DETAILED ACTION
Acknowledgement
This final office action is in response to the amendment filed on 06/22/2026.
Status of Claims
Claims 3, 9, and 15 have been cancelled.
Claims 1, 7, and 13 have been amended.
Claims 1, 2, 4-8, 10-14, and 16-18 are now pending.
Response to Arguments
Applicant's arguments filed on 06/22/2026 regarding the 35 U.S.C. 101 and 103 rejections of the pending claims have been fully considered. The Applicant argues the following.
(1) As per the 101 rejection, the Applicant argues, in summary, that (i) amended claims are not directed to organizing human activity and mental processes, (ii) the amended claims solve a technical problem of optimizing product revenue, and (iii) the claims integrate the judicial exception into a practical application by improving computer technology by providing the user with a semi-automated solution for guided decision-making.
The Examiner respectfully disagrees with all arguments. The Examiner maintains the position that the claims are directed to the abstract groups of Mental Processes and Certain Methods of Organizing Human Activity because the claims describe a process of analyzing product data, sales data, and product mix scenarios in order to predict a best-selling product mix and estimate a target value, which can practically be performed in the mind with pen and paper using mathematical calculations. These steps also mirror activities that a marketing professional or product planner would perform, thus reflecting certain methods of organizing human activity (e.g. marketing or sales activities or behaviors). Per the October 2019 Patent Subject Matter Eligibility Guidance and MPEP 2106.04(a), a claim recites a judicial exception when the judicial exception is “set forth” or “described” in the claim.
The Examiner also maintains the position that the additional elements recited in the amended claims and listed in Steps 2A(2) and 2B do not integrate the abstract idea into a practical application nor provide significantly more because the additional elements do not improve the functioning of a computer or another technology and do not provide a technical solution to a technical problem. The additional elements reflect the use of computer technology to perform an abstract process and the mere automation of a once manual process. MPEP 2106.05(a)(I) states that “mere automation of manual processes or increasing the speed of a process where these purported improvements come solely from the capabilities of a general-purpose computer are not sufficient to show an improvement in computer-functionality”. Computer technology is not improved beyond its original functions and capabilities with the implementation of the Applicant’s invention. The Examiner also submits that optimizing product revenue is not a technical problem and does not require a computer or technology to perform and/or address. The claims reflect an improvement in the abstract idea (e.g. analysis, prediction, product revenue, decision making, etc.), which is not an improvement in technology (MPEP 2106.05(a)(II)). Applying an abstract idea on a computer does not integrate a judicial exception into a practical application or provide an inventive concept (see MPEP 2106.05(f)). Therefore, the 35 U.S.C. 101 rejection is maintained.
(2) As per the 103 rejection, the Applicant argues that none of the prior arts Ettl, Anderson, and Li disclose the amended features of claim 1.
The Examiner finds the Applicant’s arguments persuasive. Therefore, the 103 rejection has been withdrawn.
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 .
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 therefore, subject to the conditions and requirements of this title.
Claims 1-2, 4-8, 10-14, and 16-18 are rejected under 35 U.S.C. 101 because the claimed invention, “Systems and Methods for Optimizing Product Revenue”, is directed to an abstract idea, specifically Mental Processes and Certain Methods of Organizing Human Activity, without significantly more. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements individually or in combination provide mere instructions to implement the abstract idea on a computer.
Step 1: Claims 1-2, 4-8, 10-14, and 16-18 are directed to a statutory category, namely a process (claims 1-6), a machine (claims 7-12), and a manufacture (claims 13-18).
