DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
2. This Office Action is in response to the initial filing of application #19/173752 on April 04, 2025.
3. Claims 1-20 are currently pending and are considered below.
Information Disclosure Statement
4. The information disclosure statement (IDS) submitted on 07/25/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
5. 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.
6. Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more. Representative claim 1, recites a method, which is a statutory class, the method is executed by a computer system or device, the method comprising:
obtaining a target audience for an advertising campaign, the target audience comprising
one or more audience identifiers;
storing the one or more audience identifiers in a privacy protection environment;
matching the one or more audience identifiers to an identity graph associated with a
targetable universe of consumers to obtain at least one advertising target;
directing at least one advertisement of the advertising campaign to be provided to the at
least one advertising target; and
obtaining impression results associated with the advertising campaign relative to the at
least one advertising target.
The steps of
obtaining a target audience for an advertising campaign, the target audience comprising
one or more audience identifiers;
storing the one or more audience identifiers in a privacy protection environment;
matching the one or more audience identifiers to an identity graph associated with a
targetable universe of consumers to obtain at least one advertising target;
directing at least one advertisement of the advertising campaign to be provided to the at
least one advertising target; and
obtaining impression results associated with the advertising campaign relative to the at
least one advertising target,
as drafted, is a process that, under its broadest reasonable interpretation, covers a method of organizing human activity. Given the broadest reasonable interpretation, the claim recites a method for matching audience for advertisement targeting. The above identified method steps recite commercial interactions such as sales activities and/or tailored personalized marketing relating to obtaining impression results associated with the advertising campaign relative to the at least one advertising target.
If a claim limitation, under its broadest reasonable interpretation, covers commercial interaction such as tailored personalized marketing, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of a privacy protection environment, data platform, computer system or device. The computer system or device is recited at a high-level of generality (i.e., as a generic processor performing a generic computer functions of
obtaining a target audience; storing the one or more audience identifiers; matching the one or more audience identifiers; directing at least one advertisement of the advertising campaign to be provided to the at least one advertising target; and obtaining impression results) such that they amount to no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of
a privacy protection environment, data platform, computer system or device amount to no more than mere instructions to apply the exception using generic computer components. The additional elements are similar to the additional elements found by courts to be mere instructions to apply an exception because they do no more than merely invoke computers or machinery to perform an existing process such as: a common business method or mathematical algorithm being applied on a general purpose computer (Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 US 208, 223; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334); providing a user with tailored information like advertisements based on information known about the user such as a location, address, or personal characteristics and a time of day is a fundamental practice long prevalent in our system); In re Morsa, 809 F. App’x 913, 917 (Fed. Cir. 2020). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Thus, considered as an ordered combination, the additional elements add nothing that is not already present when the steps are considered separately. That is, a privacy protection environment, data platform, computer system or device, performing commercial interactions including: obtaining a target audience; storing the one or more audience identifiers; matching the one or more audience identifiers; directing at least one advertisement of the advertising campaign to be provided to the at least one advertising target; and obtaining impression results, amount to mere instructions to apply the steps to a computer comprising of a processor.
Thus, claims 1 and 13 are not eligible.
As for dependent claims 2-12 and 1420, these claims recite limitations that further define the same abstract idea noted in claims 1 and 13. Therefore, they are considered patent ineligible for the reasons given above. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself.
Claims 1-20 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 102
7. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
8. 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
9. Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Schobeiri et al. (U.S. Patent No. 11,514,477) (hereinafter ‘Schobeiri’).
