DETAILED ACTION
Status of the Claims
This office action is submitted in response to the application filed on 4/16/25.
Examiner notes that this application is a continuation of 18674867 (now US Patent No. 12307481), 18225135 (now US Patent No. 12026742), 17590880 (now US Patent No. 11756073), and provisional application 63228050.
Examiner further notes Applicant’s priority date of 7/31/21, which stems from the aforementioned parent applications.
Examiner further notes Applicant’s IDS submissions on 4/16/25, 8/27/25, 11/10/25, 2/1/26, 4/6/26, and 5/18/26.
Claims 1-20 are currently pending and have been examined.
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 .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1–20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1–20 of U.S. Patent No. 12,307,481 B2 (hereinafter "'481 patent"). Although the claims at issue are not identical, they are not patentably distinct from each other.
Regarding instant claim 1 and '481 patent claim 1: The instant claim 1 recites a computer-implemented method of analyzing a success of an electronic message campaign by sensing actions of recipients via at least one sensor, determining a level of engagement, electronically sending a present campaign to recipients of an active contact list, and controlling visual content based on engagement level. '481 patent claim 1 recites the same core method — analyzing campaign success by sensing actions via at least one sensor, determining a success score and level of engagement, sending a present campaign to recipients of an adaptively adjusted active contact list, and controlling visual content based on engagement level — but additionally requires obtaining an initial contact list, checking the initial contact list against engagement rules, generating an active contact list by modifying the initial contact list, adaptively adjusting the active contact list by eliminating non-engaged recipients based on the success score, identifying engaged recipients over a predetermined period of time, and adjusting the predetermined period of time based on evaluated success. Instant claim 1 is therefore a broader version of '481 patent claim 1 that omits the contact list management, adaptive adjustment, and time period adjustment limitations. Since the instant claim is an obvious broadening that merely omits limitations from the patented claim, instant claim 1 is not patentably distinct from '481 patent claim 1. See In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993) (claims in a later application that are broader than claims in an earlier patent are not patentably distinct).
Regarding instant claims 2 and 3: The additional limitations of instant claims 2 and 3 — obtaining an initial contact list, checking engagement rules, generating an active contact list, sending to the active contact list (claim 2), and determining a success score, adaptively adjusting by eliminating non-engaged recipients, identifying engaged recipients over a predetermined period, and adjusting the predetermined period (claim 3) — are recited in '481 patent claim 1. Therefore, instant claims 1+2+3 taken together correspond to '481 patent claim 1, further confirming that instant claim 1 alone is an obvious broadening of the patented claim.
Regarding instant claim 19 and '481 patent claim 17: Instant claim 19 recites a system that mirrors the method of instant claim 1. '481 patent claim 17 recites a system that mirrors '481 patent claim 1. The same analysis applies. Instant claim 19 is a broader version of '481 patent claim 17, and is not patentably distinct therefrom.
Regarding instant claim 20: Instant claim 20 depends from instant claim 19 and recites the combined limitations of instant claims 2 and 3. These limitations correspond to the contact list management, adaptive adjustment, and time period adjustment limitations recited in '481 patent claim 17. Therefore, instant claim 20 is not patentably distinct from '481 patent claim 17.
Regarding instant claims 4–18: The additional limitations of instant claims 4–18 correspond to limitations recited in the dependent claims of the '481 patent as follows:
Instant claim 4 (location/motion sensors, engagement based on location/motion) corresponds to '481 patent claim 2.
Instant claim 5 (device-to-device interaction, influence-based visual content control) corresponds to '481 patent claim 3.
Instant claim 6 (location visit patterns, engagement based on patterns) corresponds to '481 patent claim 4.
Instant claim 7 (web activity sensing, engagement based on web activity) corresponds to '481 patent claim 5.
Instant claim 8 (plurality of predetermined periods with different qualifications) corresponds to '481 patent claim 6.
Instant claim 9 (hand motions, eyesight, orientations indicating product interaction) corresponds to '481 patent claim 7.
Instant claim 10 (bidirectional time period adjustment based on success) corresponds to '481 patent claim 8.
Instant claim 11 (active contact list updates every send) corresponds to '481 patent claim 9.
Instant claims 12–13 (volume threshold, reducing below threshold) correspond to '481 patent claims 10–11.
Instant claims 14–15 (unengaged recipient identification, percentage threshold elimination) correspond to '481 patent claims 12–13.
Instant claim 16 (open rate) corresponds to '481 patent claim 14.
Instant claim 17 (click-through rate) corresponds to '481 patent claim 15.
Instant claim 18 (conversion rate) corresponds to '481 patent claim 16.
Accordingly, instant claims 4–18 are not patentably distinct from the corresponding claims of the '481 patent.
Claims 1–20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1–20 of U.S. Patent No. 12,026,742 B2 (hereinafter "'742 patent"). Although the claims at issue are not identical, they are not patentably distinct from each other.
Regarding instant claim 1 and '742 patent claim 1: The '742 patent claim 1 recites the same core method as instant claim 1 — analyzing campaign success by sensing recipient actions, determining engagement level, sending a present campaign, and controlling visual content based on engagement — but additionally requires: (a) the sensor to be specifically a "location sensor and motion sensors" rather than the instant claim's generic "at least one sensor"; and (b) the contact list management, adaptive adjustment, and time period adjustment limitations that are absent from instant claim 1 but present in instant claims 2 and 3. Instant claim 1 is therefore a broader version of '742 patent claim 1 that both broadens the sensor requirement and omits the contact list management limitations. Since the instant claim is an obvious broadening of the patented claim, instant claim 1 is not patentably distinct from '742 patent claim 1.
Regarding instant claim 19 and '742 patent claim 17: The same analysis applies. Instant claim 19 is a broader version of '742 patent claim 17, and is not patentably distinct therefrom.
Regarding instant claims 2–3, 20: The contact list management limitations of instant claims 2–3 (and claim 20, which incorporates claims 2–3) are recited in '742 patent claim 1/17, further confirming the obvious broadening relationship.
Regarding instant claims 4–18: The additional limitations of instant claims 4–18 correspond to limitations recited in the dependent claims of the '742 patent as follows:
Instant claim 4 (location/motion sensors) is anticipated by '742 patent claim 1, which requires location and motion sensors in its independent claim.
