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
1. This Office Action is in response to the Amendment filed on January 8, 2026, which paper has been placed of record in the file.
2. Claims 1-14, 16, 18-19, and 22-24 are pending in this application.
Claim Rejections - 35 USC § 101
3. 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.
4. Claims 1-14, 16, 18-19, and 22-24 are rejected under 35 U.S.C. 101 because the claim invention is directed to a judicial exception (i.e., law of nature, natural phenomenon, or abstract idea) without significantly more.
Regarding independent claim 1, which is analyzing as the following:
Step 1: This part of the eligibility analysis evaluates whether the claim falls within any statutory category. See MPEP 2106.03. The claim recites a system for providing marketing management, planning, creation and execution capabilities to businesses. Thus, the claims are to a machine, which is one of the statutory categories of invention. (Step 1: YES).
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim.
The claim recites a system for providing marketing management, planning, creation and execution capabilities to businesses. The system receives marketing information from the target audience via user inputted answers to questionnaire, then analyzes to extract key concepts. The system then generates marketing action plan. The claim recites the steps: analyze the first-party data and extracting therefrom a plurality of key concepts; generate a dynamic user-specific and brand-specific data repository, and generate channel-specific of cross-channel marketing action plan and corresponding personalized marketing assets, and/or marketing strategy, under its broadest reasonable interpretation when read in light of the Specification, falls within “Certain Methods of Organizing Human Activity” grouping of abstract ideas as they cover performance of commercial or legal interactions including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, business relations.
Moreover, the claim recites analyze the first-party data and extracting therefrom a plurality of key concepts; generate a dynamic user-specific and brand-specific data repository, and generate channel-specific of cross-channel marketing action plan and corresponding personalized marketing assets, and/or marketing strategy, as drafted, is a process that, under its broadest reasonable interpretation when read in light of the Specification, covers performance of the limitations in the mind, can be practically performed by human in their mind or with pen/paper, but for the recitation of generic computer components. That is, other than reciting “a computer/processor/automatically”, nothing in the claim elements preclude the steps from practically being performed in the mind. The mere nominal recitation of generic computing devices does not take the claim limitation out of the Mental Processes grouping of abstract ideas. Thus, if a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas (concepts performed in the human mind including an observation, evaluation, judgment, opinion). See MPEP 2106.04(a)(2), subsection III.
Therefore, the claim recites an abstract idea. (Step 2A, Prong One: YES).
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
The claim recites the additional elements of “user interface configured to collect first-party data”, “autonomously retrieve, without requiring user prompts: insights, analytics and performance data from second-party media platforms; and third-party data from the Internet, and from at least one application program interface (API)”, “analyzing, using a natural language model, the first party data and extract therefrom”, and “apply one or more predictive and generative machine-learning or deep-leaning models, to generate without requiring user prompting a channel-specific or cross-channel marketing action plan.” The claim also recites that the steps of “analyze the first-party data and extracting therefrom a plurality of key concepts; generate a dynamic user-specific and brand-specific data repository, and generate channel-specific of cross-channel marketing action plan and corresponding personalized marketing assets, and/or marketing strategy” are performed by a processor.
The additional elements “user interface configured to collect first-party data”, “autonomously retrieve, without requiring user prompts: insights, analytics and performance data from second-party media platforms; and third-party data from the Internet, and from at least one application program interface (API)” are mere data gathering and transmitting recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (“whether the limitation is significant”). In addition, all uses of the recited judicial exceptions require such data gathering and outputting, and, as such, these limitations do not impose any meaningful limits on the claim. These limitations amount to necessary data gathering and outputting. See MPEP 2106.05. Moreover, these additional elements do not provide any improvement to the technology, improvement to the functioning of the computer, improvement to the user interface/Internet and/or application program interface (API), they are just merely used as general means for collecting and displaying data. It is similar to other concepts that have been identified by the courts Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48; Collecting information, analyzing it, and displaying certain results of the collection and analysis, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016).
The additional elements “analyzing, using a natural language model, the first party data and extract therefrom”, and “apply one or more predictive and generative machine-learning or deep-leaning models, to generate without requiring user prompting a channel-specific or cross-channel marketing action plan” provide nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception.
The additional element “analyzing, using a natural language model, the first party data and extract therefrom” is used to generally apply the abstract idea and invokes the computer merely as a tool to perform an existing process. See MPEP 2106.05(f).
The additional element “apply one or more predictive and generative machine-learning or deep-leaning models, to generate without requiring user prompting a channel-specific or cross-channel marketing action plan” is used to generally apply the abstract idea without placing any limits on how the machine learning functions. Rather, this limitation only recites the outcome of “generate a digital marketing action plan” and does not include any details about how the solution is accomplished. See MPEP 2106.05(f).
The additional element “apply one or more predictive and generative machine-learning or deep-leaning models, to generate without requiring user prompting a channel-specific or cross-channel marketing action plan” also merely indicates a field of use or technological environment in which the judicial exception is performed. Although the additional element “apply one or more predictive and generative machine-learning or deep-leaning models, to generate without requiring user prompting a channel-specific or cross-channel marketing action plan” limits the identified judicial exceptions “generate a channel-specific or cross-channel marketing action plan”, this type of limitation merely confines the use of the abstract idea to a particular technological environment (machine learning) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Further, the steps of “analyze the first-party data and extracting therefrom a plurality of key concepts; generate a dynamic user-specific and brand-specific data repository, and generate channel-specific of cross-channel marketing action plan and corresponding personalized marketing assets, and/or marketing strategy”, are recited as being performed by the processor. The processor is recited at a high level of generality and is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). The additional elements recite generic computer components the processor, a memory, and software programming instructions that are recited a high-level of generality that merely perform, conduct, carry out, implement, and/or narrow the abstract idea itself. Accordingly, the additional elements evaluated individually and in combination do not integrate the abstract idea into a practical application because they comprise or include limitations that are not indicative of integration into a practical application such as 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).
Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception (Step 2A, Prong One: YES).
Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole, amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
As explained with respect to Step 2A, Prong Two, the additional elements of “analyzing, using a natural language model, the first party data and extract therefrom”, and “apply one or more predictive and generative machine-learning or deep-leaning models, to generate without requiring user prompting a channel-specific or cross-channel marketing action plan” are at best mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept. See MPEP 2106.05(f).
