Prosecution Insights
Last updated: April 19, 2026
Application No. 15/006,759

CUSTOMER QUEUE PRIORITIZATION THROUGH LOCATION DETECTION

Non-Final OA §103
Filed
Jan 26, 2016
Examiner
CHEN, WENREN
Art Unit
3626
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Comenity LLC
OA Round
16 (Non-Final)
14%
Grant Probability
At Risk
16-17
OA Rounds
3y 6m
To Grant
41%
With Interview

Examiner Intelligence

Grants only 14% of cases
14%
Career Allow Rate
27 granted / 198 resolved
-38.4% vs TC avg
Strong +27% interview lift
Without
With
+27.1%
Interview Lift
resolved cases with interview
Typical timeline
3y 6m
Avg Prosecution
41 currently pending
Career history
239
Total Applications
across all art units

Statute-Specific Performance

§101
32.0%
-8.0% vs TC avg
§103
32.0%
-8.0% vs TC avg
§102
11.4%
-28.6% vs TC avg
§112
21.0%
-19.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 198 resolved cases

Office Action

§103
DETAILED ACTION Status of the Application The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . The amendment filed November 26, 2025 has been entered: Claims 1, 2, 8-11, 16, and 17 are amended. Claims 1, 2, 8-11, 16, and 17 are pending. Priority The present application claims priority to Provisional Application 62/202,062, filed on 8/6/2015. Response to Amendment 35 U.S.C. 112(a) rejection is withdrawn in light of the amendment. Claim Objections have been added in light of the amendment. 35 U.S.C. 103 rejection is maintained in light of the amendment. Claim Objections Claims 1, 2, 8-11, 16, and 17 are objected to because of the following informalities: claims 1 and 10 recite “wherein said mobile application operating on said customer's mobile device is enabled to look for a transmission from said beacon and, when said transmission is detected, said mobile application operating on said customer's mobile device will notify said customer of location-relevant content; said processor automatically providing, to the store's computing system and from an application” should read “wherein a mobile application operating on said customer's mobile device is enabled to look for a transmission from said beacon and, when said transmission is detected, said mobile application operating on said customer's mobile device will notify said customer of location-relevant content; said processor automatically providing, to the store's computing system and from said mobile application” (bold and underline emphasis included). Appropriate correction is required. Dependent claims 2, 8, 9, 11, 16, and 17 depend on claims 1 and 10 above and therefore inherit the deficiencies of their parent claim. Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 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. The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under pre-AIA 35 U.S.C. 103(a) are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. Claims 1, 2, 8-11, 16, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Zhao (US 20140058870 A1, reference previously introduced under “Relevant Prior Art Not Relied Upon” of Non-Final Office Action mailed on September 24, 2020) in view of Statler et al. (US 20130030915 A1, hereinafter “Statler”) and further in view of Postrel (US 2015/0140982 A1). Regarding claims 1 and 10, Zhao discloses a computer-implemented method (para. [0014], “process”) and a non-transitory computer-readable storage medium having instructions embodied therein that when executed cause a computer system to perform a method prioritizing customer service, the method (para. [0048] and [0068], “computer readable medium”) comprising: a processor (para. [0048]) automatically receiving, when a customer enters a store location, at a store's computing system and from at least one beacon of a plurality of beacons, location information indicating that a plurality of customers have entered a retail store location, the location information provided to said at least one beacon from a mobile device in possession of each of said plurality of customers (Abstract: “When a customer approaches or enters a merchant's store the customer has signed up with, the user device carried by the customer wirelessly broadcasts a signal for the customer key unique to the merchant key.” Para. [0023] disclosing the user device may have GPOS capability. In Para. [0031]-[0032] disclosing “a customer walks into or approaches a store of merchant with whom the customer has previously signed up for the customer/merchant key generation, the user device carried by the customer broadcasts out a wireless signal unique to the customer key stored in the user device, which is captured by the merchant's server. The wireless technology used for that purpose may be any technology employed for a relatively short-range wireless communication such that the merchant server may be able to capture the wireless broadcast of the customer key only when the user device comes in a sufficient proximity to the merchant server, e.g., not farther than the boundary of a parking ground neighboring the merchant's physical store. Such short-range wireless communication technology includes, but is not limited to, a Wi-Fi or a Bluetooth connection.” (Bold emphasis included). The short-range wireless communication to identify the proximity location of the customer’s mobile to the merchant server can be Wi-Fi or a Bluetooth connection, which is consistent to the applicant’s specification in paragraphs [0017], [0037], [0040], [0057]-[0059], and [0091] for beacon communication can be any short-range wireless communication such as Wi-Fi and Bluetooth communication); said processor (para. [0048]) automatically providing, to the store's computing system and from an application operating on the mobile device (para. [0021]: preinstalled user application on user mobile device), personal information for each of said plurality of customer (para. [0052], “User device 310 may further include a key generation application 325 by which the user 305 may create or modify the user's shopping profile, which may be stored in the user device 310, payment provider server 370 via network 