Instant claim 5 (device-to-device interaction, influence) corresponds to '742 patent claim 2.
Instant claim 6 (location visit patterns) corresponds to '742 patent claim 3.
Instant claim 7 (web activity) corresponds to '742 patent claim 4.
Instant claim 8 (plurality of predetermined periods) corresponds to '742 patent claim 5.
Instant claim 9 (hand motions, orientations, product interaction) corresponds to '742 patent claim 6.
Instant claim 10 (bidirectional time period adjustment) corresponds to '742 patent claim 7.
Instant claim 11 (updates every send) corresponds to '742 patent claim 8.
Instant claims 12–13 (volume threshold) correspond to '742 patent claims 10–11.
Instant claims 14–15 (unengaged identification, percentage threshold) correspond to '742 patent claims 12–13.
Instant claim 16 (open rate) corresponds to '742 patent claim 14.
Instant claim 17 (click-through rate) corresponds to '742 patent claim 15.
Instant claim 18 (conversion rate) corresponds to '742 patent claim 16.
Accordingly, instant claims 2–20 are not patentably distinct from the corresponding claims of the '742 patent.
Claims 1–20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1–19 of U.S. Patent No. 11,756,073 B2 (hereinafter "'073 patent"). Although the claims at issue are not identical, they are not patentably distinct from each other.
Regarding instant claim 1 and '073 patent claim 1: '073 patent claim 1 is the narrowest independent claim in the patent family. It recites the same core method as instant claim 1 — analyzing campaign success, determining engagement, sending a present campaign, and controlling visual content — but additionally requires: (a) "location sensor and motion sensors" rather than the instant claim's generic "at least one sensor"; (b) the contact list management, adaptive adjustment, and time period adjustment limitations (present in instant claims 2–3); (c) identifying patterns of location visits (present in instant claim 6); (d) determining device-to-device interaction and influence (present in instant claim 5); and (e) controlling visual content based on both engagement level and influence (present in instant claim 5). Instant claim 1 is therefore a substantially broader version of '073 patent claim 1 that omits multiple limitations. Since the instant claim is an obvious broadening of the patented claim, instant claim 1 is not patentably distinct from '073 patent claim 1.
Regarding instant claim 19 and '073 patent claim 17: The same analysis applies. Instant claim 19 is a broader version of '073 patent claim 17, and is not patentably distinct therefrom.
Regarding instant claims 2–6, 20: The contact list management (claims 2–3), device-to-device interaction and influence (claim 5), and location visit patterns (claim 6) limitations are all recited in '073 patent claim 1, further confirming the obvious broadening relationship. Claim 20 incorporates claims 2–3 and is likewise not patentably distinct.
Regarding instant claims 4, 7–18: The additional limitations of instant claims 4 and 7–18 correspond to limitations recited in the claims of the '073 patent as follows:
Instant claim 4 (location/motion sensors) is anticipated by '073 patent claim 1, which requires location and motion sensors in its independent claim.
Instant claim 7 (web activity) corresponds to '073 patent claim 2.
Instant claim 8 (plurality of predetermined periods) corresponds to '073 patent claim 3.
Instant claim 9 (hand motions, orientations, product interaction) corresponds to '073 patent claim 4.
Instant claim 10 (bidirectional time period adjustment) corresponds to '073 patent claim 5.
Instant claim 11 (updates every send) corresponds to '073 patent claim 6.
Instant claims 12–13 (volume threshold) correspond to '073 patent claims 8–9.
Instant claims 14–15 (unengaged identification, percentage threshold) correspond to '073 patent claims 10–11.
Instant claim 16 (open rate) corresponds to '073 patent claim 12.
Instant claim 17 (click-through rate) corresponds to '073 patent claim 13.
Instant claim 18 (conversion rate) corresponds to '073 patent claim 14.
Accordingly, instant claims 2–20 are not patentably distinct from the corresponding claims of the '073 patent.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1–20 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.
Step 1: Claims 1–20 are directed to patent-eligible subject matter categories under 35 U.S.C. § 101. Specifically, claim 1 recites a computer-implemented method, and thus falls within the "process" category. Claim 19 recites a system comprising a server electronically networked with computing devices, and thus falls within the "machine" category. Claims 2–18 depend from claim 1, and thus likewise fall within the "process" category. Claim 20 depends from claim 19, and thus likewise falls within the "machine" category. Accordingly, the claims satisfy Step 1. See MPEP § 2106.03.
Step 2A, Prong One: Independent claims 1 and 19, in part, describe an invention comprising: analyzing a success of an electronic message campaign by sensing actions of the recipients in response to receiving electronic messages; identifying and tracking sensed actions of the user; determining a level of engagement of the recipient based on the tracked sensed actions; and providing message based on the level of engagement of the recipient. As such, the invention is directed to the abstract idea of collecting and analyzing recipient engagement data to determine engagement levels and determine the content of campaign messages accordingly, which, pursuant to MPEP § 2106.04(a)(2), is aptly categorized as a method of organizing human activity (managing commercial interactions between marketers and campaign recipients, including advertising and marketing activities and behaviors). Therefore, under Step 2A, Prong One, the claims recite a judicial exception.
Next, the aforementioned claims recite additional elements that are associated with the judicial exception, including: receiving electronic messages and electronically sending electronic message campaigns to recipients. The Examiner understands these limitations to be insignificant extra-solution activity. See Accenture Global Servs., GmbH v. Guidewire Software, Inc., 728 F.3d 1336, 108 U.S.P.Q.2d 1173 (Fed. Cir. 2013), citing Cf. Diamond v. Diehr, 450 U.S. 175, 191–192 (1981) ("[I]nsignificant post-solution activity will not transform an unpatentable principle into a patentable process.").
The aforementioned claims also recite additional elements including: a server electronically networked with a plurality of computing devices of a plurality of recipients (claim 19); computing devices of recipients; an application loaded on the computing device; at least one sensor of the computing device (which under the broadest reasonable interpretation encompasses a touchscreen or other generic input sensor); and a campaign success engine. These limitations are recited at a high level of generality and appear to be nothing more than generic computer components used to apply the abstract idea.