Claims 1 and 13: Schobeiri discloses a method and a system comprising:
obtaining a target audience for an advertising campaign, the target audience comprising one or more audience identifiers, Schobeiri teaches at circle 1, an advertiser 230 may provide a set of information to the CDN 210, and the set of information may include a deterministic identifier associated with a user (for example, user 220) and details associated with market segment membership/association or browsing/purchasing behavior/preferences of the user (for example, information regarding the particular user's preferences for products, services, or businesses, and so forth). This transmitted set of information may be collected from any suitable source, such as from first party data collected by the advertiser 230. For instance, this information can be collected from software running on the user device 225 when the user 220 utilizes the user device 225 to browse or purchase goods or services. Or, the information may have been provided and made available to the advertiser 230 by a third-party, such as from data collected by the publisher 215) (see at least Fig. 2. ref. 1; col. 12, Lines 27-36);
storing the one or more audience identifiers in a privacy protection environment, Schobeiri teaches the CDN 210 may store this received information by indexing it to the corresponding deterministic identifier (for example, store all the behavior and preferences of user 220 indexed to the user's email address) or user identity/profile associated with a user (for example, use the received deterministic identifier to look up a user identity/profile that can have many deterministic identifiers attached to it, and then store the received set of information to that user identity/profile); col. 10, I. 47-59: the CDN 110 may perform data management functions, such as performance aggregation and "clean room" data processing involving receiving log level data (e.g., bid, impressions, online events, attributed event, etc.) ; processing log level data into aggregated performance data; receiving or producing tokens/pseudonymous identifiers for use in data processing or safe delivery to a third party; delivering processed performance data and/or log level data to permission parties; and/or intaking third-party algorithms, training third-party algorithms on permissioned logs, and enabling use of the third-party algorithms for activation in real-time or on an ad hoc basis) (see at least col. 13, lines 1-9);
matching the one or more audience identifiers to an identity graph associated with a targetable universe of consumers to obtain at least one advertising target, Schobeiri teaches at circle 4, the CDN 210 may create an encrypted, electronic token for the deterministic identifier received from the publisher 215 (for example, at circle 3). The token may contain available information about segment membership/association for the user associated with the received deterministic identifier, which the CDN 210 can look-up and retrieve based on the received deterministic identifier. This token should not contain the received deterministic identifier, any other deterministic identifiers associated with the user, or any other personally identifiable information for the user. For instance, within the context of the main example, the CDN 210 may receive from the publisher 215 (for example, at circle 3) an email address for user 220 and check to see if any segment membership/association information exists for that email address or a user identity/profile associated with that email address. Either case would suffice here if the user 220 used the same email address with the advertiser 230 and the publisher 215, as the deterministic identifier received from the publisher 215 (for example, at circle 3) would match the deterministic identifier received from the advertiser 230 (for example, at circle 1) and can be used to look-up and retrieve the available segment membership/association (for example, stored at circle 1). In this case, the segment membership/association information for user 220 included in the token would indicate that the user 220 is a first party audience of advertiser 230 and has purchased brand 'X' diapers (see at least (col. 14, Lines 20-46); Furthermore, Schobeiri teaches the decision (demand) latency can be reduced if the DSP published identity graph or other user data to the CDN 410 as well. This could also enable cross-device sharing for dynamic creative optimization, user attribute/segment association sharing for site optimization, and so forth. An example scenario benefiting from reduced decision latency would be if the data within a decrypted token includes a device ID or cookie ID, and the DSP may have the opportunity to look up that ID in a device graph or identity graph to determine bid eligibility for advertisers which have enabled cross-device targeting. For example, if a decrypted token includes "cookie123", an advertiser's marketing campaign is targeting "cookie456", and the DSP has a cross-device graph which has linked "cookie123" and "cookie456", then the DSP will consider the bid opportunity eligible for the advertiser to bid on (e.g., "matched") However, this look-up process for determining bid eligibility takes time, and the latency could possibly be reduced if the device graph were stored in full/part on the CDN 410 (which could then manage the lookup) Beyond cross-device association, the DSP may have other criteria for a "matched" impression on user IDs, such as segment association. For example, an advertiser may want to target users who have shown an interest in luxury goods, "segment 789." When a bid request comes to the DSP, "segment 789" must be referenced to determine eligibility (is the user associated with the impression opportunity a match, and therefore available for bidding) .) (see at least col. 22, Lines 35-64);
directing at least one advertisement of the advertising campaign to be provided to the at least one advertising target, Schobeiri teaches the DSP 435 can determine that the user is eligible for targeting (for example, after decrypting the token including the user data) and submit a bid response back to the CDN 410) (ibid.; see at least col. 22, Lines 19-22); and
obtaining impression results associated with the advertising campaign relative to the at least one advertising target, Schobeiri teaches receiving log level data (e.g., bid, impressions, online events, attributed event, etc.) ; processing log level data into aggregated performance data; receiving or producing tokens/pseudonymous identifiers for use in data processing or safe delivery to a third party; delivering processed performance data and/or log level data to permission parties) (see at least col. 10, Lines 52-56).
