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 responsive to amendment filed on 06/03/2026. Claims 2, 4, 7, 22, 24, 27, 30, and 32 are amended. Claims 2-9, and 22-33 are pending examination.
Claim Rejections - 35 USC § 101
2. 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 2-9 and 22-33 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.
Claim(s) 22 is/are drawn to method (i.e., a process), claim(s) 2 is/are drawn to a system (i.e., a machine/manufacture), and claim(s) 30 is/are drawn to non-transitory computer readable medium (i.e., a machine/manufacture). As such, claims 2, 22, and 30 is/are drawn to one of the statutory categories of invention.
Claims 2-9 and 22-33 are directed to providing offer and transaction history in a data feed and determining and providing benefit to a first user based on a second user activity associated with the offer. Specifically, claim(s) 2, 22, and 30 recite(s) determine an offer to extend to a user based on an interest of the user; first learning model trained for predicting offers, provide the offer in a data feed for an account of the user, wherein the data feed is provided via a social payment using an application programming interface (API) integration, wherein the data feed enables the offer and a transaction history of the account to be shared with one or more other users; detect that the user has processed a transaction associated with the offer using the account of the user; generate a share code for the transaction, wherein the share code identifies the user and is associated with at least one of an online merchant or an item associated with the transaction; post the share code to the data feed associated with the account via the API integration, wherein the data feed exposes the share code to the one or more other users via the social payment; provide an indication that the user has processed the transaction in the data feed in an association with the offer and the transaction wherein the indication is shared with the one or more other users via the data feed; determine a user activity associated with at least one of the indication, the offer, or a use of the share code by at least one of the one or more other users; determine a first benefit for the user based on the user activity and a second model trained for predicting benefits; and provide the first benefit to the account of the user, which is grouped within the Methods Of Organizing Human Activity and is similar to the concept of (commercial or legal interactions including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors business relations) grouping of abstract ideas in prong one of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 54 (January 7, 2019)). Accordingly, the claims recite an abstract idea (See pages 7, 10, Alice Corporation Pty. Ltd. v. CLS Bank International, et al., US Supreme Court, No. 13-298, June 19, 2014; 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 53-54 (January 7, 2019)).
The Claim limitations are listed under Methods Of Organizing Human Activity, and grouped as following:
determine an offer to extend to a user based on an interest of the user; first learning model trained for predicting offers, provide the offer in a data feed for an account of the user, wherein the data feed is provided via a social payment using an application programming interface (API) integration, wherein the data feed enables the offer and a transaction history of the account to be shared with one or more other users; which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations),
detect that the user has processed a transaction associated with the offer using the account of the user; which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations),
generate a share code for the transaction, wherein the share code identifies the user and is associated with at least one of an online merchant or an item associated with the transaction; post the share code to the data feed associated with the account via the API integration, wherein the data feed exposes the share code to the one or more other users via the social payment; which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations),
provide an indication that the user has processed the transaction in the data feed in an association with the offer and the transaction wherein the indication is shared with the one or more other users via the data feed; which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations),
determine a user activity associated with at least one of the indication, the offer, or a use of the share code by at least one of the one or more other users; determine a first benefit for the user based on the user activity and a second model trained for predicting benefits; and provide the first benefit to the account of the user; which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations).