The aforementioned claims further recite an application loaded on the computing device controlling sensing of at least one sensor of the computing device based on reception of the electronic message. This limitation amounts to an instruction to use the generic sensor hardware identified above to gather data for the abstract idea — i.e., it is an "apply it" limitation. See MPEP § 2106.05(f). Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 223 (2014), 110 USPQ2d 1977, 1983 (2014).
Step 2A, Prong Two: Looking at the elements individually and in combination, the claims as a whole do not integrate the judicial exception into a practical application because they fail to: improve the functioning of a computer or a technical field; apply the judicial exception in the treatment or prophylaxis of a disease; apply the judicial exception with a particular machine; effect a transformation or reduction of a particular article to a different state or thing; or apply the judicial exception beyond generally linking the use of the judicial exception to a particular technological environment. Rather, the claims merely use a computer as a tool to perform the abstract idea, and/or add insignificant extra-solution activity to the judicial exception, and/or generally link the use of the judicial exception to a particular technological environment (e.g., generic computing devices and servers connected to a network for distributing electronic messages). Accordingly, the claims do not integrate the judicial exception into a practical application, and the analysis proceeds to Step 2B.
Step 2B: The claims do not include additional elements sufficient to amount to significantly more than the judicial exception. The additional elements, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea itself. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or any other technology, and their collective functions are merely facilitated by generic computer implementation.
Additionally, pursuant to the requirement under Berkheimer v. HP Inc., 881 F.3d 1360, 125 USPQ2d 1649 (Fed. Cir. 2018), the following citations are provided to demonstrate that the additional elements, identified above, are well-understood, routine, and conventional. See MPEP § 2106.05(d).
Receiving or transmitting data over a network. Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362; OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015).
Thus, taken alone and in combination, the additional elements do not amount to significantly more than the above-identified judicial exception, and claims 1–20 are ineligible under 35 U.S.C. § 101.
Next, claims 2–18 depend from claim 1 and include all limitations contained therein, and claim 20 depends from claim 19 and includes all limitations contained therein. These claims do not recite any additional elements sufficient to transform the abstract idea into patent-eligible subject matter. Specifically:
Claims 2 and 20 further limit the method to obtaining an initial contact list, checking the initial contact list against engagement rules, generating an active contact list by modifying the initial contact list, and electronically sending the campaign to the active contact list. These limitations describe additional steps of managing and curating a contact list based on engagement criteria and transmitting campaign messages — amounting to further refinements of the abstract commercial activity of managing a targeted marketing campaign and additional insignificant extra-solution activity (transmitting data), without meaningfully limiting the abstract idea. Claim 20 further includes the limitations of claim 3 discussed below.
Claim 3 further limits the method to determining a success score, adaptively adjusting the active contact list by eliminating non-engaged recipients based on the success score, identifying engaged recipients over a predetermined period of time, and adjusting the predetermined period of time based on evaluated success. These limitations specify scoring, filtering, and time-period adjustment rules that further define the contours of the data analysis process without adding significantly more than the abstract idea.
Claims 4 and 9 further limit the method to sensing location and motion of the computing device via location and motion sensors (claim 4), and sensing hand motions and device orientations indicating product interaction (claim 9), and using those sensed inputs to further determine engagement. The location sensors, motion sensors, accelerometer, gyroscope, and compass referenced in these claims are generic sensor hardware found on commercially available mobile devices. These limitations serve only as additional data-gathering inputs to the engagement determination — the core of the abstract idea — and do not recite any improvement to computer functionality or any other technical advance beyond the abstract idea itself.
Claim 5 further limits the method to determining whether devices of recipients interact with one another based on sensed location and motion, and using the resulting influence data to control visual content. These limitations describe additional data analysis steps that further define the abstract commercial activity of engagement-based content targeting, without meaningfully limiting the abstract idea.
Claim 6 further limits the method to identifying patterns of location visits and using those patterns to further determine engagement. These limitations describe additional data collection and analysis that further define the abstract commercial activity without adding significantly more.
Claim 7 further limits the method to sensing web activity of recipients and using the sensed web activity to further determine engagement. Tracking web activity such as browsing, clicking, and purchasing is a well-known data collection technique in the field of digital marketing that does not confer patent eligibility.
Claim 8 further limits the method to using a plurality of predetermined periods of time with different engagement qualification criteria. Using multiple time periods with different qualification criteria is a further specification of the business rules governing the engagement determination process, without adding significantly more.
Claim 10 further limits the method to bidirectional adjustment of the predetermined period of time based on campaign success. This is a further specification of the business rules governing the campaign management process, without adding significantly more.
Claim 11 further limits the method to updating the active contact list as frequently as every campaign send. This is a further specification of the timing of the list management process, without adding significantly more.
Claims 12–13 further limit the method to comparing a recipient count against a numerical threshold (claim 12) and reducing the count below that threshold (claim 13). These are well-known data comparison and list management techniques that do not add significantly more than the abstract idea.
Claims 14–15 further limit the method to identifying unengaged recipients, comparing recipient counts (claim 14), applying a percentage threshold, and eliminating recipients exceeding that threshold (claim 15). These limitations describe well-known business rule and data analysis techniques used in marketing list management, without adding significantly more.
Claims 16–18 further limit the level of engagement to specific metrics — namely, an open rate (claim 16), a click-through rate (claim 17), and a conversion rate (claim 18). Open rate, click-through rate, and conversion rate are well-known engagement metrics used in the field of email marketing. Specifying a particular metric for the engagement determination does not recite any improvement to computer functionality or any other technical advance beyond the abstract idea itself.
Therefore, claims 1–20 are not drawn to eligible subject matter, as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1–3, 7–8, 10–20 are rejected under 35 U.S.C. 103 as being unpatentable over Pisupati et al. (US 11,488,204 B2) in view of Ramakrishnan et al. (US 9,608,942 B1).