Claims 2 and 14: Schobeiri discloses the method and system according to claims 1 and 13, and Schobeiri further teaches further comprising generating a scorecard based on the impression results and the target audience, Schobeiri teaches the token management system 706 may also keep track of which impression opportunity
corresponds to which token, and also which entities have received which tokens. The token management system 706 may store copies of generated tokens in the token
database 716 (see at least col.35 lines 11-20).
Claims 3: Schobeiri discloses the method and system according to claims 1 and 13, and Schobeiri further teaches wherein the target audience is obtained from an advertising entity and corresponds to an audience the advertising entity is targeting, Schobeiri teaches the CDN 110 may be an edge cloud network, such as an IoT edge cloud network, that is capable of performing edge computing (for example, performing processing at the edge of the network, close to the end-device). In some embodiments, the CDN 110 may have a cloudlet, which is a mobility-enhanced small-scale cloud datacenter that is located at the edge of the Internet. The main purpose of the cloudlet is supporting resource-intensive and interactive mobile applications by providing powerful computing resources to mobile devices with lower latency. Such configurations for the CDN 110 may utilize decreased bandwidth, reduce network load, and allow for computation offloading for real-time applications. In some embodiments, the CDN 110 may be any cloud provider with a mechanism for distributed key value transaction processing and computation at the edge (see at least col 10 lines 32-59; col12 lines 43-67).
Claims 4: Schobeiri discloses the method and system according to claims 1 and 13, and Schobeiri further teaches wherein the target audience comprises one or more target characteristics corresponding to an advertising campaign of an advertising entity, Schobeiri teaches the CDN 110 may be an edge cloud network, such as an IoT edge cloud network, that is capable of performing edge computing (for example, performing processing at the edge of the network, close to the end-device). In some embodiments, the CDN 110 may have a cloudlet, which is a mobility-enhanced small-scale cloud datacenter that is located at the edge of the Internet. The main purpose of the cloudlet is supporting resource-intensive and interactive mobile applications by providing powerful computing resources to mobile devices with lower latency. Such configurations for the CDN 110 may utilize decreased bandwidth, reduce network load, and allow for computation offloading for real-time applications. In some embodiments, the CDN 110 may be any cloud provider with a mechanism for distributed key value transaction processing and computation at the edge (see at least col 10 lines 32-59; col12 lines 43-67).
Claims 5 and 16: Schobeiri discloses the method and system according to claims 1 and 13, and Schobeiri further teaches wherein the one or more audience identifiers include one or more privacy sensitive characteristics that are used to identify individual targets in the target audience, Schobeiri teaches the CDN 110 may be an edge cloud network, such as an IoT edge cloud network, that is capable of performing edge computing (for example, performing processing at the edge of the network, close to the end-device). In some embodiments, the CDN 110 may have a cloudlet, which is a mobility-enhanced small-scale cloud datacenter that is located at the edge of the Internet. The main purpose of the cloudlet is supporting resource-intensive and interactive mobile applications by providing powerful computing resources to mobile devices with lower latency. Such configurations for the CDN 110 may utilize decreased bandwidth, reduce network load, and allow for computation offloading for real-time applications. In some embodiments, the CDN 110 may be any cloud provider with a mechanism for distributed key value transaction processing and computation at the edge (see at least col 10 lines 32-59; col12 lines 43-67).