The additional elements “user interface configured to collect first-party data”, “autonomously retrieve, without requiring user prompts: insights, analytics and performance data from second-party media platforms; and third-party data from the Internet, and from at least one application program interface (API)” were found to be insignificant extra-solution activity in Step 2A, Prong Two, because they were determined to be insignificant limitations as necessary data gathering and transmitting. However, a conclusion that an additional element is insignificant extra solution activity in Step 2A, Prong Two should be re-evaluated in Step 2B. See MPEP 2106.05, subsection I.A. At Step 2B, the evaluation of the insignificant extra-solution activity consideration takes into account whether or not the extra-solution activity is well understood, routine, and conventional in the field. See MPEP 2106.05(g).
As discussed in Step 2A, Prong Two above, the additional elements of “user interface configured to collect first-party data”, “autonomously retrieve, without requiring user prompts: insights, analytics and performance data from second-party media platforms; and third-party data from the Internet, and from at least one application program interface (API)” are recited at a high level of generality. These elements amount to gathering and transmitting data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II. The courts have recognized the following computer functions as well understood, routine, and conventional functions when they are claimed in a merely genetic manner (e.g., at a high level of generality) or as insignificant extra-solution activity: Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
As discussed in Step 2A, Prong Two above, the recitation of the processor to perform limitations “analyze the first-party data and extracting therefrom a plurality of key concepts; generate a dynamic user-specific and brand-specific data repository, and generate channel-specific of cross-channel marketing action plan and corresponding personalized marketing assets, and/or marketing strategy”, amounts to no more than mere instructions to apply the exception using a generic computer component.
Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept. Therefore, the claim is not patent eligible. (Step 2B: NO).
Regarding dependent claims 2-14, 16, 18-19, and 22-24, the dependent claims do not impart patent eligibility to the abstract idea of the independent claim. The dependent claims rather further narrow the abstract idea and the narrower scope does not change the outcome of the two-part Mayo test. Narrowing the scope of the claims is not enough to impart eligibility as it is still interpreted as an abstract idea, a narrower abstract idea.
Regarding dependent claim 2, the claim simply refines the abstract idea by further reciting execute the action plan via one or more associated execution platforms, that fall under the category of Organizing Human activity and Mental process groupings of abstract ideas as described above in the independent claim 1. Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 3, the claim simply refines the abstract idea by further reciting autonomously collect performance data from the one or more associated execution platforms and updating the user- specific data repository…, that fall under the category of Organizing Human activity and Mental process groupings of abstract ideas as described above in the independent claim 1. Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 4, the claim simply refines the abstract idea by further reciting prompt the user with one or more additional questions and updating the user-specific data repository…, that fall under the category of Organizing Human activity and Mental process groupings of abstract ideas as described above in the independent claim 1. Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 5, the claim recites the additional element wherein generating the marketing for the action plan comprises applying one or more natural language processing (NLP) models on the user-specific data repository to produce an output with personalized, data-based marketing assets, is used to generally apply the abstract idea and invokes the computer merely as a tool to perform an existing process. See MPEP 2106.05(f). (See claim 1 above). Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 6, the claim recites the additional element wherein the output is selected from a text document, a blog, an email, an ad, a social media post…, is mere data gathering and transmitting recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (See claim 1 above). Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 7, the claim recites the additional element wherein compile the generated action plan comprises applying a reinforcement learning algorithm on the user-specific data repository, is used to generally apply the abstract idea without placing any limits on how the machine learning functions. Rather, this limitation only recites the outcome of “generate the action plan” and does not include any details about how the solution is accomplished. See MPEP 2106.05(f). (See claim 1 above). Moreover, the claim recites the additional elements combines real-time performance data from autonomously collected performance metrics of the user on any single channel and/or a combination of, and/or human feedback, which are mere data gathering and transmitting recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (See claim 1 above). Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 8, the claim recites the additional elements wherein the action plan comprises one or more actions selected from creating marketing assets, generating an SEO content plan posting on social media, sending an email, creating and/or publishing a blog, creating and/or publishing an advertisement campaign or any combination thereof, are mere data gathering and transmitting recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (See claim 1 above). Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 9, the claim recites the additional elements wherein compiling a marketing strategy or an action plan comprises selecting one or more channels for publishing the generated assets and/or determining a budget plan for the marketing strategy or action plan., wherein the one or more channels comprise any one or more of a social network…, are mere data gathering and transmitting recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (See claim 1 above). Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 10, the claim simply refines the abstract idea by further reciting wherein compiling an action plan comprises identifying the best channel…, that fall under the category of Organizing Human activity and Mental process groupings of abstract ideas as described above in the independent claim 1. Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 11, the claim simply refines the abstract idea by further reciting wherein the key concepts comprise any one or more of: one or more insights on the company, one or more strategies, one or more action plans…, that fall under the category of Organizing Human activity and Mental process groupings of abstract ideas as described above in the independent claim 1. Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claims 12-14 and 16-17, the claims simply refine the abstract idea by further reciting wherein the extracted data is associated with at least one of: the company of the user, one or more clients/prospects of the company of the user …, that fall under the category of Organizing Human activity and Mental process groupings of abstract ideas as described above in the independent claim 1. Thus, the dependent claims do not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 18, the claim recites the additional element wherein generating the user-specific data repository comprises applying an expert knowledge module and a reinforcement learning algorithm on the inputted answers, is used to generally apply the abstract idea without placing any limits on how the machine learning functions. Rather, this limitation only recites the outcome of “generate the action plan” and does not include any details about how the solution is accomplished. See MPEP 2106.05(f). (See claim 1 above). Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 19, the claim recites the additional elements wherein the processor is further configured to update the user data repository by extracting additional data from the internet and/or at least one application program interface (API)…, are mere data gathering and transmitting recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (See claim 1 above). Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 22, the claim recites the additional elements wherein the platform comprises a multi-model architecture allowing different marketing products to be fine-tuned using different models to generate the digital marketing action plan and the personalized marketing assets, which are mere data gathering and transmitting recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (See claim 1 above). Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 23, the claim recites the additional elements wherein the second party media platforms comprise one or more of: social media platforms, user analytics platforms an/or user ad platforms, which are mere data gathering and transmitting recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (See claim 1 above). Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Regarding dependent claim 24, the claim simply refines the abstract idea by further reciting wherein the user-specific data repository further includes the user's desired business outcomes and/or key performance indicators (KPIs), and wherein the generated action plan is selected based on a probability of achieving said outcomes and/or KPIs, that fall under the category of Organizing Human activity and Mental process groupings of abstract ideas as described above in the independent claim 1. Thus, the dependent claim does not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application under Step 2A-Prong Two), results in the claim being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Therefore, none of the dependent claims alone or as an ordered combination add limitations that qualify as significantly more than the abstract idea.
Accordingly, claims 1-14, 16, 18-19, and 22-24 are not draw to eligible subject matter as they are directed to an abstract idea without significantly more and are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
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 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.
