more electronic commerce websites, wherein determining the at least one reason comprises ranking at least a portion of the obtained data pertaining to the digital behavior of the user in relation to one or more subject matter-related sections of the one or more electronic commerce websites, wherein the ranking is based at least in part on processing the at least a portion of the obtained data pertaining to the digital behavior of the user using at least one distance function; and

performing one or more automated actions based at least in part on the at least one determined reason, wherein performing one or more automated actions comprises:

automatically training the supervised artificial intelligence classification model using at least a portion of the at least one determined reason and at least one logistic regression algorithm in connection with at least one scaler and at least one classifier implemented as variables; and

generating and outputting to the user, during the transaction-related session and using at least one chatbot comprising at least one automated conversation exchange processing program integrated with at least a portion of the one or more electronic commerce websites, one or more product recommendations related to the one or more electronic commerce websites, wherein generating and outputting the one or more product recommendations to the user comprises generating and outputting, in approximately real-time during the transaction-related session, the one or more product recommendations using the at least one chatbot integrated with at least a portion of the one or more electronic commerce websites;

wherein the method is performed by at least one processing device comprising a processor coupled to a memory.

2. The computer-implemented method of claim 1 , wherein performing the one or more automated actions comprises generating and outputting to the user, during the transaction-related session, one or more transaction-related offers customized for the user.

3. The computer-implemented method of claim 2 , wherein outputting to the user the one or more transaction-related offers customized for the user comprises outputting, during the transaction-related session, the one or more transaction-related offers to the at least one chatbot integrated with at least a portion of the one or more electronic commerce web sites.

4. The computer-implemented method of claim 1 , wherein performing the one or more automated actions is further based at least in part on one or more user preferences determined from the user's purchase history.

5. The computer-implemented method of claim 1 , wherein the data pertaining to digital behavior of the user comprise data pertaining to pointer hover activity on the one or more electronic commerce websites.

6. The computer-implemented method of claim 1 , wherein the data pertaining to digital behavior of the user comprise data pertaining to click activity on the one or more electronic commerce websites.

7. The computer-implemented method of claim 1 , wherein generating and outputting the one or more product recommendations using the at least one chatbot integrated with at least a portion of the one or more electronic commerce websites comprises outputting the one or more product recommendations at least one of visually as text data and visually as image data via at least one interface associated with the one or more electronic commerce websites.

8. A non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device:

to obtain data pertaining to digital behavior of a user during a transaction-related session on one or more electronic commerce websites;

to classify the user into one of multiple categories by processing at least a portion of the obtained data pertaining to the digital behavior of the user using a supervised artificial intelligence classification model, wherein the multiple categories correspond to multiple predicted levels of user intention to complete a transaction;

to determine, based at least in part on the classification of the user and the obtained data pertaining to the digital behavior of the user, at least one reason why the user may not complete a transaction during the transaction-related session on the one or more electronic commerce websites, wherein determining the at least one reason comprises ranking at least a portion of the obtained data pertaining to the digital behavior of the user in relation to one or more subject matter-related sections of the one or more electronic commerce websites, wherein the ranking is based at least in part on processing the at least a portion of the obtained data pertaining to the digital behavior of the user using at least one distance function; and

to perform one or more automated actions based at least in part on the at least one determined reason, wherein performing one or more automated actions comprises:

automatically training the supervised artificial intelligence classification model using at least a portion of the at least one determined reason and at least one logistic regression algorithm in connection with at least one scaler and at least one classifier implemented as variables; and

generating and outputting to the user, during the transaction-related session and using at least one chatbot comprising at least one automated conversation exchange processing program integrated with at least a portion of the one or more electronic commerce websites, one or more product recommendations related to the one or more electronic commerce websites, wherein generating and outputting the one or more product recommendations to the user comprises generating and outputting, in approximately real-time during the transaction-related session, the one or more product recommendations using the at least one chatbot integrated with at least a portion of the one or more electronic commerce websites.

9. The non-transitory processor-readable storage medium of claim 8 , wherein performing the one or more automated actions comprises generating and outputting to the user, during the transaction-related session, one or more transaction-related offers customized for the user.

10. The non-transitory processor-readable storage medium of claim 9 , wherein outputting to the user the one or more transaction-related offers customized for the user comprises outputting, during the transaction-related session, the one or more transaction-related offers to the at least one chatbot integrated with at least a portion of the one or more electronic commerce web sites.