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 54-55 (January 7, 2019)), the additional element(s) of the claim(s) such as system, non-transitory memory, hardware processors, system, machine, non-transitory machine-readable medium merely use(s) a computer as a tool to perform an abstract idea and/or generally link(s) the use of a judicial exception to a particular technological environment. Specifically, the system, non-transitory memory, hardware processors, system, machine, non-transitory machine-readable medium perform(s) the steps or functions of determine an offer to extend to a user based on an interest of the user; first learning model trained for predicting offers, provide the offer in a data feed for an account of the user, wherein the data feed is provided via a social payment using an application programming interface (API) integration, wherein the data feed enables the offer and a transaction history of the account to be shared with one or more other users; detect that the user has processed a transaction associated with the offer using the account of the user; generate a share code for the transaction, wherein the share code identifies the user and is associated with at least one of an online merchant or an item associated with the transaction; post the share code to the data feed associated with the account via the API integration, wherein the data feed exposes the share code to the one or more other users via the social payment; provide an indication that the user has processed the transaction in the data feed in an association with the offer and the transaction wherein the indication is shared with the one or more other users via the data feed; determine a user activity associated with at least one of the indication, the offer, or a use of the share code by at least one of the one or more other users; determine a first benefit for the user based on the user activity and a second model trained for predicting benefits; and provide the first benefit to the account of the user. The use of a processor/computer as a tool to implement the abstract idea and/or generally linking the use of the abstract idea to a particular technological environment does not integrate the abstract idea into a practical application because it requires no more than a computer performing functions that correspond to acts required to carry out the abstract idea. The additional elements do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition (Vanda Memo), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e) and Vanda Memo). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claims are directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when analyzed under step 2B of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 56 (January 7, 2019)), the additional element(s) of using a system, non-transitory memory, hardware processors, system, machine, non-transitory machine-readable medium to perform the steps amounts to no more than using a computer or processor to automate and/or implement the abstract idea of providing offer and transaction history in a data feed and determining and providing benefit to a first user based on a second user activity associated with the offer. As discussed above, taking the claim elements separately, the system, non-transitory memory, hardware processors, system, machine, non-transitory machine-readable medium perform(s) the steps or functions of determine an offer to extend to a user based on an interest of the user; first learning model trained for predicting offers, provide the offer in a data feed for an account of the user, wherein the data feed is provided via a social payment using an application programming interface (API) integration, wherein the data feed enables the offer and a transaction history of the account to be shared with one or more other users; detect that the user has processed a transaction associated with the offer using the account of the user; generate a share code for the transaction, wherein the share code identifies the user and is associated with at least one of an online merchant or an item associated with the transaction; post the share code to the data feed associated with the account via the API integration, wherein the data feed exposes the share code to the one or more other users via the social payment; provide an indication that the user has processed the transaction in the data feed in an association with the offer and the transaction wherein the indication is shared with the one or more other users via the data feed; determine a user activity associated with at least one of the indication, the offer, or a use of the share code by at least one of the one or more other users; determine a first benefit for the user based on the user activity and a second model trained for predicting benefits; and provide the first benefit to the account of the user. These functions correspond to the actions required to perform the abstract idea. Viewed as a whole, the combination of elements recited in the claims merely recite the concept of providing offer and transaction history in a data feed and determining and providing benefit to a first user based on a second user activity associated with the offer. Therefore, the use of these additional elements does no more than employ the computer as a tool to automate and/or implement the abstract idea. The use of a computer or processor to merely automate and/or implement the abstract idea cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)). Therefore, the claim is not patent eligible.
As for dependent claims 3-9 and 23-29, and 31-33 further describe the abstract idea of providing offer and transaction history in a data feed and determining and providing benefit to a first user based on a second user activity associated with the offer. Claim(s) 3-9 and 23-29, and 31-33 does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when analyzed under step 2B of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 56 (January 7, 2019)), the additional element(s) of using a system, non-transitory memory, hardware processors, system, machine, non-transitory machine-readable medium to perform the steps amounts to no more than using a computer or processor to automate and/or implement the abstract idea of providing offer and transaction history in a data feed and determining and providing benefit to a first user based on a second user activity associated with the offer. As discussed above, taking the claim elements separately, the system, non-transitory memory, hardware processors, system, machine, non-transitory machine-readable medium perform(s) the steps or functions of generate a post for the data feed based on at least one of the offer or the first benefit, wherein the post comprises a second benefit available to the user and additional users for at least one of an item or a merchant associated with the offer; and wherein the offer in the data feed includes a code usable when processing transactions associated with the offer for a discount, and wherein the user activity comprises using the code for at least one additional transaction, track user data for the user over a period of time from at least one of visited webpages by the user or software applications used by the user, wherein the offer is further determined based on the user data, wherein the user data comprises at least one of a past purchase, a web browsing history, a digital shopping list, one or more account subscriptions, a purchase benefit preference, or a second benefit previously provided to the user, wherein the user activity is one of a plurality of different interactions that can be performed with the offer by the one or more other users, and wherein each of the plurality of different interactions provides a separate benefit to the user based on a likelihood that a purchase is made from a corresponding one of the plurality of different interactions, receive a request for an incentive offer from the user based on the first benefit provided to the user; and generate the incentive offer for the user based on at least one of the first benefit or a second benefit conferrable to the user from a past account activity of the account, wherein the first and second ML models comprises one of a multi-layer ML model, a decision tree model, or a clustering model, and wherein at least one of the multi-layer model comprises an input layer, at least one hidden layer, and the output layer each having one or more trained nodes . These functions correspond to the actions required to perform the abstract idea. Viewed as a whole, the combination of elements recited in the claims merely recite the concept of providing offer and transaction history in a data feed and determining and providing benefit to a first user based on a second user activity associated with the offer. Therefore, the use of these additional elements does no more than employ the computer as a tool to automate and/or implement the abstract idea. The use of a computer or processor to merely automate and/or implement the abstract idea cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)). Therefore, the claim is not patent eligible.