Claim Rejections - 35 USC § 102
5. 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.
6. Claims 1-14, 16, 18-19, and 22-24 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Khoury et al. (hereinafter Khoury, US 2021/0224858).
Regarding to claim 1, Khoury discloses a virtual marketing agent (VMA) platform comprising:
a user interface configured to collect first-party data, the first-party data comprising user inputted answers to a questionnaire (para [0120], FIG. 1B, in generating a communication, e.g., an advertisement to be disbursed, either manually or automatically, a user may make a request, at a project dashboard 22 generated and presented at a local computing 20 resource of the system, that a communication be generated, such as via an HTTP request entered at a browser interface. The request may be made in the form of entering responses to an online interview, or may be made by presenting selections to a user via one or more, e.g., a series, of drop down menus, or may be made on an intuitive basis by the system suggesting information by which the advertisement is to be generated; para [0450], to identify factors of particular interest to an online retailer and/or a consumer thereof, the system may present one or more users to a series of questions, such as via an automated interview process, the responses to which may be used to characterize and/or rank content that may be useful to a user of the system, such as for generating communications and/or for making purchases); and
a processor configured to:
analyze, using a natural language model, the inputted answers and extract therefrom a plurality of key concepts parameters (para [0202], the replies may be parsed, such as by a natural language processing element, e.g., based on key words or phrases used, and through the directed selection and/or generation of responses can intelligently direct the conversation toward an end goal so as to funnel the consumer conversant to a desired action. Such natural language processing may be keyed off of keywords, phrases, expressed or implied sentiments, feedback, and the like; para [0045], the server may include a data collection engine for obtaining and extracting data from a web page. In such an instance, the data collected may include a plurality of media components, such as a text element and an image or video element that may be used as an advertising component of the system);
autonomously retrieve, without requiring user prompts (para [0218], The present autonomous smart bot module therefore is configured for overcoming these problems, and are thus, configured for being scalable, upwards and downwards to handle the online demand across the system, where one or more different automated chat bots may be responding to communications being run across several different interfaces of a national brand, each dealing with an individualized consumer in a personalized, localized, and catered manner, such as where answers to various queries can be generated and given in a personalized and location dependent manner, autonomously, such as via an autonomous, intelligent smart bot):
a. insights, analytics and performance data from second-party media platforms, (para [0081], the data collection module 12 may include one or more collection processing engines 16 that are configured for collecting data from one or more web pages of a website and/or for generating communication content out of the collected content. Specifically, one or more sets of processing engines may be included and configured for generating one or more content items, sentiments, and/or communications); and/or
b. third-party data from the internet, and from at least one application program interface (API), said third-party data comprising competitor activity, trends, market dynamics, gaps and opportunities, and/or contextual data associated with external events (para [0113], the collecting and/or generating of the content data may include querying one or more webpages of one or more websites, e.g., social media modalities, based on one or more filters, such as where the one or more filters may include: a keyword filter, a character filter, a number filter, a language filter, a text-recognition filter, an image recognition filter, an image filter, a sentiment filter, a geolocation filter, an antonym filter, a chronological filter, a characteristic filter, and the like. In certain instances, the collected data may include content data that includes a media component, such as a text element and/or an image element; para [0114], the collected data may further include metadata, such as metadata associated with one or more of the content data, a collection of content data, geographic data, website data, webpage data, metric data, and the like. In such an instance, the metric data may include characteristic data characterizing one or more characteristics of the content data, the collection of content data, the content recipient, the geographic data, as well as the website data and the webpage data from which the content was collected and/or to be posted, and the like; para [0153], the system server may include one or more APIs from which to receive content and data from other system servers, e.g., social media servers, such as with respect to the deployment of advertisements, e.g., on their platforms, and may also include APIs for receiving content and/or data, such as from sellers of products or services, which are the subjects of the advertisement, where the received data pertains to the consumers who performed an act in response to having been exposed to the advertisement);
generate a dynamic user-specific and brand-specific data repository, based on the autonomously retrieved data and the extracted parameters (para [0143], During the communication generation and distribution process, a target audience may be defined. For instance, a target audience may be generated from one or more lists, derived from one or more online, or internal database, searches, or may be selected from amongst a number of pre-identified audiences saved in a library, such as in customer resource management database, point of sale database, and/or other target recipient characteristic database. The audience may be defined by one or more shared or non-shared attributes amongst its members, such as with respect to age, gender, language, demographics, interest, and/or behaviors; para [0260], the system may be configured for tracking content, as it is generated, posted online, interacted with, collected, modified, and reused, and may further be configured for identifying and tracking those who engage with that content, such as in manner so as to generate a personal characteristic profile those who engage with the content, such as by responding to a call for action provided by the communication); and
apply one or more predictive and generative machine-learning or deep-learning models to the user-specific data repository to proactively generate, without requiring user prompting a channel-specific or cross-channel marketing action plan and corresponding personalized marketing assets, and/or marketing strategy (para [0443] the machine-learning module may be employed so as to generate a profile of a company and/or a follower or consumer or potential consumer of the company, such as a defined communication recipient. The profile may be a list of properties, qualities, characteristics, and/or metrics that describe the company, their products or services, and/or their engagement with online media and/or the system. As such, the profile may be generated by a plurality of different methods, such as by providing an interview to the user and saving their responses, further characteristics may be determined based on their engagement with the system, specifically, or social media generally, such as by what they post, how and when they comment, the images they upload, and/or the activities surrounding the images they post, and the like).
Regarding to claim 2, Khoury discloses the platform of claim 1, wherein the processor is further configured to execute the action plan via one or more associated execution platforms (para [0138], the controls of the project dashboard 22 may further be configured for allowing the content generator, e.g., system user, to select an objective, a budget, a target audience, target characterizations and demographics, and a geographical distance within which the communication is to be distributed).
Regarding to claim 3, Khoury discloses the platform of claim 2, wherein the processor is further configured to autonomously collect performance data from the one or more associated execution platforms and update the user- specific data repository based on the collected performance data (para [0158], the system may be configured to track and evaluate the performance of the communications, e.g., advertisements, and based on this evaluation may make suggestions based on the determined performance, such as with respect to the selection of communication elements that have been scored and been proven to have a beneficial impact, such as with respect to increasing impressions and conversions, e.g., lift, where such analysis may be performed on the corporate or local level; para [0102], the images and/or texts may be viewed, such as via a preview display 22a, selected, e.g., from a variety of elements in an image or text library, and can be inserted into the template so as to generate the communication, such as by selection by a user of the system, or by the system itself, e.g., automatically and autonomously. For instance, using the dashboard interface 22, a variety of selectable images and/or texts can be presented to the user, from which one or more selections may be made. In other instances, the images and/or texts may be generated and/or retrieved, automatically and/or autonomously by the system itself; para [0103], And as indicated, such images may also be generated by the system and be selected individually by the user, or may be selected and/or retrieved and integrated into the template dynamically, e.g., autonomously, by the system itself, such as in accordance with various selected criteria).