11. The non-transitory processor-readable storage medium of claim 8 , wherein the data pertaining to digital behavior of the user comprise data pertaining to pointer hover activity on the one or more electronic commerce websites.

12. The non-transitory processor-readable storage medium of claim 8 , wherein performing the one or more automated actions is further based at least in part on one or more user preferences determined from the user's purchase history.

13. The non-transitory processor-readable storage medium of claim 8 , wherein generating and outputting the one or more product recommendations using the at least one chatbot integrated with at least a portion of the one or more electronic commerce websites comprises outputting the one or more product recommendations at least one of visually as text data and visually as image data via at least one interface associated with the one or more electronic commerce websites.

14. An apparatus comprising:

at least one processing device comprising a processor coupled to a memory;

the at least one processing device being configured:

to obtain data pertaining to digital behavior of a user during a transaction-related session on one or more electronic commerce websites;

to classify the user into one of multiple categories by processing at least a portion of the obtained data pertaining to the digital behavior of the user using a supervised artificial intelligence classification model, wherein the multiple categories correspond to multiple predicted levels of user intention to complete a transaction;

to determine, based at least in part on the classification of the user and the obtained data pertaining to the digital behavior of the user, at least one reason why the user may not complete a transaction during the transaction-related session on the one or more electronic commerce websites, wherein determining the at least one reason comprises ranking at least a portion of the obtained data pertaining to the digital behavior of the user in relation to one or more subject matter-related sections of the one or more electronic commerce websites, wherein the ranking is based at least in part on processing the at least a portion of the obtained data pertaining to the digital behavior of the user using at least one distance function; and

to perform one or more automated actions based at least in part on the at least one determined reason, wherein performing one or more automated actions comprises:

automatically training the supervised artificial intelligence classification model using at least a portion of the at least one determined reason and at least one logistic regression algorithm in connection with at least one scaler and at least one classifier implemented as variables; and

generating and outputting to the user, during the transaction-related session and using at least one chatbot comprising at least one automated conversation exchange processing program integrated with at least a portion of the one or more electronic commerce websites, one or more product recommendations related to the one or more electronic commerce websites, wherein generating and outputting the one or more product recommendations to the user comprises generating and outputting, in approximately real-time during the transaction-related session, the one or more product recommendations using the at least one chatbot integrated with at least a portion of the one or more electronic commerce web sites.

15. The apparatus of claim 14 , wherein performing the one or more automated actions comprises generating and outputting to the user, during the transaction-related session, one or more transaction-related offers customized for the user.

16. The apparatus of claim 15 , wherein outputting to the user the one or more transaction-related offers customized for the user comprises outputting, during the transaction-related session, the one or more transaction-related offers to the at least one chatbot integrated with at least a portion of the one or more electronic commerce websites.

17. The apparatus of claim 14 , wherein the data pertaining to digital behavior of the user comprise data pertaining to pointer hover activity on the one or more electronic commerce websites.

18. The apparatus of claim 14 , wherein the data pertaining to digital behavior of the user comprise data pertaining to click activity on the one or more electronic commerce websites.

19. The apparatus of claim 14 , wherein performing the one or more automated actions is further based at least in part on one or more user preferences determined from the user's purchase history.

20. The apparatus of claim 14 , wherein generating and outputting the one or more product recommendations using the at least one chatbot integrated with at least a portion of the one or more electronic commerce websites comprises outputting the one or more product recommendations at least one of visually as text data and visually as image data via at least one interface associated with the one or more electronic commerce websites.

Assignments (9)
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053574/0221) Recorded Jun 10, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 060333/0001 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053578/0183) Recorded Jun 10, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 060332/0864 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053573/0535) Recorded Jun 10, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 060333/0106 →
RELEASE OF SECURITY INTEREST AT REEL 053531 FRAME 0108 Recorded Nov 2, 2021
From: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 058001/0371 →
SECURITY INTEREST Recorded Aug 21, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
Reel/Frame 053578/0183 →
SECURITY INTEREST Recorded Aug 21, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
Reel/Frame 053573/0535 →
SECURITY INTEREST Recorded Aug 21, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
Reel/Frame 053574/0221 →
SECURITY AGREEMENT Recorded Aug 18, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
To: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
Reel/Frame 053531/0108 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 15, 2020
From: SHARMA, RIPUNJAY; NAYAK, PARTHA SARATHI
To: DELL PRODUCTS L.P.
Reel/Frame 052670/0461 →
Cited By (1)
US 12,645,838