Claims 1 and 19: Pisupati discloses a computer-implemented method and a system, comprising:
a server electronically networked with a plurality of computing devices of a plurality of recipients of an electronic mail campaign (col. 5, ll. 23–47; FIG. 1. Pisupati's campaign platform 110 communicates via the Internet, cellular communication, or other suitable methods with a plurality of recipient computing devices 120a–n, which include smartphones, tablets, laptops, and desktop computers, to distribute marketing campaign messages to a plurality of intended recipients.);
analyzing a success of an electronic message campaign, comprising sensing actions of the recipients in response to electronically receiving electronic messages of the electronic message campaign (col. 6, ll. 56–67; col. 7, ll. 1–25; FIG. 2, steps 210–230. Pisupati's campaign platform 110 monitors the campaigns sent to each intended recipient and the intended recipients' engagement with those campaigns by tracking whether each recipient opened the campaign message, clicked a link in the message, or otherwise interacted with it, thereby sensing actions of the recipients in response to receiving the electronic messages.);
wherein analyzing the success comprises: a computing device of one or more of the recipients receiving an electronic message (col. 5, ll. 41–47; col. 6, ll. 23–31; FIG. 1. Pisupati's recipient computing devices 120a–n receive campaign messages sent by the campaign platform 110.);
an application loaded on the computing device controlling sensing of at least one sensor of the computing device based on reception of the electronic message (col. 5, ll. 41–47; col. 7, ll. 1–12. Pisupati teaches that recipient computing devices 120a–n — including smartphones and tablets — receive campaign messages, and that the recipient's email system tracks whether the recipient opened the message and clicked links within the message, transmitting indications of those interactions back to the campaign platform 110. Under the broadest reasonable interpretation, such tracked user interactions — opens and clicks — are sensed via an input sensor of the computing device, such as a touchscreen, mouse, or trackpad, and the client application necessarily processes those sensor inputs to identify the interactions based on reception of the electronic message.);
the application loaded on the computing device identifying and tracking sensed actions of the computing device (col. 7, ll. 1–12. Pisupati teaches that the recipient's email system tracks the recipient's interactions with the campaign message — specifically, whether the email was opened, which is indicated by a read receipt or other indication transmitted back to the campaign platform 110, and whether the recipient clicked a link in the message. Under the broadest reasonable interpretation, it would have been understood by one of ordinary skill in the art that these tracked open and click interactions are identified by the client application processing input-sensor events on the computing device, and the resulting interaction data constitutes tracked sensed actions.);
determining, by a campaign success engine, a level of engagement of the recipient based on the tracked sensed actions (col. 7, ll. 27–67; col. 8, ll. 1–12; FIG. 2, steps 220–230; FIG. 3. Pisupati's campaign platform 110 determines, for each intended recipient, a recency value (the number of days since the recipient last opened a campaign message) and a frequency value (the number of times the recipient has opened campaigns in a predetermined period of observation). Based on these values and the tracked response rate over consecutive periods, the campaign platform 110 determines a fatigue status — undersaturated, unsaturated, or saturated — for each recipient, which constitutes a level of engagement. The campaign platform 110 further performs a sub-segmentation process that ranks saturated recipients from most fatigued to least fatigued, producing a granular engagement determination.); and
electronically sending a present electronic message campaign to recipients of an active contact list (col. 6, ll. 23–31; col. 8, ll. 50–58; FIG. 1; FIG. 2, step 240. Pisupati's campaign platform 110 maintains a list of recipients 113 and sends campaign messages to the intended recipients on that list. The list is dynamically managed: recipients in a "normal" state are kept in the list and receive campaigns, while fatigued recipients are removed from the list during the rest state and added back during the safe state, making the list an active contact list that is adjusted based on engagement evaluation.).
Pisupati does not appear to explicitly disclose controlling a visual content of displays of computing devices of each of the recipients of the present electronic message based on the level of engagement of the recipient.
Ramakrishnan, however, discloses controlling a visual content of displays of computing devices of each of the recipients of the present electronic message based on the level of engagement of the recipient (col. 6, ll. 20–50; col. 7, ll. 1–20; col. 11, ll. 20–40; FIGS. 1A–1B; FIG. 2, steps 40–45. Ramakrishnan teaches generating personalized email content pieces customized in accord with individual recipient behaviors. In a data collection phase, the system collects a history of actual responses to calls to action in prior email campaigns, identifying which recipients opened emails and which recipients clicked on content pieces within those emails. In a feature engineering phase, the system extracts features characterizing both the digital content piece — including visual features such as black-and-white vs. color image, size of image, presence of model, image resolution, and above-or-below-the-fold placement — and the recipient's prior engagement behavior — including whether the recipient previously clicked through a product category in email, previously purchased a product, or previously browsed a product. In an email campaign phase, the system uses the resulting model to generate and transmit to each recipient a digital content piece having visual features selected to maximize the probability that the particular recipient will respond to the call to action, based on that recipient's engagement history. At least two recipients receive content pieces that differ from one another, because the model incorporates recipient-specific engagement characteristics. Thus, the visual content displayed on each recipient's computing device is controlled based on the recipient's level of engagement with prior campaigns.)
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Pisupati's campaign platform to incorporate Ramakrishnan's engagement-based personalization of email content so that the visual content of campaign messages sent to recipients on the active contact list is customized for each recipient based on their determined level of engagement. One would have been motivated to do so in order to maximize the probability that each recipient will respond to the campaign, because Ramakrishnan teaches that personalizing email content features based on a recipient's prior engagement behavior (rather than sending the same content to all recipients) predictably yields higher click-through rates and improved campaign effectiveness (Ramakrishnan, col. 1, ll. 15–30; col. 5, ll. 5–50).