Regarding to claim 4, Khoury discloses the platform of claim 1, wherein the processor is further configured to prompt the user with one or more additional questions and update the user-specific data repository based on answers to the one or more additional questions (para [0151], the system may be configured to elicit or otherwise receive recipient response data back from the social media platform and/or communication recipient, such as where the response data pertains to the effectiveness of the advertisement to achieve a defined objective, such as reach, looks or views, clicks, impressions, engagements, transactions, conversions, shares, up votes, and the like. In such an instance, the response data may be collected from all those who receive the messaging, such as those within or outside of the sender's defined social network. In reaction to this response data, the database and tagging modality can be updated with respect to future use).
Regarding to claim 5, Khoury discloses the platform of claim 1, wherein generating the marketing assets for the action plan comprises applying one or more natural language processing (NLP) models on the user-specific data repository to produce an output with personalized, data-based marketing assets (para 0226], Hence, as the user enters words into a text box at the graphical user interface, the system performs a natural language analysis of the words, identifies relevant key words and images, and performs a search of one or more categorical data structures so as to return results that are analyzed and predicted to be of relevance to the communication being crafted, which results may be in text or image format).
Regarding to claim 6, Khoury discloses the platform of claim 5, wherein the output is selected from a text document, a blog, an email, an ad, a social media post, investor deck, one pager, company profile, business plan, marketing plan, competitive analysis, swot analysis, financial plan and any combination thereof, in one or more of a text, image, video and/or audio format (para [0111], In one implementation, the analytics module 27 may be configured for determining one or more objectives of a communication campaign. For instance, the analytics module 27 may be configured for determining and configuring a budget for the campaign, and therefore, may perform a budget analysis that can be made to determine what the communication spend should be, e.g., based on a determined or predicted return on investment, and may further be configured for analyzing what effectiveness resulted; para [0133], Once a target and/or audience has been defined, then the platform may be used to generate the campaign creatives for fashioning an advertisement that may be created in a manner so as to be of particular interest to the recipient and/or audience being targeted. For instance, the platform may provide a variety of tools for generating advertisement creatives so as to produce templated advertisements capable of transmitting media rich files, including dynamic texts, dynamic images, videos, animations, graphics, links, calls to action, patterns, and the like, such as based on a correspondence between the products and goods being offered and the characteristics of one or more communication recipients).
Regarding to claim 7, Khoury discloses the platform of claim 1, wherein the processor is configured to compile the generated the action plan, the compiling comprising applying a reinforcement learning algorithm on the user-specific data repository, that combines real-time performance data from autonomously collected performance metrics of the user on any single channel and/or a combination of, and/or human feedback (para [0267], Specifically, the categorized content can then be entered into an approximate nearest numbers graph, or other data structure, and can be subjected to, or otherwise be evaluated by an AI module of the system, such as by being employed within one or more deep learning processes. For instance, the AI module of the system may evaluate each piece of content that is collected such as for the purpose of evaluating and/or scoring the content, e.g., against one or more metrics. For example, content can be evaluated and scored on an account by account, platform by platform, location by location, and/or audience by audience basis and/or with respect to one or more objectives sought to be achieved; para [0099], a compiler 24 may be included where the compiler 24 is configured for integrating and compiling the suggested and/or selected media component into the suggested and/or selected media template so as to compile the corresponding codes and generate the communication. In a particular instance, one or more campaign objectives and/or parameters can be determined at this stage, such that the determined and/or selected texts, images, media rich assets may be called, e.g., by the project builder 22 and/or compiler 24, or otherwise be populated into designated data fields or containers of one or more layers of a selected template).
Regarding to claim 8, Khoury discloses the platform of claim 1, wherein the action plan comprises one or more actions selected from creating marketing assets, generating an SEO content plan posting on social media, sending an email, creating and /or publishing a blog, creating/or publishing an advertisement campaign or any combination thereof (para [0204], generating communications, but for generating an advertisement campaign along with all of the activities pursuant to running the campaign, including the development of one or more workflows that may be implemented in running the campaign, which workflows may include data collection and aggregation, generating a context for a communication, generating a communication, e.g., via a communication builder, calendaring all of the events leading up to running advertisement campaign, as well as scheduling the mass distribution of advertisements and other communications, performing one or more conflicts checks, such as based on content, geography, timing, and location, and tracking and determining of how the communications are received by one or more recipients).
Regarding to claim 9, Khoury discloses the platform of claim 1, wherein compiling a marketing strategy or an action plan comprises selecting one or more channels for publishing the generated assets and/or determining a budget plan for the marketing strategy or action plan, wherein the one or more channels comprise any one or more of a social network, a program, a conference, an email, a blog, an ad, a press release, a message, a media publication, a meeting, or any combination thereof, and selecting one or more media formats, comprising text, video, image, multi-image, audio or any combination thereof (para [0141], the advertisement may be published or otherwise transmitted, e.g., via a suitably configured distribution engine 28 to one or more social media platforms, such as FACEBOOK®, INSTAGRAM®, TWITTER®, TIKTOK®, and the like, for distribution thereby, for example, by a single or multiple corporate or local account. In one exemplary embodiment, communication publishing may be performed at the group, e.g., corporate, level, such as from two to thousands of locations, and in other embodiments, a single corporate and/or local account can be employed for the purpose of distributing the communication to a much smaller local level. Publishing may be performed in accordance with various different parameters, such as based on a determined budget allocation, and based on one or more selected communication campaign objectives; para [0125], Typically, the advertisement may include, or may be made to include dynamic text and images, where such image content can include digital photos, a carousel of images, videos, animations, GIFs, JPEGS, GIPHY's, and the like. In various instances, a database and/or library of prefabricated content may include a carousel of advertisements or content thereof of different categories and types, such as text, image, carousel, videos, and the like, which may be made available to a communication generator for selection in the generation of a communication).