Subject Matter Overcoming the Cited Prior Art
3. As detailed in the Office Action the Examiner has not applied a prior art rejection to Claim(s) 2-9 and 22-33 when viewed in combination with the corresponding independent claims, however the claim(s) has/have been rejected other grounds as detailed in the Office Action.
In reference to independent claims 2, 22, and 30, the Office is unaware of any references that teach, individually or without an unreasonable combination of references, the combination of limitations steps found in the claims especially limitation that says: “provide the offer in a data feed for an account of the user, wherein the data feed is provided via a social payment platform using an application programming interface (API) integration between the system and the social payment platform, wherein the data feed enables the offer and a transaction history of the account to be shared with one or more other users and generate a share code for the transaction, wherein the share code identifies the user and is associated with at least one of an online merchant or an item associated with the transaction; post the share code to the data feed associated with the account via the API integration, wherein the data feed exposes the share code to the one or more other users via the social payment platform.”. No reference found that would teach the above limitation(s).
The first most relevant prior art identified by the Examiner is 20170330229 “Bryant”. It teaches an RFID-based wireless ordering system in which a consumer uses a wireless ordering device to read RFID tags from mass media publications, such as magazines and billboards, to order products from vendors. See paragraphs [0028]-[0029] of Bryant. Bryant further teaches a rewards system where users accumulate rewards by sharing messages about advertisements or purchases via social media tools such as Facebook and Twitter. Id. at paragraphs [0066]-[0067], Bryant teaches that rewards may be calculated based on reactions of other users to shared messages including their subsequent purchases. See Bryant, paragraph [0079], but it does not teach a social payment platform that provides a data feed via an API integration. Moreover, Bryant is silent with regard to generating a share code for a transaction that identifies the user and is associated with a merchant or item, posting the share code to the data feed via the API integration, or determining user activity via the API integration, which may include a use of the share code by others. Therefore, it lacks the combination of claimed elements as claimed by the independent claims.
The second most relevant prior art identified by the Examiner is/are 20130024260 “Peterson”. It teaches an e-commerce incentive program where a purchaser is encouraged to publicize on the social media websites such as Facebook and Twitter via dialogue boxes. See paragraph [0046] of Peterson. Peterson further teaches providing rewards based on the number of subsequent purchasers within a specified time period. See Peterson, paragraphs [0032]-[0033], but it is missing the feature of enables a purchaser to post information about their purchase on external third-party social media platforms. Peterson does not disclose, teach, or suggest that a social payment platform provides a data feed via an API integration to another system so that the information may be posted. Moreover, Peterson is similarly silent with regard to generating a share code, posting the share code to the data feed via the API integration, or determining user activity via the API integration. Therefore, it lacks the combination of claimed elements as claimed by the independent claims.
