DETAILED ACTION
This action is in response to a filing filed on March 10th, 2025. Claims 1-20 have been examined in this application. The Information Disclosure Statement (IDS) filed on 05/20/25, 08/25/25, 11/24/25, 04/02/2026, and 05/20/2026 has been acknowledged.
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 .
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., an abstract idea) without significantly more.
Step 1: Claims 1-5 is/are drawn to system (i.e., a manufacture), claims 6-14 is/are drawn to method (i.e., a process), and claims 15-20 is/are drawn to computer readable storage medium (i.e., a manufacture). As such, claims 1-20 is/are drawn to one of the statutory categories of invention (Step 1: YES).
Step 2A - Prong One: In prong one of step 2A, the claim(s) is/are analyzed to evaluate whether it/they recite(s) a judicial exception.
Representative Claim 1: A system comprising: one or more processors;
and one or more non-transitory computer-readable media storing instructions executable by the one or more processors, wherein the instructions, when executed, cause the system to perform operations comprising:
receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store;
receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store;
determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order are to be grouped together as a first batched order;
receiving first location data from a first computing device associated with the first pickup entity;
determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store;
and sending a first message to a store computing device associated with the store, the first message being indicative of the first estimated arrival time and the first batched order associated with the first pickup entity.
(Examiner notes: The underlined claim terms above are interpreted as additional elements beyond the abstract idea and are further analyzed under Step 2A - Prong Two)
Under their broadest reasonable interpretation, claim 1 is directed to the abstract idea of receiving first and second pickup orders associated with the same pickup entity and directed to the same store; determining, based on information associated with the pickup entity, that the orders are to be grouped as a batched order; determining an estimated arrival time for the pickup entity; and communicating the batched-order and estimated-arrival information to the store. These limitations, when considered together, recite coordinating fulfillment of multiple commercial pickup orders by grouping orders associated with the same pickup entity and providing the store with grouped-order and anticipated arrival information. This is a certain method of organizing human activity, specifically a commercial interaction involving sales activity and the business relationship between the pickup entity and the store. These limitations describe coordination of the commercial relationship and interactions between a customer or pickup provider and a store in connection with the fulfillment of retail orders. Accordingly, the limitations fall within the certain methods of organizing human activity grouping, specifically commercial interactions, including sales activities or behaviors and business relations.
Dependent claims 2-5, 7-14, and 16-20 recite additional details of that same abstract idea. Claims 2, 9, and 18 recite receiving additional pickup orders associated with a second user, grouping those orders as a second batched order, determining a second estimated arrival time, comparing the estimated arrival times of the first and second users, and notifying the store of the earlier-arriving batched order. Claims 3, 10, and 19 recite generating and communicating an order queue that lists the batched orders based on their respective estimated arrival times. Claims 4, 11, and 20 recite determining preparation durations and preparation-starting times for the batched orders and updating the order queue based on those starting times. Claims 5 and 12 recite that the pickup entity or third party is a pickup service provider, deliverer, or non-human entity. Claims 7 and 16 recite associating the user with identifying information, such as a username, contact information, address, order identifier, or transaction identifier. Claims 8 and 17 recite receiving user-location information, determining an estimated arrival time from that information, and communicating the estimated arrival time to the store. Claim 13 recites receiving a batched-order status from the store and communicating that status to the user, and claim 14 recites that the status is a ready, processing, or waiting state. These dependent claims merely specify additional users or pickup entities, types of identifying and location information, order-grouping and prioritization criteria, preparation scheduling information, and communications used to coordinate the same commercial pickup-order transaction. Accordingly, dependent claims 2–5, 7–14, and 16–20 continue to recite the abstract idea of organizing and coordinating fulfillment of commercial pickup orders by grouping related orders, determining arrival and preparation priority, and communicating order and status information between a user and a store.
Independent claim(s) 6 and 15 recite/describe nearly identical steps (and therefore also recite limitations that fall within this subject matter grouping of abstract ideas), and this/these claim(s) is/are therefore determined to recite an abstract idea under the same analysis.