Claims 6 and 17: Schobeiri discloses the method and system according to claims 1 and 13, and Schobeiri further teaches wherein the privacy protection environment is a cleanroom, Schobeiri teaches there may be various functions that are entrusted to the one or more CDN vendors 160 to perform on behalf of the CDN 110 as a translation layer between the CDN 110 and the participants of the real-time bidding process or as a third party facilitator of the real-time bidding process. For instance, the CDN 110 may utilize the one or more CDN vendors 160 to manage one or more databases and perform identity and access management functionality (e.g., identity translation or identity escrow) for the participants of the real-time bidding process. The CDN 110 may also utilize the one or more CDN vendors 160 to manage performance aggregation functionality ( e.g., "clean room" data processing) (see at least col. 11 line 44 through col. 12 line 13).
Claims 7 and 18: Schobeiri discloses the method and system according to claims 6 and 17, and Schobeiri further teaches wherein the cleanroom comprises an approval from a data accessor and an approval from a data provider, and the cleanroom is monitored by a data platform, Schobeiri teaches there may be various functions that are entrusted to the one or more CDN vendors 160 to perform on behalf of the CDN 110 as a translation layer between the CDN 110 and the participants of the real-time bidding process or as a third party facilitator of the real-time bidding process. For instance, the CDN 110 may utilize the one or more CDN vendors 160 to manage one or more databases and perform identity and access management functionality (e.g., identity translation or identity escrow) for the participants of the real-time bidding process. The CDN 110 may also utilize the one or more CDN vendors 160 to manage performance aggregation functionality ( e.g., "clean room" data processing) (see at least col. 11 line 44 through col. 12 line 13).
Claims 8 and 18: Schobeiri discloses the method and system according to claims 6 and 17, and Schobeiri further teaches wherein the cleanroom is configured to output aggregated data, Schobeiri teaches there may be various functions that are entrusted to the one or more CDN vendors 160 to perform on behalf of the CDN 110 as a translation layer between the CDN 110 and the participants of the real-time bidding process or as a third party facilitator of the real-time bidding process. For instance, the CDN 110 may utilize the one or more CDN vendors 160 to manage one or more databases and perform identity and access management functionality (e.g., identity translation or identity escrow) for the participants of the real-time bidding process. The CDN 110 may also utilize the one or more CDN vendors 160 to manage performance aggregation functionality ( e.g., "clean room" data processing) (see at least col. 11 line 44 through col. 12 line 13).
Claim 9: Schobeiri discloses the method and system according to claims 1 and 13, and Schobeiri further teaches wherein the privacy protection environment comprises a
contractual agreement between a data accessor, a data provider, and a data platform, Schobeiri teaches there may be various functions that are entrusted to the one or more CDN vendors 160 to perform on behalf of the CDN 110 as a translation layer between the CDN 110 and the participants of the real-time bidding process or as a third party facilitator of the real-time bidding process. For instance, the CDN 110 may utilize the one or more CDN vendors 160 to manage one or more databases and perform identity and access management functionality (e.g., identity translation or identity escrow) for the participants of the real-time bidding process. The CDN 110 may also utilize the one or more CDN vendors 160 to manage performance aggregation functionality ( e.g., "clean room" data processing) (see at least col. 11 line 44 through col. 12 line 13).
Claim 10: Schobeiri discloses the method according to claims 9, and Schobeiri further teaches wherein the data platform comprises multi-layer redundancies to reduce a likelihood of leakage of the one or more audience identifiers, Schobeiri teaches performing user PII to match in database (see at least Figure 9B).
Claims 11 and 19: Schobeiri discloses the method and system according to claims 1 and 13, and Schobeiri further teaches wherein the identity graph comprises one or more characteristics individually associated with consumers in the targetable universe of consumers and a corresponding consumer identifier, Schobeiri teaches performing user PII to match in database (see at least Figure 9B).