The third most relevant prior art found by the Examiner is 20210192496 “Gregovic”. It teaches processes for digital wallet reward optimization using machine learning models to predict reward amounts for different payment cards at checkout. See paragraphs [0019]-[0021] of Gregovic. In particular, Gregovic teaches that ML models classify transactions as capable of providing rewards, which may be used to predict reward amounts for cards in a digital wallet. Id. at paragraphs [0047]-[0058], but its missing the features of providing offers through a social payment platform via an API integration, much less share code generation and posting or API-based tracking of share code usage by other users. Therefore, it lacks the combination of claimed elements as claimed by the independent claims.
All these references listed above teaches some of the features in the limitations of the claim but when combining it becomes not obvious and the references would teach the claim as a whole.
Examiner note: none of the references or combined references teach the combination of limitations of claim 2, 22, and 30 or no reference found that would teaches the combination of limitations of claim 2, 22, and 30, especially claim limitations: provide the offer in a data feed for an account of the user, wherein the data feed is provided via a social payment platform using an application programming interface (API) integration between the system and the social payment platform, wherein the data feed enables the offer and a transaction history of the account to be shared with one or more other users and generate a share code for the transaction, wherein the share code identifies the user and is associated with at least one of an online merchant or an item associated with the transaction; post the share code to the data feed associated with the account via the API integration, wherein the data feed exposes the share code to the one or more other users via the social payment platform, and which is an idea of systems and methods for a computational platform using machine learning for integration data sharing platforms. A user may engage in a transaction with another user, such as a purchase of goods, services, or other items from a merchant. A service provider may provide a data feed to the user via integrated computational platforms that allows the user to post data including information regarding the processed transaction. The post may include a share code that links back to the user and their corresponding transaction. Thereafter, the post may be viewed by other users and the share code may be used by the other users in order to perform similar transaction processing, where these later transactions are linked back to the original user. Tracking of these later transactions may be done through application extensions that allow the computational platforms to track user data over different online interactions.
When taken as a whole, the claims are not rendered obvious as the available prior art does not suggest or otherwise render obvious the noted features nor does the available prior art suggest or otherwise render obvious further modification of the evidence at hand. Such modifications would require substantial reconstruction relying solely on improper hindsight bias, and thus would not be obvious. Therefore, the prior art rejection has been withdrawn.
NPL Reference
4. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The NPL “Predicting Customer Churn with Amazon Machine Learning” describes “Losing customers is costly for any business. Identifying unhappy customers early on gives you a chance to offer them incentives to stay. This post describes using machine learning (ML) for the automated identification of unhappy customers, also known as customer churn prediction. ML models rarely give perfect predictions though, so my post is also about how to incorporate the relative costs of prediction mistakes when determining the financial outcome of using ML. I use an example of churn that is familiar to all of us–leaving a mobile phone operator. Seems like I can always find fault with my provider du jour! And if my provider knows that I’m thinking of leaving, it can offer timely incentives–I can always use a phone upgrade or perhaps have a new feature activated–and I might just stick around. Incentives are often much more cost effective than losing and reacquiring a customer.”.
Pertinent Art
5. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Reference#20210090145 teaches similar invention which describes the user profile configuration circuit 216 is structured to enable the user to configure a user profile associated with the user's merchant offer account. For instance, the circuit 216 may enable the user to provide user-specific information regarding preferred products or services, preferred merchants, location information, user demographics, and the like. The circuit 216 may also enable the user to add the user's contacts (e.g., friends, family, etc.) to the user profile, including any gift-related dates associated with the user's contacts (e.g., anniversaries, birthdays, holidays, etc.), as well as product or service preferences for the contacts (e.g., hobbies, interests, preferred products, owned products, etc.). The circuit 216 may also enable the user to connect the user's merchant offer account to one or more social media profiles held by the user (e.g., Twitter, Facebook, Instagram, etc.), including to enable the merchant offer client application 136 (i.e., the offer computing system 102) to access the user's social media posts, feed, and contacts (e.g., friends, followers, etc.). The user may also enable the merchant offer client application 136 to post to the user's social media account(s) on behalf of the user (e.g., when a merchant offer is accepted or a product is purchased).