As such, the Examiner concludes that claim 1 recites an abstract idea (Step 2A – Prong One: YES).
Step 2A - Prong Two: In prong two of step 2A, an evaluation is made whether a claim recites any additional element, or combination of additional elements, that integrate the exception into a practical application of that exception. An “addition element” is an element that is recited in the claim in addition to (beyond) the judicial exception (i.e., an element/limitation that sets forth an abstract idea is not an additional element). The phrase “integration into a practical application” is defined as requiring an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception.
The requirement to execute the claimed steps/functions using a processor and one or more non-transitory computer-readable media, etc. (Claim 1, 6, and 15) is/are equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer.
Similarly, the limitations of applying a processor and one or more non-transitory computer-readable media, etc. (Claim 1, 6, and 15, and dependent claims 2-5, 7-14, and 16-20) are recited at a high level of generality and amount to no more than mere instructions to apply the exception using generic computer components. This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(f)).
Further, the additional limitations beyond the abstract idea identified above, serves merely to generally link the use of the judicial exception to a particular technological environment or field of use. Specifically, it/they serve(s) to limit the application of the abstract idea to computerized environments (e.g., receiving, determining, sending, etc. steps performed by a processor and one or more non-transitory computer-readable media, etc.). This reasoning was demonstrated in Intellectual Ventures I LLC v. Capital One Bank (Fed. Cir. 2015), where the court determined "an abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment, such as the Internet [or] a computer"). This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(h)).
The recited additional element(s) of receiving pickup orders, pickup-entity information, user information, and location data merely gathers information used to carry out the commercial process. Sending messages containing batched-order, estimated-arrival-time, queue, or order-status information merely transmits or presents the results of the commercial organization and scheduling process. The limitations of grouping orders as a batched order, determining an estimated arrival time, and communicating the batched-order and arrival information to the extent the receiving and transmitting limitations are considered additional elements, they merely append insignificant extra-solution activity to the judicial exception, including pre-solution data gathering and post-solution transmission or presentation of results (Independent Claim 1, 6, and 15), additionally and/or alternatively simply append insignificant extra-solution activity to the judicial exception, (e.g., mere pre-solution activity, such as data gathering, in conjunction with an abstract idea). This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application. (See MPEP 2106.05(g)).
Dependent claims 2–5, 7–14, and 16–20 also fail to integrate the abstract idea into a practical application. Claims 2, 9, and 18 merely repeat the same commercial order-management process for a second user by receiving additional pickup orders and location data, grouping the orders as another batch, calculating another estimated arrival time, comparing the users’ estimated arrival times, and communicating the comparison to the store. Receiving the additional orders and location information is further data gathering; comparing arrival times merely applies a commercial prioritization rule; and communicating the resulting priority merely outputs the result. Claims 3, 10, and 19 merely organize the batched-order and estimated-arrival information into an order queue and transmit the queue to the store computing device. Organizing commercial information according to estimated arrival times and presenting the resulting ordered list merely further defines how the commercial fulfillment information is arranged and displayed. Claims 4, 11, and 20 merely determine preparation durations and preparation-starting times and update the order queue according to those times. These limitations further define business scheduling rules used to decide when store personnel should begin preparing the orders. They do not improve the operation of a computer, location system, network, or store equipment. Claims 5 and 12 merely specify the type of person or entity that performs the pickup, such as a pickup service provider, deliverer, or non-human entity. These limitations merely restrict the commercial process to particular participants or a particular field of use and do not recite a technical mechanism for operating or controlling a non-human entity. Claims 7 and 16 merely specify types of identifying information associated with a user, such as a username, phone number, email address, physical address, order identifier, or transaction identifier. These limitations merely identify the type of commercial data collected or stored. Claims 8 and 17 merely receive location information, calculate an estimated arrival time from the location information, and communicate the estimated arrival time to the store. Receiving location information is pre-solution data gathering; calculating an arrival estimate further defines the commercial coordination process; and transmitting the estimated arrival time merely presents the result. Claim 13 merely receives order-status information from the store and transmits the status information to the user device. These limitations merely gather and relay information concerning the progress of the commercial pickup transaction. Claim 14 merely specifies that the communicated status may be ready, processing, or waiting. This limitation merely defines the type of commercial status information presented and does not change how the computer or communication technology operates. These additional limitations merely gather additional order, user, location, timing, or status data; specify the participants or types of information used; apply commercial grouping, comparison, prioritization, and scheduling rules; or communicate the resulting information. They do not improve the operation of the underlying technology and do not provide a technical solution to a technical problem.