Step 2A (1): Independent claims 1, 7, and 13 are directed to an abstract idea of Mental Processes and Certain Methods of Organizing Human Activity, based on the following claim limitations: “receiving,…, a product family further comprising one or more of product models, from a user, wherein each product model amongst the one or more product models comprises a plurality of feature families, wherein each feature family amongst the plurality of feature families comprises a plurality of feature variants; generating,…, one or more configurations for each of the one or more product models, from (i) the plurality of feature variants, (ii) one or more supply constraints, and (iii) one or more usage policies, wherein each of the one or more configurations pertains to a unique bundle of the plurality of feature variants; extracting,…, a historical sales data pertaining to the one or more configurations of each of the one or more product models; predicting, by using one or more forecasting models…, a best-selling product configuration mix from the one or more configurations, across the one or more product models and a plurality of feature families based on the historical sales data, wherein the best-selling configuration mix comprises a plurality of product-feature variant bundles; creating,…, one or more scenarios for the best-selling product configuration mix,… further comprising of a plurality of options, wherein the plurality of options comprises a predefined scenario objective list including a max product revenue, one or more scenario dimensions, a predefined scenario dimensions list including a demand, a supply, usage and one or more scenario levels, wherein the step of creating the one or more scenarios comprises: selecting a scenario objective from a predefined scenario objective list; selecting one or more scenario dimensions from a predefined scenario dimensions list; selecting one or more scenario levels from a predefined scenario levels lit, wherein each of the one or more scenario dimensions comprises the one or more scenario levels; and creating the one or more scenarios based on one or more combinations of the one or more scenario levels: mapping each of product families to feature families that shared across all the product models and their product families, wherein the each of the product families is mapped into a set of feature variants and a product model is built by selecting exactly one feature variant from each of the feature families and enables systematic structure series of the one or more scenarios under constrained feature variant supply and usage; obtaining,…, one or more datasets pertaining to each of the one or more scenarios, the one or more datasets are created for each scenario configuration, using (i) the plurality of product-feature variant bundles of the best-selling product configuration mix, (ii) one or more supply constraints, and (iii) the one or more usage policies, and wherein the one or more datasets created for each scenario comprises one or more lane-costs, the one or more supply constraints, and the one or more usage policies; optimizing, by using the one or more created datasets…, the one or more scenarios selected based on a selected business scenario type by using an objective function, and generating a plurality of optimization values, wherein the plurality of optimization values comprises an optimal value, a range of optimality, and a shadow price, for the selected business scenario type; estimating,…, a final target value for the one or more product models based on a first set of inputs and a second set of inputs, wherein the first set of inputs comprise a historic target value pertaining to the one or more scenarios of the plurality of product models, and wherein the second set of inputs comprises at least one of a price, and an interest rate associated with one or more products; and selecting,…, at least one scenario amongst the one or more scenarios as a focal scenario, based on a comparison between an associated scenario objective value and the final target value, wherein process of selecting is repeated iteratively, till the total revenue deviation from target is within tolerance, wherein the difference between the associated scenario objective value and the final target value is exceeding a predefined tolerance, one or more deviations identified by comparing one or more selected plurality of options, and one or more constraints of the focal scenario with the plurality of options, and the constraints of a base scenario, and the one or more constraints of the focal scenario are iteratively modified, to improve the associated scenario objective value, till the one or more deviations of the associated scenario objective value in comparison to the estimated final target value is within the predefined tolerance.”. These claim limitations describes a process of analyzing product data, sales data, and product mix scenarios in order to predict a best-selling product mix and estimate a target value, which can practically be performed in the human mind with pen and paper using mathematical calculations. The claim limitations also reflect marketing and sales activities and behaviors. Dependent claims 2, 4-6, 8, 10-12, 14, and 16-18 further describe the product mix features, lane costs, scenario objectives, and scenario analysis to estimate a target value. Therefore, these limitations, under the broadest reasonable interpretation, fall within the abstract groupings of Mental Processes which include concepts performed in the human mind such as observations, evaluations, judgments, and opinions and Certain Methods of Organizing Human Activity which encompasses commercial interactions including subject matter relating to marketing or sales activities or behaviors, and business relations. Mental Processes include claims directed to collecting information, analyzing it, and displaying certain results of the collection and analysis even if they are claimed as being performed on a computer. Certain Methods of Organizing Human Activity can encompass the activity of a single person (e.g. a person following a set of instructions), activity that involve multiple people (e.g. a commercial interaction), and certain activity between a person and a computer (e.g. a method of anonymous loan shopping). Therefore, claims 1-2, 4-8, 10-14, and 16-18 as a whole are directed to an abstract idea and are not patent eligible.