Claim 2: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses obtaining, by a server, an initial contact list (col. 5, ll. 51–67; col. 6, ll. 23–31; FIG. 1. Pisupati's campaign platform 110 includes a profile database 111 storing a plurality of intended recipient profiles 112a–n, and a list of recipients 113 comprising the intended recipients to receive campaign messages.);
checking, by the server, the initial contact list to determine that the initial contact list satisfies an initial set of engagement rules (col. 7, ll. 27–67; FIG. 2, steps 210–230; FIG. 3. Pisupati's campaign platform 110 monitors sent campaigns and engagement, determines recency and frequency values for each recipient, and determines a fatigue status for each intended recipient profile based on those values, thereby checking whether the contact list satisfies engagement rules.);
generating, by the server, the active contact list comprising modifying the initial contact list when the initial contact list does not satisfy the initial set of engagement rules (col. 8, ll. 60–67; col. 9, ll. 1–19; FIG. 2, steps 250–260. When the campaign platform 110 determines that intended recipient profiles have a "saturated" fatigue status, it performs sub-segmentation, identifies the most send-fatigued recipients, and removes them from the recipients list 113 by transitioning their state attribute to "rest," thereby generating a modified active contact list.); and
electronically sending, by the server, the electronic message campaign to recipients of the active contact list (col. 8, ll. 50–58; FIG. 2, step 240. Pisupati's campaign platform 110 sends campaign messages to the intended recipients remaining on the recipients list 113 — i.e., those in the "normal" state.).
Claim 3: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses determining, by a campaign success engine, a success score of the electronic messages based on the tracked sensed actions (col. 9, ll. 5–12; FIG. 4. Pisupati's campaign platform 110 calculates a fatigue score for each saturated recipient based on (1) a degree of reduction in the engagement rate, (2) the degree of increase in sends delivered, and (3) the degree to which send volume caused the reduction in engagement. This fatigue score constitutes a success score determined from the tracked recipient actions.);
adaptively adjusting, by the server, the active contact list according to active engagement rules of based on an evaluated success of the electronically sent campaign comprising reducing a number of recipients of the active contact list by eliminating non-engaged recipients based on the determined success score of the electronic messages of the electronically sent campaign (col. 9, ll. 5–19; FIG. 2, steps 250–260; FIG. 5. Pisupati's campaign platform 110 ranks the saturated recipients from most fatigued to least fatigued based on the fatigue score, partitions the ranked list at breakpoints to form sub-segments, and removes the most-fatigued recipients in the top sub-segments from the recipients list 113 by setting their state to "rest," thereby eliminating non-engaged recipients and reducing the number of recipients on the active contact list.);
identifying engaged recipients of the electronic message campaign of the active contact list over a predetermined period of time by the active engagement rules (col. 7, ll. 27–40; FIG. 3. Pisupati's campaign platform 110 uses a predetermined period of observation — such as the previous 60 days or 30 days — to determine frequency values and engagement rates, and identifies recipients whose fatigue status is "unsaturated" as engaged recipients over that period.); and
adaptively adjusting the active contact list according to active engagement rules based on an evaluated success of the electronically sent campaign comprising adjusting the predetermined period of time based on the evaluated success of the electronically sent campaign (col. 10, ll. 24–43; FIG. 6. When a recipient "relapses" — i.e., the campaign platform 110 determines the recipient remains saturated after the safe state — the time spent in the rest state is increased according to the function f(n) = 7 + (n+1)², where n is the number of relapses. This constitutes an adaptive adjustment of the predetermined time period based on the evaluated success of the campaign, because the duration of exclusion from the active contact list increases when engagement remains poor.).
Claim 7: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Ramakrishnan further discloses sensing, by the application loaded on the computing device, web activity of the one or more recipients; wherein the level of engagement of the recipient is further based on the sense web activity (col. 7, ll. 1–20. Ramakrishnan teaches that recipient features used to characterize engagement include whether the recipient browsed a product in the past 7 days, visited a website, clicked through a product category in email, added a product to an ecommerce shopping cart, or purchased a product online. Each of these web activities is tracked and used as an input feature to the click-prediction model that determines engagement level.).
The rationale for combining Pisupati and Ramakrishnan is articulated above and is reincorporated herein by reference.
Claim 8: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses a plurality of predetermined periods of time, wherein qualification of whether a recipient is an engaged recipient is different for different of the predetermined periods of time (col. 7, ll. 27–67; FIG. 3. Pisupati teaches that the campaign platform 110 uses multiple time-based parameters to evaluate engagement: a "period of observation" (e.g., 60 days or 30 days) for determining the frequency value, a separate "predetermined time frame" (e.g., the last month) for determining whether the recipient has opened any campaigns, and a "consecutive period of time" (e.g., a certain number of consecutive days) for detecting decreased engagement. The qualification criteria differ across these periods: the frequency value measures the count of opens over the period of observation, while the recency determination measures whether any campaign was opened within the predetermined time frame, and the engagement trend analysis measures a decrease in response rate over the consecutive period.).
Claim 10: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses wherein the predetermined period of time increases when the evaluated success indicates the electronically sent campaign is determined to be successful, and wherein the predetermined period of time decreases when the evaluated success indicates the electronically sent campaign is determined to be unsuccessful (col. 10, ll. 24–43; FIG. 6. Pisupati teaches that when a recipient "relapses" — i.e., the campaign platform 110 determines the recipient's engagement remains at the "saturated" level after the safe state period — the rest state duration increases according to f(n) = 7 + (n+1)², resulting in progressively longer exclusion periods for recipients exhibiting continued poor engagement. Pisupati also teaches that when the campaign platform 110 determines during the safe state that engagement has improved sufficiently, the recipient transitions to the "normal" state and the standard evaluation period resumes. Under the broadest reasonable interpretation, the bidirectional adjustment of time periods based on evaluated campaign success — expanding the engagement window when results are favorable, and contracting it when results are unfavorable — is reasonably encompassed by Pisupati's disclosed mechanism of lengthening exclusion for poor results and returning to standard evaluation for improved results.).
Claim 11: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses wherein the active contact list adaptively updates as frequently as every time the electronic message campaign is electronically sent (col. 6, ll. 61–67; col. 8, ll. 33–49. Pisupati teaches that the campaign platform 110 "continually monitors the campaigns that have been sent to each intended recipient and the intended recipients' engagement with the campaigns," and the filtering state machine transitions recipients between normal, rest, and safe states on an ongoing basis, allowing the active contact list to be updated in connection with each campaign send cycle.).
Claim 12: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses wherein checking the initial contact list to determine that the initial contact list satisfies the initial set of engagement rules comprises: determining whether a number of recipients of the initial contact list is greater than a first contact number threshold (col. 9, ll. 5–15; FIG. 4; FIG. 5. Pisupati teaches that the campaign platform 110 performs a sub-segmentation process on saturated recipients, ranking them from most fatigued to least fatigued and applying breakpoints to partition the ranked list into sub-segments. A predetermined number of the top sub-segments are selected for removal. Under the broadest reasonable interpretation, the breakpoint partitions define partition boundaries that function as numerical thresholds for identifying which ranked recipients fall within sub-segments selected for removal.).