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claim(s) is/are directed to an abstract idea (Step 2A – Prong two: NO).
Step 2B: In step 2B, the claims are analyzed to determine whether any additional element, or combination of additional elements, is/are sufficient to ensure that the claims amount to significantly more than the judicial exception. This analysis is also termed a search for an "inventive concept." An "inventive concept" is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim as a whole amounts to significantly more than the judicial exception itself. Alice Corp., 134 S. Ct. at 2355, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 72-73, 101 USPQ2d at 1966).
As discussed above in “Step 2A – Prong 2”, the identified additional elements in independent claim(s) 1, 6, and 15, and dependent claims 2-5, 7-14, and 16-20 are equivalent to adding the words “apply it” on a generic computer, and/or generally link the use of the judicial exception to a particular technological environment or field of use. Therefore, the claims as a whole do not amount to significantly more than the judicial exception itself.
The recited additional element(s) of receiving pickup orders, pickup-entity information, user information, and location data merely gathers information used to carry out the commercial process. Sending messages containing batched-order, estimated-arrival-time, queue, or order-status information merely transmits or presents the results of the commercial organization and scheduling process (Claim(s) 1, 6, and 15), additionally and/or alternatively simply append insignificant extra-solution activity to the judicial exception, (e.g., mere pre-solution activity, such as data gathering, in conjunction with an abstract idea) i.e. is similar to “Receiving or transmitting data over a network, e.g., using the Internet to gather data”, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), “Storing and retrieving information in memory”, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; “Presenting offers to potential customers and gathering statistics generated based on the testing about how potential customers responded to the offers; the statistics are then used to calculate an optimized price”, Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d 1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir. 2014) (optical character recognition), is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here) (See MPEP 2106.05(d) (II)).
This conclusion is based on a factual determination. Applicant’s own disclosure at paragraph [0039] acknowledges that “managing computing device(s) 204 can receive order data and/or user data from the user computing device(s) 206, and can store the order data in the memory 224 of the order managing component 228. In some examples, the order data may indicate services and/or items ordered by the user (e.g., food items, drink items, prescription drugs, grocery item examples, the order managing component 228 can store the timestamp data (which may indicate the time the order was made) associated with the order data input from the user computing device(s) 206. In some examples, the order data and/or the user data can further include an order identifier (e.g., an order ID) and/or a transaction identifier” (i.e., conventional nature of receiving and transmitting data/messages over a network). This additional element therefore do not ensure the claim amounts to significantly more than the abstract idea.