360, or both” disclosing the shopping profile as the personal information stored locally on the mobile device), the personal information comprising: at least one upcoming important event, and a date of said at least one upcoming important event (para. [0013], [0015], [0016], and [0038], disclosing the user’s shopping profile includes holidays and “personal celebration days like a birthday, an anniversary (wedding, work, etc.) of the user, a relative, or a best friend, and a baby shower, a bridal shower, and so on”); said processor (para. [0048]) automatically accessing, via the store's computing system, a database comprising a previous purchase history for each of said plurality of customers (para. [0018] and [0038] disclosing the accessing of the stored user’s profile includes customer’s past shopping history collected by the payment provider); said processor (para. [0048]) automatically determining, at the store's computing system, previous purchases that each said customer of the plurality of customers have made at said store location (para. [0018] and [0038] disclosing the accessing of the stored user’s profile includes customer’s past shopping history collected by the payment provider); said processor (para. [0048]) automatically providing, from the store's computing system and to a sales associate's mobile device, the customer based on said previous purchases (para. [0039] disclosing the automatic system for transmitting from the merchant server to merchant’s computer for customer who just walked into its store in an ordered way by the merchant application based on user profile including customer’s past shopping history); and said processor (para. [0048]) automatically indicating, said customer that a store employee should contact to serve and help, said indicating comprising: a present location of said customer within said retail store (para. [0039], “When the merchant accesses to the user's profile, all or selected information contained therein about a particular customer, who just did or is going to walk into its store, may be immediately transmitted from the payment provider to the merchant server and displayed or popped up, for instance, on a merchant's computer in an ordered way by a merchant application. What is displayed on the merchant's computer may even include the customer's picture. Seeing the picture, the store sales clerk may be able to readily recognize the particular customer entering or shopping in the store, and approach the customer to provide any helpful suggestions, recommendations or advice in finding and selecting items, based on the various information the merchant acquired about the customer's shopping preferences and needs.” and [0040], “the store clerk may still be able to locate the position of the customer inside the store via a sensor in the merchant server that can track down the source of the wireless signal of the customer key transmitted from the user device.”), and said at least one upcoming important event (para. [0015] and [0038] disclosing the user’s shopping profile is set up with information for seasonal holidays or personal celebration days like a birthday and anniversary, is communicated to the merchant). Zhao discloses the providing and indicating of the customer that a store employee should contact to serve and help in an ordered way by the merchant’s application, however, Zhao does not expressly disclose the ordered way by the merchant application for providing customer service includes the prioritizing of customer ranking based on previous purchases. Specifically, Zhao fails to expressly teach the limitations (italic emphasis): wherein said mobile application operating on said customer's mobile device is enabled to look for a transmission from said beacon and, when said transmission is detected, said mobile application operating on said customer's mobile device will notify said customer of location-relevant content; said processor automatically placing each of said plurality of customers into a prioritized customer ranking based on said previous purchases; the prioritized customer ranking for each customer based on said previous purchases; and said processor automatically indicating, in the automatically provided prioritized customer ranking, said customer. However, Statler is directed to similar field of apparatus and methods for providing in-store shopping assistance using mobile device, which specifically teaches, said processor (para. [0057]) automatically placing each of said plurality of customers into a prioritized customer ranking based on said previous purchases; the prioritized customer ranking for each customer based on said previous purchases (para. [0035], [0050], and [0067], disclosing prioritizing customer based on customer profile, buying habit, customer’s buying power and priority level (e.g., a measure of how valuable the customer may be to the retailer, for example, based on one or more of a credit rating, purchase history, etc.)); and said processor automatically indicating, in the automatically provided prioritized customer ranking, said customer that a store employee should contact to serve and help (Fig.2 and para. [0035] disclose the shopping assistance server (i.e. store’s computing system) receives customer information and the system will determine to send help dispatch to the customer based on customer profile of priority level (i.e. the prioritized customer ranking)). Therefore, it would have been obvious for one of ordinary skill in the art, before the effective filling of the invention to modify the system and method for providing in-store service assistance based on user’s profile of Zhao to include the feature of prioritizing customers into a prioritized customer ranking based on the user’s profile based on previous purchase history as taught by Statler for the motivation of providing a more effective and enhanced system and method for in-store customer service to accurately customers who needs help, as discussed in the specification of Statler, para. [0006], “retailers struggle with staffing to provide the quality