Claim 13: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses wherein generating the active contact list comprises modifying the initial contact list by reducing the number of recipients to below the first contact threshold (col. 9, ll. 13–19; FIG. 2, step 260; FIG. 5. Pisupati teaches that the campaign platform 110 removes the most-fatigued intended recipient profiles in the top sub-segments from the recipients list 113 by transitioning their state to "rest." Under the broadest reasonable interpretation, this removal reduces the number of recipients remaining in the ranked portion of the active list implicated by the partition boundary used to select recipients for removal.).
Claim 14: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses wherein checking the initial contact list to determine that the initial contact list satisfies the initial set of engagement rules comprises: identifying a number of unengaged recipients of the initial contact list (col. 7, ll. 41–67; FIG. 2, steps 220–230; FIG. 3. Pisupati's campaign platform 110 determines, for each intended recipient, a fatigue status. Recipients whose fatigue status is "saturated" are identified as unengaged recipients.); and
comparing the number of recipients of the initial contact list with a number of recipients of the initial contact list minus the unengaged recipients are removed from the initial contact list (col. 9, ll. 5–15; FIG. 4; FIG. 5. Pisupati teaches that the sub-segmentation process evaluates the saturated (unengaged) recipients relative to the overall recipient population and partitions the ranked list to determine how many need to be removed. Under the broadest reasonable interpretation, this process reasonably encompasses a comparison between the total number of recipients and the number that would remain after the unengaged recipients are removed, because the partitioning is performed on a ranked set of saturated recipients relative to the broader recipient population and thereby reasonably encompasses evaluating the effect of removing identified unengaged recipients from the list.).
Claim 15: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses eliminating the unengaged recipients if the compared number of recipients of the initial contact list with a number of recipients of the initial contact list minus the unengaged recipients is greater than a threshold percentage (col. 9, ll. 13–19; FIG. 5. Pisupati teaches that the campaign platform 110 applies breakpoint partitions to the ranked list of saturated recipients, and the recipients in the top sub-segments — i.e., the most send-fatigued — are removed from the recipients list 113. Under the broadest reasonable interpretation, the breakpoint partitions reasonably function as a threshold proportion for selecting a portion of the saturated population for elimination.).
Claim 16: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses wherein analyzing the success of the electronic message campaign comprises determining an open rate of the campaign, including determining a percentage of recipients that opened the campaign (col. 7, ll. 27–40; col. 8, ll. 3–12; FIG. 3. Pisupati teaches that the campaign platform 110 monitors whether each intended recipient opened the campaign email, determines a frequency value based on the number of times the recipient opened campaigns within the period of observation, and determines a response rate by dividing the number of responses over a predetermined period by the number of sent campaigns over the same period. Under the broadest reasonable interpretation, these monitored open counts and response rate calculations reasonably encompass determining an open rate of the campaign, including the percentage of recipients that opened it.).
Claim 17: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses wherein analyzing the success of the electronic message campaign comprises determining a click through rate of the campaign, including determining a percentage of recipients that selected a link within the campaign (col. 7, ll. 8–12; col. 8, ll. 3–12. Pisupati teaches that the specific interaction monitored by the campaign platform 110 depends on the channel of communication, and for at least some channels, engagement includes a "click of a link in the message." The campaign platform 110 tracks these click interactions and determines engagement rates from them. Under the broadest reasonable interpretation, tracking recipient clicks on links within campaign messages and calculating engagement rates therefrom reasonably encompasses determining a click-through rate of the campaign.).
Claim 18: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Ramakrishnan further discloses wherein analyzing the success of the electronic message campaign comprises determining a conversion rate of the campaign, including determining a percentage of recipients that are determined to have performed an action based on the campaign (col. 1, ll. 15–30; col. 5, ll. 5–10; col. 7, ll. 47–65; col. 8, ll. 5–25. Ramakrishnan teaches that the system tracks responses to calls to action in email campaigns, where such responses include clicking on a "buy now" or "reserve yours today" button, completing a purchase of a product or service, and visiting a website. In the data collection phase, the system collects a history of actual responses to calls to action in prior campaigns and identifies which recipients opened emails and which responded by performing these conversion actions. This data is used to calculate click-through and conversion metrics that inform the personalization model.).
The rationale for combining Pisupati and Ramakrishnan is articulated above and is reincorporated herein by reference.
Claim 20: The Pisupati/Ramakrishnan combination discloses those limitations cited above.