Viewing the additional limitations in combination also shows that they fail to ensure the claims amount to significantly more than the abstract idea. When considered as an ordered combination, the additional components of the claims add nothing that is not already present when considered separately, and thus simply append the abstract idea with words equivalent to “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer or/and append the abstract idea with insignificant extra solution activity associated with the implementation of the judicial exception, (e.g., mere data gathering, post-solution activity) and/or simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
Dependent claims 2-5, 7-14, and 16-20 fail to include additional elements that amount to significantly more than the abstract idea. Claims 2, 9, and 18 merely repeat the same pickup-order process for a second user by receiving additional orders and location information, grouping the additional orders as another batch, determining another estimated arrival time, comparing the estimated arrival times, and communicating the resulting priority to the store. These limitations merely collect additional commercial information, apply the same grouping and prioritization rules to another customer, and communicate the result. Repeating an abstract process for another participant does not provide an inventive concept. Claims 3, 10, and 19 merely organize the batched orders into an order queue according to estimated arrival times and communicate the queue to the store computing device. Generating the queue merely organizes and ranks commercial order information, while sending the queue merely presents the result of that organization. The claims do not recite a new database structure, memory-management technique, or improved graphical-interface technology for generating or transmitting the queue. Claims 4, 11, and 20 merely determine preparation durations and preparation-starting times and update the queue according to those times. These limitations further define commercial scheduling and prioritization rules used to determine when store personnel should prepare particular orders. The claims do not recite an improved scheduling algorithm, a specific technical calculation, or a technological mechanism that controls preparation equipment or otherwise improves store technology. Claims 5 and 12 merely specify that the pickup entity or third party may be a pickup service provider, deliverer, or non-human entity. These limitations merely identify the type of participant that performs the pickup or restrict the abstract process to a particular field of use. Although the claims refer to a non-human entity, they do not recite any particular robot, autonomous vehicle, control system, navigation system, or technical operation of such an entity. Claims 7 and 16 merely specify types of information associated with the user, such as a username, phone number, email address, physical address, order identifier, or transaction identifier. These limitations merely define the type of identifying data collected, stored, or associated with the commercial transaction and do not improve the operation of the underlying computer technology. Claims 8 and 17 merely receive location information, determine an estimated arrival time from the location information, and communicate the estimated arrival time to the store. The location information is merely additional input data; determining the ETA applies the commercial arrival coordination rule; and transmitting the ETA merely communicates the resulting information. The claims do not recite an improved GPS receiver, location-detection process, route-generation technique, or ETA-calculation technology. Claim 13 merely receives order-status information from the store and communicates that information to the user device. These limitations perform routine receipt and transmission of commercial status information and do not recite an improved communication protocol or messaging architecture. Claim 14 merely specifies that the communicated commercial status is a ready, processing, or waiting state. Accordingly, dependent claims 2-5, 7-14, and 16-20 merely add further commercial information, participants, timing criteria, scheduling rules, identifying data, status categories, and information-transmission functions to the abstract pickup-order coordination process and do not add an inventive concept and do not amount to significantly more than the judicial exception.
When viewed as an ordered combination, the additional elements of claims 2-5, 7-14, and 16-20 merely instruct to implement the abstract idea using generic computer components to collect, store, represent, and display information. The claims do not recite any unconventional arrangement of elements, nor do they effect an improvement to computer functionality or another technical field and therefore fail to integrate the abstract concept into a practical application and it is recited at a high level of generality and does not integrate the judicial exception into a practical application.
The Examiner has therefore determined that no additional element, or combination of additional claims elements is/are sufficient to ensure the claim(s) amount to significantly more than the abstract idea identified above (Step 2B: NO).
Therefore, claims 1-20 are not eligible subject matter under 35 USC 101.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-5, 9-11, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Pub. 20200410421 (“Nelson”) in view of U.S. Pub. 20220156696 (“Chopra”) in view of U.S. Pub. 20160292664 (“Gilfoyle”).
As per claims 1, Nelson discloses, system comprising: one or more processors; and one or more non-transitory computer-readable media storing instructions executable by the one or more processors, wherein the instructions, when executed, cause the system to perform operations comprising (“storage device 406 is capable of providing mass storage for the computing device 400. In some implementations, the storage device 406 may be or contain a computer-readable medium, such as a floppy disk device, a hard disk device, an optical disk device, or a tape device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations. A computer program product can be tangibly embodied in an information carrier. The computer program product may also contain instructions that, when executed, perform one or more methods, such as those described above. The computer program product can also be tangibly embodied in a computer- or machine-readable medium, such as the memory 404, the storage device 406, or memory on the processor 402”) (0095):
receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store (Examiner interprets that a online drive-up order corresponds to the claimed first pickup order; the customer who travels to the store corresponds to the first pickup entity; and store 106 corresponds to the claimed store. The first time point is the time at which the first order is placed or received) (“The server system 116 can facilitate fulfillment of the order by providing details of the order, such as ordered items, identity of the user, an order number, time that the order was placed, etc. to one or more computing devices located at a fulfillment center such as a store 106. For example, the store 106 can be part of a chain of affiliated stores associated with a retailer and the server system 116 can be a server system associated with the retailer. Upon receiving an on-line order from the user, the server system 116 can identify the store 106 as an appropriate fulfillment location for the order based on information such as, an indication of a preferred location for fulfillment indicated by the user at the mobile device 102 or another computing device, a current location of the mobile device 102, another location associated with the user (e.g., home or work address information entered by the user into a customer profile), based on item availability (e.g., by identifying a store where all or a majority of the items in the order are in stock), or based on a combination of these and one or more other factors … At the time of placing the order, or at a different time, such as when logging into the dedicated application, the user of the mobile device 102 can indicate a desired order fulfillment method for the order. For example, the user can specify that the order is for drive-up fulfillment. A drive-up fulfillment allows the user to drive to a fulfillment location, such as a retail store location, a warehouse, or another location where an employee of the retailer can meet the user at the user's vehicle 104, verify that the user is receiving the proper order, and provide the items to the user without the user being required to exit his vehicle. For example, the user can travel to the store 106, park in a designated area of the parking lot of the store 106, notify an employee that they have arrived”) (0020-0022);
receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store (Examiner interprets that The word “later” establishes that the second order is made at a second time point after the first time point. Because both orders are associated with the same customer, both are associated with the same first pickup entity. The surrounding disclosure concerns fulfillment at store 106; thus, both drive-up orders are directed to the same store) (“multiple active orders can be associated with a single customer. For example, a customer may place a first order for drive-up fulfillment and later realize that they would like to purchase additional items and make a second order for drive-up fulfillment. The field 272 indicates a second active order associated with the customer. The field 272 includes a checkbox 274 that functions in a similar manner to the checkbox 262. For example, the employee can select both checkboxes 262 and 274 to take actions with respect to both orders for the customer. The sub-field 276 nested under the field 272 indicates that the second order is located at storage location “SD-A023,” which can be, for example, an indication of bin A023 at a secondary staging area (e.g., for use when the front of store staging area is full, or a staging area for refrigerated and/or frozen items). The sub-field 276 includes an indicator 278 indicating that there are four bags for the second order located at storage bin SD-A023”) (0078),
determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order are to be grouped together as a first batched order (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets that Nelson supplies the pickup-entity information, such as the customer identifier, customer account, and vehicle information, that associates the two orders with the same customer. Nelson also teaches joint treatment of those orders i.e. organizes active orders under a customer identifier and permits an employee to select and take action on one or more orders associated with that customer. Nelson specifically permits both the first and second orders to be selected and acted upon together) (“the employee can select the order listing 132 (or another order listing) to view details on the associated order and/or other orders associated with the user. For example, upon the employee selecting the order listing 132 displayed as part of the user interface 120, the computing device 118 displays the user interface 248 containing details on active orders placed by Cindy L. … user interface 248 indicates that the customer indicated in the header 250 has arrived and includes a timer 254 indicating the amount of time that has elapsed since the customer has arrived. In some implementations, prior to arrival of the customer, the field 252 will include an indicator of “order placed” or “on the way” to indicate the customer's status. For example, the field 252 can indicate that the customer is on the way and the timer 254 can indicate an ETA for the customer. The field 252 further includes vehicle identification information for the customer to allow the employee to more easily identify the customer's vehicle when bringing the customer's order items to the drive-up fulfillment location in the parking lot of the store 106. The field 252 further includes an icon 258 indicating that the order(s) for the customer are drive-up fulfillment orders (rather than in-store pickup, delivery, etc.)”) (0073-0075, 0078);
