DETAILED ACTION
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 .
Acknowledgments
Claims 11-20 are non-elected.
Claims 1-10 and 21-43 are pending.
Applicant filed information disclosure statement 10/7/2025.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 9/26/2025 has been entered.
Response to Arguments
35 USC 101
Applicant's arguments filed 9/26/2025 have been fully considered but they are not persuasive. Examiner maintains 35 USC 101 rejection.
Applicant argues on page 18 that the claims do not fall in the certain methods of organizing human activity abstract idea grouping.
Examiner respectfully disagrees.
The claims state CRM which is customer relationship management and the claims are trying to optimize this management as seen in the claims. This clearly puts the claims in the abstract idea grouping of certain methods of organizing human activity (advertising, marketing or sales activities or behaviors; business relations, interactions between people).
Applicant argues on page 19
For example, the claims clearly recites steps that cannot be practically performed in the human mind, such as using a communication network, orchestrating machine learning models, applying machine learning models to predict probabilities, transmitting features to a remote system, or generating a graphical user interface.
Examiner respectfully disagrees.
The additional elements of communication network, machine learning models, remote system, and GUI are merely tools to implement the abstract idea of a mental process and certain methods of organizing human activity. Limitations that are not indicative of integration into a practical application include: Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). In addition, additional elements are not part of the Step 2A prong 1 analysis which the Applicant is using here to justify patentability.
Applicant argues on page 19
The claims as amended also recite a practical application. According to the Federal Circuit, "[s]oftware can make non-abstract improvements to computer technology just as hardware improvements can, and sometimes the improvements can be accomplished through either route." Enfish v. Microsoft, 822 F.3d 1327, 1335 (Fed. Cir. 2016). In the instant case, the recited elements improve computer technology by, inter alia, improving CRM data analysis and optimization.
Examiner respectfully disagrees
The claims are not addressing a technical problem nor do they provide a technical solution. The claims are solving the business problem of increasing revenue, maximizing profits, increasing customer satisfaction, increasing customer retention, increasing market share, and increasing sales and service effectiveness within an organization (See para 0003 in Specification). In addition, improving data analysis and optimization are merely improvements nested in the abstract idea of a mental process that includes determining/analyzing. A technical problem and technical solution is seen in the court case of McRO. The patents in McRO were an improvement on 3-D animation wherein the prior art comprised that "for each keyframe, the artist would look at the screen and, relying on her judgment, manipulate the character model until it looked right — a visual and subjective process." Thus, the patents in McRO aimed to automate a 3-D animator's tasks, specifically, determining when to set keyframes and setting those keyframes.
35 USC 103
Applicant’s arguments, filed 2/25/2025, with respect to 35 USC 103 have been fully considered and are persuasive. Examiner withdraws 35 USC 103 rejection.
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 1-10 and 21-43 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more than the judicial exception itself.
Regarding Step 1 of subject matter eligibility for whether the claims fall within a statutory category (See MPEP 2106.03), claims 1-10 and 21-43 are directed to the statutory category of a method, apparatus, and non-transitory computer readable medium.
Regarding step 2A-1, Claims 1-10 and 21-43 recite a Judicial Exception. Exemplary independent claim 1 and similarly claims 21 and 31 recite the limitations of
Obtain… CRM data … selecting…application from a group of…applications, wherein each…application is configured to generate one or more use case insights with one or more objectives; obtaining one or more data models including an industry-specific data model from the CRM data; orchestrate…a plurality of…models… to determine one or more…models effective for at least one of the one or more objectives… inferencing using the data…models and the one or more obtained data models to predict probabilities that optimize the at least one of the one or more objectives…transmitting… the predicted probabilities to apply at least one of the one or more use case insights that optimizes the at least one of the one or more objectives…
Generating…evidence package by determining at least one current value of at least one contribution by one or more features associated with the one or more determined machine learning models to at least one of the predicted probabilities; generating…and displaying…(i) the at least one of the one or more use case insights that optimizes the at least one of the one or more objectives of the selected Al CRM application and (ii) the at least one current value of the at least one contribution by the one or more features associated with the one or more determined machine learning models to the at least one of the predicted probabilities.
These limitations, as drafted, are a process that, under its broadest reasonable interpretation cover concepts of obtaining, inferencing, selecting, determining, transmitting, generating, applying, predicting, and displaying data. The claim limitations fall under the abstract idea grouping of mental process, because the limitations can be performed in the human mind, or by a human using a pen and paper. For example, but for the language of processor and memory, the claims language encompasses simply obtaining CRM data, selecting data, orchestrate models, determining which model is effective, predicting probabilities with respect to inferencing data, transmitting data and applying a case insight with respect to the predicted probabilities. The claims further state generating an evidence package and GUI and displaying information. These are mere data manipulation steps that do not require a computer. Optimizing business objectives is not novel and has been done before the technological age. Given a real-world example, these steps can easily be done by a manager in charge of optimizing a business.