Regarding to claim 10, Khoury discloses the platform of claim 9, wherein compiling an action plan comprises identifying the best channel, the best message, competitor gap analysis to identify white-space opportunities, an optimal timing, an optimal budget and/or frequency of activity within each channel, and a feasible pathway to achieving user outcome KPIs at an optimal ROI (para [0322], the system can determine one or more trends and patterns in the timing of posting for any particular location for a brand employing the communications platform so as to determine when the optimal time for distributing a communication will be, such as a point in time at which webpage traffic in a community market place is at its highest; para [0142], budgeting can be determined based on a fixed budget evenly split across distribution locations, recipient classes, or a floating budget based on a performed or perceived cost benefit analysis, such as where more budget is allocated to those locations that are best suited for generating a greater return on investment within a defined recipient class; para [0158], the system may be configured to track and evaluate the performance of the communications, e.g., advertisements, and based on this evaluation may make suggestions based on the determined performance, such as with respect to the selection of communication elements that have been scored and been proven to have a beneficial impact, such as with respect to increasing impressions and conversions, e.g., lift, where such analysis may be performed on the corporate or local level).
Regarding to claim 11, Khoury discloses the method of claim 1, wherein the key concepts comprise any one or more of: one or more insights on the company, or more insights on the competitors, one or more insights on the market dynamics, one or more strategies, one or more action plans, one or more marketing assets, one or more business goals or any combination thereof (para [0160], The data to be collected and analyzed may pertain to one or more locations, content information related to a generated and/or distributed advertisement and/or its effectiveness, various discussions being held about the advertisement, the products or services proffered, and/or its audiences, recipient data, discussions about the advertised company, the reputation of the company, data pertaining to the creative elements, data about ad plus and/or boost functions, and reports generated with respect thereto).
Regarding to claim 12, Khoury discloses the platform of claim 1, wherein the extracted data is associated with at least one of: the company of the user, one or more clients/prospects of the company of the user, one or more competitors of the company of the user, the professional field of the user’s company, the target market of the company of the user, or any combination thereof (para [0194], the system may perform an analysis and increase reach and engagement by boosting the communications number, style, and frequency of the same or similar communications. For example, where a company has made an investment in a certain amount of advertising that has evidenced signs of success, the system may make a determination that by increasing the investment in further like advertising may result in additional gains).
Regarding to claim 13, Khoury discloses the platform of claim 1, wherein the extracted data comprises parameters comprising any one or more of: activities of the company of the user, performance of the company of the user, results of the company of the user, activities of one or more competitor companies of the user, performance of one or more competitor companies of the user, results of one or more competitor companies of the user, and/or any combination thereof (para [0194], Thus, the system may not only determine and allocate a budget, such as for running a communications campaign, but may further perform an analysis and recommending re-allocation as well as increasing or decreasing the budgeted allocation, such as based on needs and/or performance. In a manner such as this, one or more determined objectives, such as increased sales, brand awareness, and consistency in messaging may be ensured and optimized by the platform of the system).
Regarding to claim 14, Khoury discloses the platform of claim 1, wherein generating the user-specific data repository comprises comparing two or more parameters of the extracted data (para [0150], the system may include a tracking module 35 configured for tracking and/or comparing the performance of the campaigns at the individual location or group level. Particularly, the system may be configured to track the effectiveness of the communications, and/or components thereof, such as with respect to the advertisement's ability to become an impression, e.g., influence a consumer's desire to view the advertisement, and/or to become a conversion, e.g., influence the consumer to make a purchase of the advertised goods or services).
Regarding to claim 16, Khoury discloses the platform of claim 1, wherein the questionnaire comprises one or more question modules, wherein each question module comprises one or more different questions, and wherein one or more of the question modules comprises one or more questions selected from: requesting the company's name, company's webpage, business goals, key performance indicators (KPIs), and/or any combination thereof (para [0120], The request may be made in the form of entering responses to an online interview, or may be made by presenting selections to a user via one or more, e.g., a series, of drop down menus, or may be made on an intuitive basis by the system suggesting information by which the advertisement is to be generated; para [0405], the system may generate and employ one or more data structures that may be queried so as to predict an answer to one or more questions. For example, as described in detail herein, the system may be configured for receiving information with regard to the actions of one or more online, e.g., a plurality of social media, users. Such information may include website of interest information, content of interest information, target consumer identifying information, consumer social circle information, as well as social media engagement information, and the like. In various embodiments, to identify factors of particular interest to an online retailer and/or a consumer thereof, the system may present one or more users to a series of questions, such as via an automated interview process, the responses to which may be used to characterize and/or rank content that may be useful to a user of the system, such as for generating communications and/or for making purchases; para [0148], For instance, a number of characteristics of one or more business entities, products or services to be offered, communication elements, and/or communication recipient characteristics can be used in determining content to be recommended and/or used in generating, targeting, and distributing communications, so as to focus communications to a limited audience, e.g., within a defined demographic and/or a limited geographical region and/or having one or more defined characteristics of interest).
Regarding to claim 18, Khoury discloses the platform of claim 1, wherein generating the user data repository comprises applying an expert knowledge module and a reinforcement learning algorithm on the inputted answers, and the derivative autonomously extracted data (para [0230], Particularly, the analyses engines described herein can identify the characteristics that make content good for particular users, the communications can be transmitted to end users, and feedback can be retrieved to determine how well the communications worked to achieve a predicted result, all of which data can then be fed back into the system to train the predictive models being employed by the machine learning engine, as well as to inform the inference engines; para [0164], Particularly, with respect to communication generation, the AI module 29 may be configured for autonomously selecting the template and the media component such as where the selecting may be based on results of one or more evaluations, analyses, and/or scoring protocols being run on communication content).
Regarding to claim 19, Khoury discloses the platform of claim 1, wherein the processor is further configured to update the user data repository by extracting additional data from the internet and/or at least one application program interface (API), based on the plurality of key parameters; and wherein the processor is further configured to autonomously and proactively update the user-specific data repository and/or the output based, at least in part, on the additional extracted data; and wherein the processor is further configured to receive, from the user, new and/or adjusted answers to the questionnaire, and updating the key parameters, the output and/or the data repository, based on the new and/or adjusted answers (para [0262], This data may be tracked through business relations, e.g., LDE data, suitably configured APIs, internet collection, e.g., scraping, eliciting information directly from the consumer, voluntary information proffered by the consumer, CRM and POS data, following the consumer on their social media platforms; para [0151], In such an instance, the response data may be collected from all those who receive the messaging, such as those within or outside of the sender's defined social network. In reaction to this response data, the database and tagging modality can be updated with respect to future use; para [0236], For instance, the system may include a series of processing engines that can be configured as a reputation manager, whereby the reputation manager may oversee communication recipient response and filter for reputation sentiment of how recipients are feeling about the business organization communicator. Where a reputation significant communication is identified, the system may schedule one or more tasks to be performed based on the received feedback data, such as whether to use or not use the generated content again, or to modify the content, and/or feed the data to the machine learning protocol prior to further use)
Regarding to claim 22, Khoury discloses the platform of claim 1, wherein the platform comprises a multi-model architecture allowing different marketing products to be fine-tuned using different models to generate the digital marketing action plan and the personalized marketing assets (para [0213], the communication campaign may have layers of scoring and costs that can be counter-balanced by an increasing return on investment, such as based on a page by page and/or platform by platform model. These models may be generated via a machine learning module of the system, which model may be used to generate one or more predictions, such as to how a communication will perform, such as how closely the communication will meet the needs of one or more recipients, which predictions may be based on prior actions taken, communications responded to, by the recipient).