of advice and information that can be gained online. Consumers are frustrated with attention when they do not want it and difficulties in getting adequate help when needed.” Statler teaches a solution that is consistent to the applicant’s description in para. [0017], “Retail locations are often not staffed for one associate to help every customer/consumer. Retail locations often prioritize who they will interact with first in order to maximize sales.” Statler discloses the method and computer product for prioritizing customer service using Beacon communication of NFC, Bluetooth, and wireless communication and providing relevant offers to the customer as they navigate the store based on location of the customer (para. [0052]). However, Postrel, which is in the field of wireless beacon communication system, to specifically teaches (italic emphasis included): wherein said mobile application operating on said customer's mobile device is enabled to look for a transmission from said beacon and, when said transmission is detected, said mobile application operating on said customer's mobile device will notify said customer of location-relevant content (para. [0012], “action that may be initiated is post-processing of data provided by execution of an app triggered by the beacon identifier. For example, the beacon filter manager may allow a beacon identifier to trigger a mobile app associated with an electronics store that the user is entering. The electronics store mobile app may operate to provide a purchase offer for display to the user on the mobile device.” In para. [0014] describes an intelligent beacon that provides beacon content directly to the user, including notifications, purchase incentives (i.e., coupons) and other information), which is definition of location-relevant content in a retail setting, as supported by the Applicant’s specification in para. [0019], “a user's mobile app (e.g., application140) can be enabled to look for the transmission of beacon190 (or any other beacons). When device110 is within physical proximity to the beacon and detects it, the application can notify the customer of location-relevant content, promotions, and offers”. Further in para. [0061] and [0063] provides specific example, that user entering a TARGET store and triggers mobile app to provide information such as purchase incentive of $5 coupon on user mobile device for use in the food department of that TARGET store). Postrel addresses the similar field of technology for mobile device to automatically receive wireless signal from a beacon upon entering a premises (e.g., retail store) and can trigger an associated mobile application without user intervention. Therefore, it would have been obvious for one of ordinary skill in the art, before the effective filling of the invention to modify the manual request of help from customer in Zhao/Statler to include the feature of automatic proximity-based beacon trigger to create a more seamless and proactive customer assistance system as taught by Postrel. Regarding claims 2 and 11, the combination of Zhao, Statler, and Postrel make obvious the method of claim 1 and computer product claim of 10. Zhao further discloses said processor automatically displaying said personal information for viewing on the sales associate’s mobile device at said store location (para. [0072] disclosing the displaying of customer’s information on merchant’s computer for the store clerk to recognize the customer in the store to provide service). Regarding claims 8 and 16, the combination of Zhao, Statler, and Postrel make obvious the method of claim 1 and computer product claim of 10. Zhao discloses the sales clerk provides helpful suggestion and recommendations based on customer’s profile (para. [0039]). However, Zhao fails to expressly teach, said processor generating a promotion for said customer based on said personal information. Nonetheless, Zhao teaches, said processor generating a promotion for said customer based on said personal information (para. [0069] discloses “the shopping assistant server 110 may request offers to be provided to the customer 802, as depicted at 838, from an offer service 812. Offers may provide incentives, such as discounts, to entice a customer to make a purchase. In some aspects, the offer may be based on any of the customer profile, customer shopping history, customer search history, customer movements through the store, etc.”). Therefore, it would have been obvious for one of ordinary skill in the art, before the effective filling of the invention to modify the system and method for providing in-store service assistance based on user’s profile of Zhao to include the feature of generating a promotion for said customer based on said personal information as taught by Statler for the motivation of providing incentive for the customer to make purchase and increase revenue for the store using the system (para. [0046] and [0069]). Regarding claims 9 and 17, the combination of Zhao, Statler, and Postrel make obvious the method of claim 8 and computer product claim of 16. Statler further teaches said processor displaying said promotion on the mobile device of said customer while said customer is located at said store location (Para. [0069] discloses “a customer may stand in front of coat display for 10 minutes (as detected by navigation services), and during that time retailer may offers a get $5 off on your next visit offer. The customer may view the offer, but continues browsing. After a period of time, such as 15 minutes have passed, the customer may scan one of the manufacturer's products, and the manufacturer may provide a $20 dollar off if you buy today offer.” The indication of “detected by navigation service” discloses customer is located in store location. “Customer may view the offer” discloses the promotion offer or discount is displayed in customer mobile device. Additionally, see Claim 37-39 and Para. [0046], [0075]).Therefore, it would have been obvious for one of ordinary skill in the art, before the effective filling of the invention to modify the