In addition, the claims recite customer relationship management. The Applicant’s specification also includes sales, marketing, and customer satisfaction (See para 0003 in Applicant’s Specification). These make the claims fall in the abstract idea grouping of certain methods of organizing human activity (advertising, marketing or sales activities or behaviors; business relations, interactions between people). It is clear the limitations recite these abstract idea groupings, but for the recitations of generic computer components. The mere nominal recitations of generic computer components does not take the limitations out of the mental process and certain methods of organizing human activity grouping. The claims are focused on the combination of these abstract idea processes.
Regarding step 2A-2- This judicial exception is not integrated into a practical application, and the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The claim recites the additional elements of network, server, database server, remote system, GUI, AI CRM application, machine learning models, trained machine learning model, user interface, machine learning classifiers, remote distributed systems, electronic communication, social media post, chatbot, website, mobile device, remote data store or display, website, dynamic graphical reporting interface, processing device, apparatus, non-transitory computer readable medium, and processors. These components are recited at a high level of generality, and merely automate the steps. Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer component.
The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer components or software. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim limitations are merely automating a manual process of optimizing business objectives. Examples that the courts have indicated may not be sufficient to show an improvement in computer-functionality: iii. Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential).
Further, the claims do not provide for or recite any improvements to the functioning of a computer, or to any other technology or technical field; applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition; applying the judicial exception with, or by use of, a particular machine; effecting a transformation or reduction of a particular article to a different state or thing; or applying or using 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 have the same deficiencies as their parent claims as being directed towards an abstract idea, as the dependent claims merely narrow the scope of their parent claims. For example, the dependent claims further describe what the applications are. In addition, the dependent claims further describe what the case insights are.
Regarding step 2B the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because claim 1 recites
method, however method is not considered an additional element
claim 1 further recites communication network, server, database server, remote system, GUI, AI CRM application, machine learning models
Claims 2, 22, and 32 recite machine learning classifiers and type system
Claims 8, 28, and 38 recite trained machine learning model
Claims 7, 27, and 37 recite remote distributed systems,
Claims 9, 29, and 39 recite electronic communication, social media post, chatbot, website, mobile device, remote data store or display, website, dynamic graphical reporting interface,
Claim 21 further recites processing device, apparatus, communication network, server, database server, remote system, AI CRM application, machine learning models, GUI
Claim 31 recites non-transitory computer readable medium and processors, communication network, server, database server, remote system, AI CRM application, machine learning models, GUI
Claims 10, 30, 40 recite a type system
When looking at these additional elements individually, the additional elements are purely functional and generic, the Applicant specification states general purpose computer configurations as seen in para 0095 and 00108.
When looking at the additional elements in combination, the computer components add nothing that is not already present when the steps are considered separately. See MPEP 2106.05
Looking at these limitations as an ordered combination and individually adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use generic computer components, recitations of generic computer structure to perform generic computer functions that are used to "apply" the recited abstract idea. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claims as a whole amounts to significantly more than the abstract idea itself. Since there are no limitations in these claims that transform the exception into a patent eligible application such that these claims amount to significantly more than the exception itself, claims 1-10 and 21-43 are rejected under 35 U.S.C. 101.
Conclusion
The prior art made of record and not relied upon considered pertinent to Applicant’s disclosure.
Erhart (US 20110276513) Discloses methods and systems that provide an enterprise with the ability to conduct automated customer feedback surveys. In particular, customer interactions on social media channels are intelligently monitored, aggregated, filtered, and analyzed to determine a customer's response to a particular product or service.
Copeland (US20220350963A1) Discloses call preparation engine for customer relationship management (“CRM”)
Mandersceid (US20220383329A1) Discloses a computer-implemented method of predicting customer satisfaction scores for a call center is disclosed, along with the use of the predicted customer satisfaction scores to perform various analytical functions, such as identifying changes to the predicted customer satisfaction score and identifying root causes of the predicted customer satisfaction scores.
Rich (20220327226) Discloses a method by one or more computing devices implementing a data insights sharing service to allow a first user of the data insights sharing service to share data insights with other users of the data insights sharing service.
Orun (20220300988) Discloses methods, computer readable media, and devices for leveraging individual engagement history in account-based marketing personalization are provided.
Jackson (US 20110093441 A1) Discloses a method for detecting a delinquent or dormant customer record in a customer relationship management (CRM) database using a computer arrangement. The method includes the step of determining that the customer record does not relate to an existing customer for whom work is in progress. It is also determined that the customer record does not relate to a prospective customer. The method further includes the step of detecting the customer record when a future activity date associated with the customer record has passed.
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/MUSTAFA IQBAL/Primary Examiner, Art Unit 3625