Claims 12 and 20: Schobeiri discloses the method and system according to claims 1 and 13, and Schobeiri further teaches wherein a match between the one or more audience identifiers and the identity graph comprises identifying a number of matching characteristics to satisfy a threshold number of matched characteristics, Schobeiri teaches performing user PII to match in database (see at least Figure 9B).
Claim 15: Schobeiri discloses the system according to claims 13, and Schobeiri further teaches wherein the target audience:
is obtained from an advertising entity, Schobeiri teaches the CDN 110 may be an edge cloud network, such as an IoT edge cloud network, that is capable of performing edge computing (for example, performing processing at the edge of the network, close to the end-device). In some embodiments, the CDN 110 may have a cloudlet, which is a mobility-enhanced small-scale cloud datacenter that is located at the edge of the Internet. The main purpose of the cloudlet is supporting resource-intensive and interactive mobile applications by providing powerful computing resources to mobile devices with lower latency. Such configurations for the CDN 110 may utilize decreased bandwidth, reduce network load, and allow for computation offloading for real-time applications. In some embodiments, the CDN 110 may be any cloud provider with a mechanism for distributed key value transaction processing and computation at the edge (see at least col 10 lines 32-59; col12 lines 43-67);
corresponds to an audience the advertising entity is targeting, Schobeiri teaches the CDN 110 may be an edge cloud network, such as an IoT edge cloud network, that is capable of performing edge computing (for example, performing processing at the edge of the network, close to the end-device). In some embodiments, the CDN 110 may have a cloudlet, which is a mobility-enhanced small-scale cloud datacenter that is located at the edge of the Internet. The main purpose of the cloudlet is supporting resource-intensive and interactive mobile applications by providing powerful computing resources to mobile devices with lower latency. Such configurations for the CDN 110 may utilize decreased bandwidth, reduce network load, and allow for computation offloading for real-time applications. In some embodiments, the CDN 110 may be any cloud provider with a mechanism for distributed key value transaction processing and computation at the edge (see at least col 10 lines 32-59; col12 lines 43-67); and
comprises one or more target characteristics corresponding to an advertising campaign of an advertising entity, Schobeiri teaches the CDN 110 may be an edge cloud network, such as an IoT edge cloud network, that is capable of performing edge computing (for example, performing processing at the edge of the network, close to the end-device). In some embodiments, the CDN 110 may have a cloudlet, which is a mobility-enhanced small-scale cloud datacenter that is located at the edge of the Internet. The main purpose of the cloudlet is supporting resource-intensive and interactive mobile applications by providing powerful computing resources to mobile devices with lower latency. Such configurations for the CDN 110 may utilize decreased bandwidth, reduce network load, and allow for computation offloading for real-time applications. In some embodiments, the CDN 110 may be any cloud provider with a mechanism for distributed key value transaction processing and computation at the edge (see at least col 10 lines 32-59; col12 lines 43-67).
Conclusion
10. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
11. Randazzo et al. (U.S. Patent No. 10,181136) discloses conventional segmentation techniques may also cause privacy and security concerns. For example, it is common for conventional systems to identify consumers using identifiers or information that includes personal identifiable information (e.g., name, email address, phone number or the like). It is also common for conventional systems to exchange these identifiers over communication networks. This can lead to data leaks or losses that can potential expose personal identifiable information of the consumers to attackers or other unauthorized users. Furthermore, attackers (e.g., hackers) can use the personal identifiable information obtained from one attack against the same or additional consumers in subsequent attacks (e.g., using techniques such as phishing, social engineering or the like) (see at least paragraph (4).
12. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARILYN G MACASIANO whose telephone number is (571)270-5205. The examiner can normally be reached Monday-Friday 12:00-9:00 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, llana Spar can be reached at 571)270-7537. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MARILYN G MACASIANO/Primary Examiner, Art Unit 3622 06/13/2026
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