system and method for providing in-store service assistance based on user’s profile of Zhao to include the feature of generating a promotion for said customer based on said personal information as taught by Statler for the motivation of providing incentive for the customer to make purchase and increase revenue for the store using the system (para. [0046] and [0069]). Relevant Prior Art Not Relied Upon The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure. The additional cited art, including but not limited to the excerpts below, further establishes the state of the art at the time of Applicant’s invention and shows the following was known: Hess et al. (US 8510163 B2) is directed to system and method for prioritizing queue for retail establishments. In addition to mobile devices may receive advertisement, offers, and coupons. Xiao et al. (US 20120158934 A1) is directed to a system and method for prioritizing queue process. Hanson et al. (US20160012375A1) which is directed to methods and systems for managing customer queues using local positioning technology are presented. In some embodiments, a customer assistance computing platform may receive one or more attributes associated with a beacon signal received by a customer computing device and an identifier associated with the customer computing device. Subsequently, the computing platform may determine an identity of a customer using the customer computing device. The computing platform then may determine a location of the customer using the customer computing device based on the one or more attributes associated with the beacon signal. Thereafter, the computing platform may select at least one queue from one or more maintained queues based on the location of the customer. Then, the computing platform may update the at least one selected queue based on the identity of the customer to add the customer using the customer computing device to the at least one selected queue. Hurewitz (US 20140365334 A1) is directed to a system and method that monitors a customer's movements, locations, product interactions, and purchase behavior within a physical retail store. Emotional reactions to physical items and the virtual display are also tracked. The customer can utilize a mobile device app to request assistance from a retail store clerk. The app determines the position of the customer's mobile device within the store, such as by using Bluetooth beacons, and then transmits this position and a request for assistance to a server computer. R. Unni and R. Harmon, "Location-based services: models for strategy development in M-commerce," PICMET '03: Portland International Conference on Management of Engineering and Technology Technology Management for Reshaping the World, 2003., Portland, OR, USA, 2003, pp. 416-424, doi: 10.1109/PICMET.2003.1222821. teaching location-based customer service at retail store. J. Li, I. Ari, J. Jain, A. H. Karp and M. Dekhil, "Mobile In-store Personalized Services," 2009 IEEE International Conference on Web Services, Los Angeles, CA, USA, 2009, pp. 727-734, doi: 10.1109/ICWS.2009.107 which teaches Mobile Shopping Assistant (MSA) is a mobile application platform to deliver real-time, in-store, and personalized services, such as personalized product offerings and in-store customer advisory support, to improve the shopping experiences of in-store customers. Siddique et al. (US 20130215116 A1) is directed to system and Method For Collaborative Shopping, Business And Entertainment, which teaches collecting user profile information including preference, interest, purchasing and browsing history. Siddique teaches user mobile device determine position location using GPS to estimate relative locations of other devices Response to Arguments 35 U.S.C. 112 Rejection: The rejected claims have been amended and corresponding 112(a) rejection has been withdrawn. 35 U.S.C. 103 Rejection: The Examiner asserts that the Applicant’s arguments are directed towards amended claim limitations and are, therefore, considered moot. The examiner asserts the reference Postrel is directed to a method of system for pre and post processing of beacon id signals (title). The entire purpose of Postrel is to manage the actions that occurs when a mobile device detects a beacon. Claim 16 of Postrel and para. [0012] teaches the primary actions is to notify the user on display of mobile device. In para. [0014] describes an intelligent beacon that provides beacon content directly to the user, including notifications, purchase incentives (i.e., coupons) and other information), which is definition of location-relevant content in a retail setting, as supported by the Applicant’s specification in para. [0040], “a user's mobile app (e.g., application 140) can be enabled to look for the transmission of beacon 190 (or any other beacons). When device 110 is within physical proximity to the beacon and detects it, the application can notify the customer of location-relevant content, promotions, and offers”. Further in para. [0061], [0063], and [0108] provides specific example, that user entering a TARGET store and triggers mobile app to provide information such as purchase incentive of $5 coupon on user mobile device for use in the food department of that TARGET store, teaches the amended claim limitation, "wherein said mobile application operating on said customer's mobile device is enabled to look for a transmission from said beacon and, when said transmission is detected, said mobile application operating on said customer's mobile device will notify said customer of location-relevant content." Thus, the 103 rejection has been maintained. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to WENREN CHEN whose telephone number is (571)272-5208. The examiner can normally be reached Monday - Friday 10AM - 6PM. 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, Nathan C Uber can be reached at (571) 270-3923. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /WENREN CHEN/Primary Examiner, Art Unit 3626
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Prosecution Timeline