Regarding to claim 23, Khoury discloses the platform of claim 1, wherein the second party media platforms comprise one or more of: social media platforms, user analytics platforms an/or user ad platforms (para [0015], Particularly, the present technologies are directed to solving the gap in message management across social media platforms so as to make it possible and easy for multi-location brands and their agencies to create dynamic localized ads, store, and share ad creative across teams, and instantly promote localized ads to hundreds or thousands of locations or local social media pages and/or other interfaces).
Regarding to claim 24, Khoury discloses the platform of claim 1, wherein the user-specific data repository further includes the user's desired business outcomes and/or key performance indicators (KPIs), and wherein the generated action plan is selected based on a probability of achieving said outcomes and/or KPIs (para [0150], the system may include a tracking module 35 configured for tracking and/or comparing the performance of the campaigns at the individual location or group level. Particularly, the system may be configured to track the effectiveness of the communications, and/or components thereof, such as with respect to the advertisement's ability to become an impression, e.g., influence a consumer's desire to view the advertisement, and/or to become a conversion, e.g., influence the consumer to make a purchase of the advertised goods or services; para [0212], whether a communication is to be entered into the system by a user, selected from a preapproved list of responses, and/or suggested or generated by the system itself, the communication, or its content elements, may be subjected to a predictive model so as to determine a performance score for the content and/or for the recipient; para [0227], In this manner, the score may account for its past performance, and based on the score, content can be provided to the user for suggested use or not, which helps the user narrow down the options provided for review and selection; para [0274], the system may be configured to assign the likelihood of success for each content item and for each group and/or cluster in the data structure, e.g., based on the evaluating and scoring intelligence. The AI system, therefore, can be trained to recognize and track online content, to evaluate the content's performance in the past, to predict its future performance, e.g., via a social post predictor engine, and based on that prediction to either use (or recommend for use) that content in new communications and messaging, to edit it, or to discard it. Where content is to be evaluated and/or re-used, it may be done so based on past performance and/or location, targeted audience, and/or its expected future performance at achieving one or more defined objectives, all of which can be fed into and be displayed in an approximate nearest neighbor graph, and used for new content recommendation and generation. Specifically, each neighbor's likelihood of success may be determined, and this information may be fed in accordance with a predictive model into a content recommendation engine).
Response to Arguments/Amendment
7. Applicant's arguments with respect to claims 1-14, 16, 18-19, and 22-24 have been fully considered but are not persuasive.
I. Claim Rejections - 35 USC § 101
Claims 1-14, 16, 18-19, and 22-24 are rejected under 35 U.S.C. 101 because the claim invention is directed to a judicial exception (i.e., law of nature, natural phenomenon, or abstract idea) without significantly more (See details above).
Step 2A-Prong 1
In response to the Applicant’s arguments that claim 1 does not recite an abstract idea, the Examiner respectfully disagrees and submits that the claim recites a system for providing marketing management, planning, creation and execution capabilities to businesses. The system receives marketing information from the target audience via user inputted answers to questionnaire, then analyzes to extract key concepts. The system then generates marketing action plan. The claim recites the steps: analyze the first-party data and extracting therefrom a plurality of key concepts; generate a dynamic user-specific and brand-specific data repository, and generate channel-specific of cross-channel marketing action plan and corresponding personalized marketing assets, and/or marketing strategy, under its broadest reasonable interpretation when read in light of the Specification, falls within “Certain Methods of Organizing Human Activity” grouping of abstract ideas as they cover performance of commercial or legal interactions including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, business relations.
Moreover, the claim recites analyze the first-party data and extracting therefrom a plurality of key concepts; generate a dynamic user-specific and brand-specific data repository, and generate channel-specific of cross-channel marketing action plan and corresponding personalized marketing assets, and/or marketing strategy, as drafted, is a process that, under its broadest reasonable interpretation when read in light of the Specification, covers performance of the limitations in the mind, can be practically performed by human in their mind or with pen/paper, but for the recitation of generic computer components. That is, other than reciting “a computer/processor/automatically”, nothing in the claim elements preclude the steps from practically being performed in the mind. The mere nominal recitation of generic computing devices does not take the claim limitation out of the Mental Processes grouping of abstract ideas. Thus, if a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas (concepts performed in the human mind including an observation, evaluation, judgment, opinion). See MPEP 2106.04(a)(2), subsection III. Therefore, the claim recites an abstract idea.
The new features added to the claim “autonomously retrieve, without requiring user prompts: insights, analytics and performance data from second-party media platforms; and third-party data from the Internet, and from at least one application program interface (API)” are additional elements and are analyzing under Step2A-Prong 2.
Step 2A-Prong 2
In response to the Applicant’s arguments that the claim is integrated into a practical application, the Examiner respectfully disagrees and submits that:
The claim recites the additional elements “user interface configured to collect first-party data”, “autonomously retrieve, without requiring user prompts: insights, analytics and performance data from second-party media platforms; and third-party data from the Internet, and from at least one application program interface (API)” are mere data gathering and transmitting recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (“whether the limitation is significant”). In addition, all uses of the recited judicial exceptions require such data gathering and outputting, and, as such, these limitations do not impose any meaningful limits on the claim. These limitations amount to necessary data gathering and outputting. See MPEP 2106.05.
The additional elements “analyzing, using a natural language model, the first party data and extract therefrom”, and “apply one or more predictive and generative machine-learning or deep-leaning models, to generate without requiring user prompting a channel-specific or cross-channel marketing action plan” provide nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception.
The additional element “analyzing, using a natural language model, the first party data and extract therefrom” is used to generally apply the abstract idea and invokes the computer merely as a tool to perform an existing process. See MPEP 2106.05(f).
The additional element “apply one or more predictive and generative machine-learning or deep-leaning models, to generate without requiring user prompting a channel-specific or cross-channel marketing action plan” is used to generally apply the abstract idea without placing any limits on how the machine learning functions. Rather, this limitation only recites the outcome of “generate a digital marketing action plan” and does not include any details about how the solution is accomplished. See MPEP 2106.05(f).
