Prosecution Insights
Last updated: April 19, 2026
Application No. 18/615,769

SYSTEMS AND METHODS FOR IDENTIFYING ITEM SUBSTITUTIONS

Non-Final OA §101§102
Filed
Mar 25, 2024
Examiner
ZIMMERMAN, MATTHEW E
Art Unit
3688
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
The Boston Consulting Group Inc.
OA Round
1 (Non-Final)
52%
Grant Probability
Moderate
1-2
OA Rounds
3y 9m
To Grant
98%
With Interview

Examiner Intelligence

Grants 52% of resolved cases
52%
Career Allow Rate
291 granted / 563 resolved
At TC average
Strong +46% interview lift
Without
With
+45.9%
Interview Lift
resolved cases with interview
Typical timeline
3y 9m
Avg Prosecution
22 currently pending
Career history
585
Total Applications
across all art units

Statute-Specific Performance

§101
30.1%
-9.9% vs TC avg
§103
29.3%
-10.7% vs TC avg
§102
17.4%
-22.6% vs TC avg
§112
16.1%
-23.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 563 resolved cases

Office Action

§101 §102
Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . DETAILED ACTION Status of Claims Claim(s) 1-4 have been examined. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-4 are rejected under 35 U.S.C. 101 because the claims recite a judicial exception which is not integrated into a practical application and the claims lack an inventive concept. Step 1 is the first inquiry into eligibility analysis and asks whether the claims are directed to a statutory category. In this instance, the answer must be in the affirmative because they recite a method and system. Step 2A prong 1 is the next step in the eligibility analyses and asks whether the claimed invention recites a judicial exception. In this instance, the claims recite the following limitations which comprise the abstract idea: collecting history information, wherein the history information comprises one or more episodes from one or more customers, wherein each episode comprises one or more items and timing information, wherein a subset of the one or more episodes comprises a label identifying a mission; determining, the label identifying the mission for each of the one or more episodes for a customer of the one or more customers; determining a pattern for the label of each of the one or more episodes for the customer based on the timing information; predicting a future episode for the customer based on the pattern; This is an abstract idea because it is a certain method of organizing human activity because it involves commercial interactions such as sales and/or marketing behaviors and/or activities. Step 2A prong 2 is the next step in the eligibility analyses and looks at whether the abstract idea is integrated into a practical application. This requires an additional element or combination of additional elements in the claims to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. In this instance, the claims recite the additional elements such as: training a natural language processor on subset of the one or more episodes to generate the label for each episode based on the one or more items; using a natural language processor However, these elements do not amount to an improvement in the functioning of a computer or any other technology or technical field, apply the judicial exception with, or by use of, a particular machine, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. In addition, the recitations of the additional limitations are recited at a high level of generality and also do not amount to an improvement in the functioning of a computer or any other technology or technical field, apply the judicial exception with, or by use of, a particular machine, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. The dependent claims also fail to recite elements which amount to an improvement in the functioning of a computer or any other technology or technical field, apply the judicial exception with, or by use of, a particular machine, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. For example, claim 2 is directed at the abstract idea. In addition, even if the dependent claims were not, they do not amount to an integration according to any one of the considerations above. Step 2B is the next step in the eligibility analyses and evaluates whether the claims recite additional elements that amount to an inventive concept (i.e., “significantly more”) than the recited judicial exception. According to Office procedure, revised Step 2A overlaps with Step 2B, and thus, many of the considerations need not be re-evaluated in Step 2B because the answer will be the same. In Step 2A, several additional elements were identified as additional limitations: training a natural language processor on subset of the one or more episodes to generate the label for each episode based on the one or more items; using a natural language processor These additional limitations, including the limitations in the dependent claims, do not amount to an inventive concept because they are recited at a high level of generality and also do not amount to an improvement in the functioning of a computer or any other technology or technical field, apply the judicial exception with, or by use of, a particular machine, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. In addition, they were already analyzed under Step 2A and did not amount to a practical application of the abstract idea. Therefore, the claims lack one or more limitations which amount to an inventive concept in the claims. For these reasons, the claims are rejected under 35 U.S.C. 101. Claim Rejections - 35 USC § 102 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claim(s) 1-4 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Tavernier (US 10,706,450). Referring to Claim 1, Tavernier teaches a computer-implemented method comprising: collecting history information, wherein the history information comprises one or more episodes from one or more customers, wherein each episode comprises one or more items and timing information (see Tavernier Col. 16 line 48 to Col. 17 line 15), wherein a subset of the one or more episodes comprises a label identifying a mission (see Tavernier Col. 1 lines 61-67, auto labeling a search query of a user to define a shopping “mission”); training a natural language processor on subset of the one or more episodes to generate the label for each episode based on the one or more items (see Tavernier Col. 2 lines 42-48); determining, using the natural language processor, the label identifying the mission for each of the one or more episodes for a customer of the one or more customers (see Tavernier Col. 1 lines 60-67); determining a pattern for the label of each of the one or more episodes for the customer based on the timing information (see Tavernier Col. 6 lines 2-11 and Col. 8 lines 32-41); predicting a future episode for the customer based on the pattern (see Tavernier Col. 5 lines 34-45). Referring to Claim 2, Tavernier teaches the computer-implemented method of claim 1, further comprising generating a personalized marketing message for the customer based on the predicted future episode (see Tavernier Col. 5 lines 34-45). Referring to Claim 3, Tavernier teaches a system comprising: a non-transitory memory storing instructions and a processor for executing the instructions, the processor configured for: collecting history information, wherein the history information comprises one or more episodes from one or more customers, wherein each episode comprises one or more items and timing information (see Tavernier Col. 16 line 48 to Col. 17 line 15), wherein a subset of the one or more episodes comprises a label identifying a mission (see Tavernier Col. 1 lines 61-67, auto labeling a search query of a user to define a shopping “mission”); training a natural language processor on subset of the one or more episodes to generate the label for each episode based on the one or more items (see Tavernier Col. 2 lines 42-48); determining, using the natural language processor, the label identifying the mission for each of the one or more episodes for a customer of the one or more customers (see Tavernier Col. 1 lines 60-67); determining a pattern for the label of each of the one or more episodes for the customer based on the timing information (see Tavernier Col. 6 lines 2-11 and Col. 8 lines 32-41); predicting a future episode for the customer based on the pattern (see Tavernier Col. 5 lines 34-45). Referring to Claim 4, Tavernier teaches the system of claim 3, wherein the processor is further configured for generating a personalized marketing message for the customer based on the predicted future episode (see Tavernier Col. 5 lines 34-45). Remarks Additional prior art relevant to the application claims but not relied upon includes: KARMAKAR (US 2020/0043022) teaches AI for generating hierarchical data structures. YOON (US 2019/0179915) teaches recommending items using metadata. Reference U (see PTO-892) teaches shopping missions. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW E ZIMMERMAN whose telephone number is (571)270-5278. The examiner can normally be reached 8-4pm M-T, 8-12pm W. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jeff Smith can be reached at (571)272-6763. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /MATTHEW E ZIMMERMAN/Primary Examiner, Art Unit 3688
Read full office action

Prosecution Timeline

Mar 25, 2024
Application Filed
Dec 27, 2025
Non-Final Rejection — §101, §102
Mar 17, 2026
Examiner Interview Summary
Mar 17, 2026
Applicant Interview (Telephonic)

Precedent Cases

Applications granted by this same examiner with similar technology

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
52%
Grant Probability
98%
With Interview (+45.9%)
3y 9m
Median Time to Grant
Low
PTA Risk
Based on 563 resolved cases by this examiner. Grant probability derived from career allow rate.

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