Step 2A (2): The claims as a whole do not integrate this abstract idea into a practical application. In particular, claims 1, 7, and 13 recite additional elements of “a processor implemented method (claim 1); …via the one or more hardware processors; a configurator interface, …by using an autoregressive neural network model via the one or more hardware processors, wherein the autoregressive neural network model includes 3 layers and an input layer consist of 8 nodes, two of which are a value of the target variable from the past two periods and the other six nodes are external inputs for the current and past two periods, wherein a hidden layer include 3 nodes and an output layer using a rectified linear activation function; (claims 1, 7, and 13); a system, comprising: a memory storing instructions; one or more communication interfaces; and one or more hardware processors coupled to the memory via the one or more communication interfaces, wherein the one or more hardware processors are configured by the instructions to (claim 7); and one or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause (claim 13)”. The Examiner evaluated the claims in light of the Applicant’s specification and determined that the additional elements do not integrate the abstract idea into a practical application because the claims do not recite (a) an improvement to another technology or technical field and (b) an improvement to the functioning of the computer itself and (c) implementing the abstract idea with or by use of a particular machine, (d) effecting a particular transformation or reduction of an article, or (e) applying the judicial exception in some other meaningful way beyond generally linking the use of an abstract idea to a particular technological environment. These additional elements evaluated individually and in combination are viewed as computing and display devices that are used to perform the abstract process identified in Step 2A(1). Limitations that recite mere instructions to implement an abstract idea on a computer or merely uses a computer as a tool to perform an abstract idea are not indicative of integration into a practical application (see MPEP 2106.05(f)). Therefore, claims 1-2, 4-8, 10-14, and 16-18 as a whole do not include individual or a combination of additional elements that integrate the abstract idea into a practical application and thus are not patent eligible.
Step 2B: The claims as a whole do not include additional elements that are sufficient to amount to significantly more than the abstract idea. Claims 1, 7, and 13 recite additional elements of “a processor implemented method (claim 1); …via the one or more hardware processors; a configurator interface, …by using an autoregressive neural network model via the one or more hardware processors, wherein the autoregressive neural network model includes 3 layers and an input layer consist of 8 nodes, two of which are a value of the target variable from the past two periods and the other six nodes are external inputs for the current and past two periods, wherein a hidden layer include 3 nodes and an output layer using a rectified linear activation function (claims 1, 7, and 13); a system, comprising: a memory storing instructions; one or more communication interfaces; and one or more hardware processors coupled to the memory via the one or more communication interfaces, wherein the one or more hardware processors are configured by the instructions to (claim 7); and one or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause (claim 13)”. These additional elements evaluated individually and in combination are viewed as mere instructions to apply or implement the abstract idea on a computer. Applying an abstract idea on a computer does not integrate a judicial exception into a practical application or provide an inventive concept (see MPEP 2106.05(f)). Therefore, claims 1-2, 4-8, 10-14, and 16-18 as a whole do not include individual or a combination of additional elements that are sufficient to amount to significantly more than the abstract idea and thus are not patent eligible.
Conclusion
Claims 1-2, 4-8, 10-14, and 16-18 overcome the following prior art(s) made of record of Ettl et al. (US 2009/0164262 A1), Anderson (US 2022/0012756 A1), and Li et al. (US 2022/0261828 A1). The closest prior art(s) to the claimed invention include Gee et al. (US 2022/0194400 A1). However, none of the prior art(s) alone or in combination teach the claimed invention as detailed in independent claims 1, 7, and 13.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ayanna Minor whose telephone number is (571)272-3605. The examiner can normally be reached M-F 9am-5 pm.
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, Jerry O'Connor can be reached at 571-272-6787. 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.
/A.M./Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624
Prosecution Insights