The additional element “apply one or more predictive and generative machine-learning or deep-leaning models, to generate without requiring user prompting a channel-specific or cross-channel marketing action plan” also merely indicates a field of use or technological environment in which the judicial exception is performed. Although the additional element “apply one or more predictive and generative machine-learning or deep-leaning models, to generate without requiring user prompting a channel-specific or cross-channel marketing action plan” limits the identified judicial exceptions “generate a channel-specific or cross-channel marketing action plan”, this type of limitation merely confines the use of the abstract idea to a particular technological environment (machine learning) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Further, the steps of “analyze the first-party data and extracting therefrom a plurality of key concepts; generate a dynamic user-specific and brand-specific data repository, and generate channel-specific of cross-channel marketing action plan and corresponding personalized marketing assets, and/or marketing strategy”, are recited as being performed by the processor. The processor is recited at a high level of generality and is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). The additional elements recite generic computer components the processor, a memory, and software programming instructions that are recited a high-level of generality that merely perform, conduct, carry out, implement, and/or narrow the abstract idea itself. Accordingly, the additional elements evaluated individually and in combination do not integrate the abstract idea into a practical application because they comprise or include limitations that are not indicative of integration into a practical application such as 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).
Moreover, these additional elements do not provide any improvements to the functioning of the computer, the processor, the memory, improvement to the user interface/Internet, application program interface (API), or other technology. They do not recite a particular machine or manufacture that is integral to the claims, and do not transform or reduce a particular article to a different state or thing.
Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Step 2B
In response to the Applicant’s arguments that the claim recites “significantly more”, the Examiner respectfully disagrees and submits that:
As explained with respect to Step 2A, Prong Two, the additional elements of “analyzing, using a natural language model, the first party data and extract therefrom”, and “apply one or more predictive and generative machine-learning or deep-leaning models, to generate without requiring user prompting a channel-specific or cross-channel marketing action plan” are at best mere instructions to “apply” the abstract ideas, which cannot provide an inventive concept. See MPEP 2106.05(f).
As discussed in Step 2A, Prong Two above, the additional elements of “user interface configured to collect first-party data”, “autonomously retrieve, without requiring user prompts: insights, analytics and performance data from second-party media platforms; and third-party data from the Internet, and from at least one application program interface (API)” are recited at a high level of generality. These elements amount to gathering and transmitting data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II.
As discussed in Step 2A, Prong Two above, the recitation of the processor to perform limitations “analyze the first-party data and extracting therefrom a plurality of key concepts; generate a dynamic user-specific and brand-specific data repository, and generate channel-specific of cross-channel marketing action plan and corresponding personalized marketing assets, and/or marketing strategy”, amounts to no more than mere instructions to apply the exception using a generic computer component.
Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept. Therefore, the claim is not patent eligible.
Accordingly, the 101 rejection is maintained.
II. Claim Rejections - 35 USC § 102
Applicant's arguments filed regarding to claims 1-14, 16, 18-19, and 22-24 have been fully considered but they are not persuasive.
In response to the Applicant’s arguments that Khoury does not disclose the system autonomously retrieve, without requiring user prompting, second-party performance analytics and third-party data through machine-initiated API based ingestion, the Examiner respectfully disagrees and submits that Khoury described in para [0002], The subject matter described herein relates to the generating and distributing of online, e.g., web, content, autonomously and automatically; para [0023], A unique feature of the platform is an intuitive generating, distributing, tracking, and reporting dashboard, as well as a series of automatic and/or autonomous communication generation engines that allows a user and/or the system itself to generate, deploy, and regulate ad spend and performance at the national, regional, and local levels so as to gain key insights, develop, and elevate advertising strategies; para [0032], An advertisement builder for accessing the memory and building the advertisement may also be included, such as based on the media template and media component selected by the user, or by the system itself In such an instance, the communications builder may include one or more autonomous communications generation engines, which may be configured as one or more smart chat bots for autonomous communication generation; para [0043], Likewise, in various embodiments, the AI module may be configured for generating, or at least assisting in the generating, and distributing, of the advertisement, which may be generated and distributed automatically and/or autonomously at real time and on the fly upon the occurrence of a triggering event; para [0102], In some instances, the images and/or texts may be viewed, such as via a preview display 22a, selected, e.g., from a variety of elements in an image or text library, and can be inserted into the template so as to generate the communication, such as by selection by a user of the system, or by the system itself, e.g., automatically and autonomously; para [0103], And as indicated, such images may also be generated by the system and be selected individually by the user, or may be selected and/or retrieved and integrated into the template dynamically, e.g., autonomously, by the system itself, such as in accordance with various selected criteria. Thus, in Khoury’s, the system retrieves, generates and distributes of online, e.g., web, content, autonomously and automatically. Therefore, Khoury discloses the system autonomously retrieve, without requiring user prompting, second-party performance analytics and third-party data through machine-initiated API based ingestion as claimed.
In response to the Applicant’s arguments that Khoury contains no disclosure of such probability-driven selection or optimization against defined outcomes or KPIs; it instead generates recommendations based on questionnaire-derived concepts without autonomous, outcome-driven optimization, the Examiner respectfully disagrees and submits that Khoury described in para [0111], For instance, the system may include an analytics module 27, which may be coupled to an AI module that may include one or more machine learning and/or inference engines that form an Artificial Intelligence module 29 of the system. In one implementation, the analytics module 27 may be configured for determining one or more objectives of a communication campaign; para [0164], the AI module 29 may include a machine learning engine as well as an inference engine that are configured for interacting with one or more of the system processing engines such as for the purpose of generating and/or evaluating communications, communication content, and/or communication recipients as well as their response to communications; para [0186], More specifically, the AI module, e.g., a machine learning engine, of the platform may be configured to analyze the content items, determine their subject matter, and an inference engine of the system may be configured to evaluate the content for use as an advertisement and/or other communication, and an AI associated autonomous project builder can then generate the advertisement and/or communication in such a manner as to express the same or similar theme to the data collected and/or the source from where it was collected, such as including the same or similar subject matter, tone, look, feel, and the like. Thus, in Khoury’s, the system applies the machine learning model to proactively automatically generate advertisements. Therefore, Khoury discloses applying predictive and generative ML/DL models to proactively generate channel-specific or cross-channel action plans and marketing assets, without requiring user prompting as claimed.