Pisupati further discloses wherein the server is further configured to:
obtain an initial contact list (col. 5, ll. 51–67; col. 6, ll. 23–31; FIG. 1. Pisupati's campaign platform 110 includes a profile database 111 storing a plurality of intended recipient profiles 112a–n, and a list of recipients 113 comprising the intended recipients to receive campaign messages.);
check the initial contact list to determine that the initial contact list satisfies an initial set of engagement rules (col. 7, ll. 27–67; FIG. 2, steps 210–230; FIG. 3. Pisupati's campaign platform 110 monitors sent campaigns and engagement, determines recency and frequency values for each recipient, and determines a fatigue status for each intended recipient profile based on those values, thereby checking whether the contact list satisfies engagement rules.);
generate the active contact list comprising modifying the initial contact list when the initial contact list does not satisfy the initial set of engagement rules (col. 8, ll. 60–67; col. 9, ll. 1–19; FIG. 2, steps 250–260. When the campaign platform 110 determines that intended recipient profiles have a "saturated" fatigue status, it performs sub-segmentation, identifies the most send-fatigued recipients, and removes them from the recipients list 113 by transitioning their state attribute to "rest," thereby generating a modified active contact list.);
electronically send the electronic message campaign to recipients of the active contact list (col. 8, ll. 50–58; FIG. 2, step 240. Pisupati's campaign platform 110 sends campaign messages to the intended recipients remaining on the recipients list 113 — i.e., those in the "normal" state.);
determine a success score of the electronic messages based on the tracked sensed actions (col. 9, ll. 5–12; FIG. 4. Pisupati's campaign platform 110 calculates a fatigue score for each saturated recipient based on (1) a degree of reduction in the engagement rate, (2) the degree of increase in sends delivered, and (3) the degree to which send volume caused the reduction in engagement. This fatigue score constitutes a success score determined from the tracked recipient actions.);
adaptively adjust the active contact list according to active engagement rules of based on an evaluated success of the electronically sent campaign comprising reducing a number of recipients of the active contact list by eliminating non-engaged recipients based on the determined success score of the electronic messages of the electronically sent campaign (col. 9, ll. 5–19; FIG. 2, steps 250–260; FIG. 5. Pisupati's campaign platform 110 ranks the saturated recipients from most fatigued to least fatigued based on the fatigue score, partitions the ranked list at breakpoints to form sub-segments, and removes the most-fatigued recipients in the top sub-segments from the recipients list 113 by setting their state to "rest," thereby eliminating non-engaged recipients and reducing the number of recipients on the active contact list.);
identify engaged recipients of the electronic message campaign of the active contact list over a predetermined period of time by the active engagement rules (col. 7, ll. 27–40; FIG. 3. Pisupati's campaign platform 110 uses a predetermined period of observation — such as the previous 60 days or 30 days — to determine frequency values and engagement rates, and identifies recipients whose fatigue status is "unsaturated" as engaged recipients over that period.); and
adaptively adjust the active contact list according to active engagement rules based on an evaluated success of the electronically sent campaign comprising adjusting the predetermined period of time based on the evaluated success of the electronically sent campaign (col. 10, ll. 24–43; FIG. 6. When a recipient "relapses" — i.e., the campaign platform 110 determines the recipient remains saturated after the safe state — the time spent in the rest state is increased according to the function f(n) = 7 + (n+1)², where n is the number of relapses. This constitutes an adaptive adjustment of the predetermined time period based on the evaluated success of the campaign, because the duration of exclusion from the active contact list increases when engagement remains poor.).
Claims 4 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Pisupati et al. (US 11,488,204 B2) in view of Ramakrishnan et al. (US 9,608,942 B1), and in further view of Lau et al. (US 8,892,461 B2).
Claim 4: The Pisupati/Ramakrishnan combination discloses those limitations cited above. As discussed with respect to claim 1, Pisupati teaches recipient computing devices receiving electronic campaign messages and the recipient's email system tracking recipient interactions with those messages based on the reception of the electronic message.
However, the Pisupati/Ramakrishnan combination does not appear to explicitly disclose wherein the application loaded on the computing device controls sensing of a location sensor and motion sensors of the computing device, wherein the application loaded on the computing device identifies and tracks sensed locations of the location sensor of the computing device, and sensed motion of motion sensors of the computing device, and wherein determining the level of engagement of the recipient is based on the tracked locations, and the sensed motion.
Lau, however, discloses wherein the application loaded on the computing device controls sensing of a location sensor and motion sensors of the computing device (col. 5, ll. 6–10; col. 8, ll. 50–67; FIG. 2. Lau teaches a mobile device including a plurality of sensors — GPS 220, accelerometer 240, gyroscope 210, compass 230, and altimeter — and a controller 250 that receives location and motion information from the plurality of sensors. An application running on the mobile device processes the sensor data to generate a user profile based on tracked locations and tracked motion behavior.);
the application loaded on the computing device identifies and tracks sensed locations of the location sensor of the computing device, and sensed motion of motion sensors of the computing device (col. 5, ll. 10–25; FIG. 1; FIG. 3, steps 310–330. Lau teaches tracking a plurality of locations of the mobile device via GPS and tracking motion behavior of the mobile device via the accelerometer, gyroscope, and compass. The application identifies points of interest visited by the user, tracks visit frequency, duration, and routes, and identifies motion patterns including mode of transportation — walking, bicycling, running, and driving — each of which produces a unique motion signature.); and
wherein determining the level of engagement of the recipient is based on the tracked locations, and the sensed motion (col. 5, ll. 32–55; FIG. 4. Lau teaches generating a user profile over a period of time based on the tracked plurality of locations and the tracked motion behavior, and using that profile to provide targeted information and recommendations to the user. The user profile includes location preference, visit frequency, and motion activity patterns. It would have been obvious to use these tracked location and motion behaviors as additional inputs to the engagement determination of the Pisupati/Ramakrishnan combination, because they provide real-world behavioral characterizations of the recipient beyond digital interaction metrics.).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify the Pisupati/Ramakrishnan combination to incorporate Lau's location and motion sensor tracking on the recipient's mobile device so that the engagement determination is based on tracked locations and sensed motion in addition to tracked opens and clicks. One would have been motivated to do so in order to obtain a richer and more accurate characterization of recipient engagement by capturing real-world behavioral signals — such as whether the recipient visited a merchant location or exhibited motion patterns consistent with product interaction — that are not available from digital interaction tracking alone (Lau, col. 5, ll. 62–67; col. 6, ll. 15–20).
Claim 6: The Pisupati/Ramakrishnan/Lau combination discloses those limitations cited above.
Lau further discloses identifying patterns of location visits of the computing device of the recipient (col. 5, ll. 32–55; FIG. 4; FIG. 5. Lau teaches that the user profile includes location behavior patterns learned from fundamental statistics, including which points of interest a user visits often, at what time of day and day of week, and statistical transitions between different points of interest — such as the user visiting place A after place B. Route-based information including route usage frequency and timing is also tracked. These constitute patterns of location visits.); and
further determining, by the campaign success engine, the level of engagement of the recipient, based on the identified patterns of location visits (col. 5, ll. 62–67; col. 6, ll. 15–20; FIG. 4; FIG. 6. Lau teaches using the identified location visit patterns to provide targeted information and recommendations to the user, and to estimate the likelihood of confirmation of targeted advertising based on the user profile. A skilled artisan would have recognized that these identified visit patterns — such as a recipient repeatedly visiting a merchant location after receiving a campaign message — would serve as additional behavioral inputs to the campaign success engine's engagement determination in the Pisupati/Ramakrishnan combination.).