Response to Arguments
6. Applicant's arguments filed 06/03/2026 have been fully considered but they are not persuasive.
A. Applicant argues that the claims are not directed to a judicial exception under Step 2A Prong One. Examiner respectfully disagrees. As for Step 2A Prong One, of the Abstract idea is directed towards the abstract idea of providing offer and transaction history in a data feed and determining and providing benefit to a first user based on a second user activity associated with the offer which is grouped within the Methods Of Organizing Human Activity and is similar to the concept of (commercial or legal interactions including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors business relations) grouping of abstract ideas in prong one of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 54 (January 7, 2019)). Accordingly, the claims recite an abstract idea (See pages 7, 10, Alice Corporation Pty. Ltd. v. CLS Bank International, et al., US Supreme Court, No. 13-298, June 19, 2014; 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 53-54 (January 7, 2019)), (MPEP § 2106.04).
B. Applicant argues that the claims are not directed to a judicial exception under Step 2A Prong Two. Examiner respectfully disagrees. As for Step 2A Prong Two, the claim limitations do not include additional elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, and the claim is not more than a drafting effort designed to monopolize the judicial exception and the claim limitation simply describe the abstract idea. The limitation directed to providing offer and transaction history in a data feed and determining and providing benefit to a first user based on a second user activity associated with the offer does not add technical improvement to the abstract idea. The recitations to “system, non-transitory memory, hardware processors, system, machine, non-transitory machine-readable medium” perform(s) the steps or functions of determine an offer to extend to a user based on an interest of the user; first learning model trained for predicting offers, provide the offer in a data feed for an account of the user, wherein the data feed is provided via a social payment using an application programming interface (API) integration, wherein the data feed enables the offer and a transaction history of the account to be shared with one or more other users; detect that the user has processed a transaction associated with the offer using the account of the user; generate a share code for the transaction, wherein the share code identifies the user and is associated with at least one of an online merchant or an item associated with the transaction; post the share code to the data feed associated with the account via the API integration, wherein the data feed exposes the share code to the one or more other users via the social payment; provide an indication that the user has processed the transaction in the data feed in an association with the offer and the transaction wherein the indication is shared with the one or more other users via the data feed; determine a user activity associated with at least one of the indication, the offer, or a use of the share code by at least one of the one or more other users; determine a first benefit for the user based on the user activity and a second model trained for predicting benefits; and provide the first benefit to the account of the user. The use of a processor/computer as a tool to implement the abstract idea and/or generally linking the use of the abstract idea to a particular technological environment does not integrate the abstract idea into a practical application because it requires no more than a computer performing functions that correspond to acts required to carry out the abstract idea. The additional elements do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition (Vanda Memo), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e) and Vanda Memo). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claims are directed to an abstract idea.
C. Applicant argues that the claims are not directed to a judicial exception under Step 2B.
Examiner respectfully disagrees. As for Step 2B, The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when analyzed under step 2B of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 56 (January 7, 2019)), the limitation directed to providing offer and transaction history in a data feed and determining and providing benefit to a first user based on a second user activity associated with the offer does not add significantly more to the abstract idea. Furthermore, using well-known computer functions to execute an abstract idea does not constitute significantly more. The recitations to “system, non-transitory memory, hardware processors, system, machine, non-transitory machine-readable medium” are generically recited computer structure. These functions correspond to the actions required to perform the abstract idea. Viewed as a whole, the combination of elements recited in the claims merely recite the concept of providing offer and transaction history in a data feed and determining and providing benefit to a first user based on a second user activity associated with the offer. Therefore, the use of these additional elements does no more than employ the computer as a tool to automate and/or implement the abstract idea. The use of a computer or processor to merely automate and/or implement the abstract idea cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)). Therefore, the claim is not patent eligible.
THIS ACTION IS MADE FINAL. 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 mailing date of this final action.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TAREK ELCHANTI whose telephone number is (571) 272-9638. The examiner can normally be reached on Flex Mon - Thur 7-7:00 and Fri 7-4:00.
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/TAREK ELCHANTI/Primary Examiner, Art Unit 3621B
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