In response to the Applicant’s arguments that Khoury does not teach or suggest the dynamic user-specific and brand-specific data repository, the Examiner respectfully disagrees and submits that Khoury described in para [0143], During the communication generation and distribution process, a target audience may be defined. For instance, a target audience may be generated from one or more lists, derived from one or more online, or internal database, searches, or may be selected from amongst a number of pre-identified audiences saved in a library, such as in customer resource management database, point of sale database, and/or other target recipient characteristic database. The audience may be defined by one or more shared or non-shared attributes amongst its members, such as with respect to age, gender, language, demographics, interest, and/or behaviors; para [0260], the system may be configured for tracking content, as it is generated, posted online, interacted with, collected, modified, and reused, and may further be configured for identifying and tracking those who engage with that content, such as in manner so as to generate a personal characteristic profile those who engage with the content, such as by responding to a call for action provided by the communication; para [0121], For example, in one implementation, a template reflecting the universal look and feel of a national brand can be employed, while information pertaining to each of the localized franchisees and/or the products and services they offer that have been determined to be of interest to one or more target recipients, as well as their parameters for servicing a localized market, can be retrieved and inserted into the communication template, e.g., at one or more defined containers of one or more layers of the template, so as to generate a variety of advertisements that all have the same look and feel, but where each is uniquely catered to the local audience and/or recipients to which they are to be distributed, such as by posting on one or more social media modalities unique to each market. Thus, in Khoury’s, the system generates a personal characteristic profile from one or more lists, derived from one or more online, or internal database, searches, or may be selected from amongst a number of pre-identified audiences saved in a library. The system also retrieves the franchisees, the products and services for generating advertisements. Therefore, Khoury discloses the dynamic user-specific and brand-specific data repository as claimed.
In response to the Applicant’s arguments regarding to claim 7 that Khoury does not disclose compiling the generated action plan comprises applying a reinforcement learning algorithm combining real-time performance data and/or human feedback, the Examiner respectfully disagrees and submits that Khoury described in para [0267], Specifically, the categorized content can then be entered into an approximate nearest numbers graph, or other data structure, and can be subjected to, or otherwise be evaluated by an AI module of the system, such as by being employed within one or more deep learning processes. For instance, the AI module of the system may evaluate each piece of content that is collected such as for the purpose of evaluating and/or scoring the content, e.g., against one or more metrics. For example, content can be evaluated and scored on an account by account, platform by platform, location by location, and/or audience by audience basis and/or with respect to one or more objectives sought to be achieved; para [0099], a compiler 24 may be included where the compiler 24 is configured for integrating and compiling the suggested and/or selected media component into the suggested and/or selected media template so as to compile the corresponding codes and generate the communication. In a particular instance, one or more campaign objectives and/or parameters can be determined at this stage, such that the determined and/or selected texts, images, media rich assets may be called, e.g., by the project builder 22 and/or compiler 24, or otherwise be populated into designated data fields or containers of one or more layers of a selected template. Khoury discloses compiling the generated action plan comprises applying a reinforcement learning algorithm combining real-time performance data and/or human feedback, as claimed.
In response to the Applicant’s arguments regarding to claims 18 and 19 that Khoury does not disclose perform any monitoring of performance progression, predictive comparison, or autonomous plan evolution, the Examiner respectfully disagrees and submits that Khoury discloses described in para [0075], a communication, e.g., an advertisement, may be generated so as to be easily edited, updated, or otherwise changed, e.g., dynamically and/or on the fly, such as for use across a variety of geographically disperse locations, on a variety of different social media platforms, and/or to achieve multiple objectives per advertisement structure; para [0035], Likewise, using the devices, systems, and methods disclosed herein, communications and advertisements cannot only be generated and deployed, e.g., autonomously and on the fly, but given the layered and containerized nature of the building, the distributed advertisements can also be edited and updated real time and on the fly; para [0071], the system provides a platform for generating, evaluating, reviewing, and distributing communications, as well as for tracking, monitoring, scoring, and predicting the outcome of such communications as well as the persons who receive and/or engage with the distributed communications; para [0073], More particularly, the system provided herein can include one or more processing modules for running a communications campaign, including the generating, tracking, and reviewing of communications, as well as monitoring the effects of those communications on communication recipients; para [0106], Consequently, the system 1 may include a set of processing engines for tracking and/or monitoring communications once distributed as well as those who engage with the communication; para [0163], top performing creatives, such as with respect to one or more of impressions, conversions, engagements, reach, lead generations, and the like, can be tracked, monitored, and used in the building of new advertisements. The number of advertisements executed, e.g., per campaign, can also be tracked and optimized. Additionally, performance by objective may be determined and tracked, such as with respect to the progress thereof; para [0249], the actual results of the communication being sent to and responded to by a recipient can be collected and fed back into the machine learning component so as to be compared with the predicted results, and where useful the predictive analyses can be modified, a new model generated, and the new predictive model may be applied to new content to be generated and a new predictive result can be determined and tested. Therefore, Khoury discloses perform any monitoring of performance progression, predictive comparison, or autonomous plan evolution as claimed.
In response to the Applicant’s arguments regarding to claim 22, the Examiner submits that Khoury discloses described in para [0213], the communication campaign may have layers of scoring and costs that can be counter-balanced by an increasing return on investment, such as based on a page by page and/or platform by platform model. These models may be generated via a machine learning module of the system, which model may be used to generate one or more predictions, such as to how a communication will perform, such as how closely the communication will meet the needs of one or more recipients, which predictions may be based on prior actions taken, communications responded to, by the recipient). Therefore, Khoury discloses wherein the platform comprises a multi-model architecture allowing different marketing products to be fine-tuned using different models to generate the digital marketing action plan and the personalized marketing assets, as claimed.
Accordingly, the 102 rejection is maintained.
Conclusion
8. 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 extension fee 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 date of this final action.
9. Claims 1-14, 16, 18-19, and 22-24 are rejected.
10. The prior arts made of record and not relied upon are considered pertinent to applicant's disclosure:
Mei et al. (US 11,295,345) disclose a cost-focused determination of whether to deliver an electronic advertisement or notice to a particular user can be made through a cumulative consideration of the predicted return on investment over each of a plurality of electronic channels.
Harris et al. (US 2013/0191223) disclose a computing apparatus is configured to use a dynamic questionnaire, designed based on the spending patterns identified in the transaction data of a plurality of accounts, to determine the spending preferences of a user in accordance with the answers to the dynamic questionnaire and the spending patterns. Offers are customized for and targeted to the user based on the spending preferences of the user.
Burdick et al. (US 2008/0103902) disclose for a multi-party advertising exchange including advertising entities and publishing entities from different advertising networks, automatic apportioning of advertising transactions across inventory from different advertising channels.
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/NGA B NGUYEN/Primary Examiner, Art Unit 3625 April 17, 2026
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