The rationale for combining Lau with Pisupati and Ramakrishnan is articulated above and is reincorporated herein by reference.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Pisupati et al. (US 11,488,204 B2) in view of Ramakrishnan et al. (US 9,608,942 B1), and in further view of Lau et al. (US 8,892,461 B2) and Sprigg et al. (US 2013/0217333 A1).
The Pisupati/Ramakrishnan combination discloses those limitations cited above, but does not appear to explicitly disclose determining, by the application loaded on the computing device, whether the computing device of the recipient interacts with another computing device of another recipient based on the sensed location and motion of the computing device, and sensed location and motion of another computing device of the other recipient; and further controlling the visual content of displays of computing devices of each of the recipients of the present electronic message based on the determined influence of the recipient.
Lau discloses sensing location and motion of a mobile device of a recipient via GPS, accelerometer, gyroscope, and compass sensors, and generating a user profile based on tracked locations and motion behavior, as described above with respect to claim 4.
Sprigg further discloses determining, by the application loaded on the computing device, whether the computing device of the recipient interacts with another computing device of another recipient based on the sensed location and motion of the computing device, and sensed location and motion of another computing device of the other recipient (¶¶ 0070–0080; FIGS. 18A–18D. Sprigg teaches detecting proximity between mobile devices using short-range wireless broadcasts such as Bluetooth Low Energy. When multiple proximity broadcast receivers report concurrent sighting messages, the central server computes a location of an overlapping region related to the concurrent sighting messages and associates the overlapping region with the devices, thereby determining whether one computing device interacts with another computing device based on their respective sensed locations. Sprigg further teaches computing finer-grained locations based on received signal power levels and locations of the devices transmitting the concurrent sighting messages.).
Regarding the limitation of further controlling the visual content of displays of computing devices of each of the recipients of the present electronic message based on the determined influence of the recipient: Ramakrishnan, as previously discussed, discloses customizing the visual features of email content pieces for each recipient based on that recipient's behavioral characteristics, including features reflecting the recipient's prior interactions and engagement history (col. 6, ll. 20–50; col. 7, ll. 1–20; col. 11, ll. 20–40). It would have been obvious to use Sprigg's device-to-device interaction data as an additional influence-related behavioral input to Ramakrishnan's personalization, because a recipient's social proximity to and co-location with other recipients constitutes a behavioral signal that would predictably improve the targeting of visual content displayed to each recipient.
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify the Pisupati/Ramakrishnan combination to incorporate Lau's location and motion sensor tracking and Sprigg's device-to-device proximity detection so that the system determines whether recipient devices interact with one another and uses the resulting influence data to further control the visual content of campaign messages. One would have been motivated to do so in order to identify recipients who have social proximity to or co-location with other recipients, because such interaction data provides an additional behavioral signal indicating the recipient's potential influence on other recipients' engagement, thereby enabling more targeted content personalization (Sprigg, ¶¶ 0004–0008; Lau, col. 5, ll. 62–67; col. 6, ll. 15–20).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Pisupati et al. (US 11,488,204 B2) in view of Ramakrishnan et al. (US 9,608,942 B1), and in further view of Forsblom (US 9,799,054 B2).
The Pisupati/Ramakrishnan combination discloses those limitations cited above, but does not appear to explicitly disclose sensing at least one of hand motions, direction of eyesight, and orientations of the computing device that indicate product interaction of the recipient; and wherein the level of engagement of the recipient is further based on the indicated product interaction.
Forsblom, however, discloses sensing at least one of hand motions, direction of eyesight, and orientations of the computing device that indicate product interaction of the recipient (col. 5, ll. 48–58; col. 7, ll. 37–63; FIGS. 1, 5–13. Forsblom teaches a mobile communications device including a motion subsystem 18 with an accelerometer 46, gyroscope 48, and compass 50. The motion subsystem detects and quantifies motion and gesture inputs from the user, including hand motions such as walking steps, running movements, and drawing gestures with the phone, as well as orientations of the computing device detected via the gyroscope and compass. These motion and orientation inputs are translated to a set of quantified values that indicate the user's physical interaction with content displayed on the device. The claim recites "at least one of hand motions, direction of eyesight, and orientations of the computing device," and Forsblom satisfies this limitation through its express teaching of sensed hand motions and device orientations.);
wherein the level of engagement of the recipient is further based on the indicated product interaction (col. 8, ll. 23–40; FIGS. 7–9. Forsblom teaches that the quantified motion and gesture values are compared against predefined values corresponding to advertisement invocation instructions, and the advertisement is displayed in response to a substantial match. The user's physical hand motion and device orientation inputs are thus used to determine a level of interaction with the displayed content. It would have been obvious to one of ordinary skill in the art that such sensed hand motions and device orientations indicating product interaction would serve as additional behavioral inputs to the engagement determination of the Pisupati/Ramakrishnan combination.).
Therefore, it would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify the Pisupati/Ramakrishnan combination to incorporate Forsblom's motion and orientation sensing so that the engagement determination is further based on sensed hand motions and device orientations indicating product interaction. One would have been motivated to do so in order to capture physical engagement signals — such as the recipient physically handling, tilting, or gesturing with the device in response to displayed campaign content — that provide a more granular measure of recipient engagement than digital interaction metrics alone (Forsblom, col. 1, ll. 25–32).
Other Relevant Art
Though not cited in the aforementioned rejections, the following references are nevertheless deemed to be relevant to Applicant’s disclosures:
Brechbuhl et al. (10778628), directed to predictive scoring and messaging in messaging systems.
Blanchard et al. (20250238839), directed to a method for controlling visual content of display of electronic messages to recipients based on the level of engagement.
O’Brien et al. (10931623), directed to a method for introducing a new message source into an electronic message delivery environment.
Kebinger et al. (10771425), directed to a method for electronic message lifecycle management.
Campbell et al. (20050108092), directed to a method of rewarding the viewing of ads based on eye gaze patterns.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER BUSCH whose telephone number is (571)270-7953. The examiner can normally be reached M-F 10-7.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Waseem Ashraf can be reached at 571-270-3948. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHRISTOPHER C BUSCH/Examiner, Art Unit 3621
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