Jan 26, 2016
Application Filed
Sep 02, 2017
Non-Final Rejection — §103
Dec 07, 2017
Response Filed
Mar 04, 2018
Final Rejection — §103
Jun 07, 2018
Request for Continued Examination
Jun 08, 2018
Response after Non-Final Action
Aug 04, 2018
Non-Final Rejection — §103
Nov 09, 2018
Response Filed
Jan 26, 2019
Non-Final Rejection — §103
May 07, 2019
Response Filed
Jul 26, 2019
Final Rejection — §103
Oct 31, 2019
Request for Continued Examination
Nov 02, 2019
Response after Non-Final Action
Dec 10, 2019
Non-Final Rejection — §103
Mar 12, 2020
Response Filed
Apr 23, 2020
Final Rejection — §103
Jul 28, 2020
Request for Continued Examination
Aug 03, 2020
Response after Non-Final Action
Sep 19, 2020
Non-Final Rejection — §103
Dec 23, 2020
Response Filed
Feb 25, 2021
Final Rejection — §103
Jul 09, 2021
Notice of Allowance
Sep 08, 2021
Response after Non-Final Action
Sep 18, 2021
Response after Non-Final Action
Nov 05, 2021
Response after Non-Final Action
Jan 14, 2022
Response after Non-Final Action
Jan 19, 2022
Response after Non-Final Action
Jan 20, 2022
Response after Non-Final Action
Jan 20, 2022
Response after Non-Final Action
Sep 27, 2023
Response after Non-Final Action
Dec 21, 2023
Request for Continued Examination
Feb 17, 2024
Response after Non-Final Action
Feb 27, 2024
Non-Final Rejection — §103
Jun 04, 2024
Response Filed
Jul 26, 2024
Final Rejection — §103
Oct 30, 2024
Request for Continued Examination
Oct 31, 2024
Response after Non-Final Action
Dec 11, 2024
Non-Final Rejection — §103
Mar 17, 2025
Response Filed
May 26, 2025
Final Rejection — §103
Sep 29, 2025
Request for Continued Examination
Oct 05, 2025
Response after Non-Final Action
Oct 17, 2025
Non-Final Rejection — §103
Nov 26, 2025
Response Filed
Dec 16, 2025
Final Rejection — §103
Jan 29, 2026
Request for Continued Examination
Feb 23, 2026
Response after Non-Final Action
Mar 20, 2026
Non-Final Rejection — §103 (current)

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Expected OA Rounds
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3y 6m
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