receiving first location data from a first computing device associated with the first pickup entity (Examiner interprets that Nelson describes receiving location information from customer mobile device 102, including location information obtained by a GPS or other location-detection unit. The server periodically receives updated location information while the customer travels to store 106) (“server system 116 can also provide information on an estimated time of arrival and/or an estimated time until arrival for the user. For example, the mobile device 102 can calculate an estimated time until arrival for the user based on the estimated time for traversing the route 110 and provide this information to the server system 116 which can then provide the estimated time until arrival information to the computing device 118. As another example, the server system 116 can receive location information from the mobile device 102 and use this location information to calculate an estimated time until arrival for the user. For example, the user can give the dedicated application permission to access location information for the mobile device 102. A GPS unit or other location detection unit of the mobile device 102 can regularly determine the location for the mobile device 102. At the time of indicating to the server system 116 that the user has begun to travel along the route 110 to the store 106, the mobile device 102 can also indicate the current location of the mobile device 102. The server system 116 can then use either an internal time estimation routine, or communicate with an external routing system to identify an estimated time required for the user to travel from the current location of the mobile device 102 to the store 106 …”) (0030-0031);
determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store (Examiner interprets that the system calculates an ETA from customer-device location data. The resulting ETA indicates when the customer - the first pickup entity - will arrive at the store i.e. Nelson describes calculating an estimated time until arrival from the current location of mobile device 102 to store 106, either at the mobile device, at server system 116, or through an external routing system. Nelson also recalculates the estimated arrival time when updated location information is received) (“provide information on an estimated time of arrival and/or an estimated time until arrival for the user. For example, the mobile device 102 can calculate an estimated time until arrival for the user based on the estimated time for traversing the route 110 and provide this information to the server system 116 which can then provide the estimated time until arrival information to the computing device 118. As another example, the server system 116 can receive location information from the mobile device 102 and use this location information to calculate an estimated time until arrival for the user. For example, the user can give the dedicated application permission to access location information for the mobile device 102. A GPS unit or other location detection unit of the mobile device 102 can regularly determine the location for the mobile device 102. At the time of indicating to the server system 116 that the user has begun to travel along the route 110 to the store 106, the mobile device 102 can also indicate the current location of the mobile device 102. The server system 116 can then use either an internal time estimation routine, or communicate with an external routing system to identify an estimated time required for the user to travel from the current location of the mobile device 102 to the store 106 using any one of many known techniques … user travels along the route 110 (or another route) to the store 106, the server system 116 can periodically receive updated location information from the mobile device 102 (e.g., by periodically querying the dedicated application running on the mobile device 102 for current location information for the mobile device 102). Each time the server system 116 receives updated location information for the mobile device 102, the server system 116 can calculate or otherwise identify (e.g., by communicating with the external routing system) an updated estimated time until arrival for the user, based on the new location information. The server system 116 can then provide the updated estimated time until arrival for the user to the computing device 118”) (0030-0031);
and sending a first message to a store computing device associated with the store, the first message being indicative of the first estimated arrival time and the first batched order associated with the first pickup entity (Examiner notes that the underlined limitation is disclosed by another prior art. Nelson sends a notification to store computing device 118 that includes the customer ETA, a customer identifier, an order identifier, fulfillment type, and other order information) (“computing device 118 can include additional information such as the ETA for the user, an identifier for the user (e.g., name, user id, customer number, etc.), an identifier for the order (e.g., an order number), information on the type of fulfillment for the order (e.g., drive-up fulfillment or in-store pickup fulfillment) and/or other information associated with the order. As discussed above, the server system 116 can communicate directly with the computing device 118 via the network 114 or, in some implementations, can communicate with a central computer located at the store 106 which in turn relays information to the computing device 118 … esponse to receiving the notification that the user has begun to travel toward the store 106, the computing device 118 causes the user interface 204 to display a notification to the employee. The computing device 118 can also provide audio (e.g., ringing, text to speech) or tactile (e.g., vibration) output to notify the employee that the user is on the way. In the example depicted in FIG. 2B, the user interface 204 is displaying a lock screen for the computing device 118. The computing device 118 can provide a notification 206 on the lock screen that indicates that a new user is on the way to the store 106. The notification 206 includes an indicator 208 that a guest is on the way (i.e., the user has begun to travel toward the store 106). The notification 206 further includes an order identifier 210 that includes an order number for the user's order and an indicator 212 of the estimated time until the user arrives at the store 106”) (0040-0041).
Nelson specifically doesn’t disclose, are to be grouped together as a first batched order, however Chopra discloses, are to be grouped together as a first batched order (Examiner interprets that describes receiving order, courier, merchant, timestamp, and location information and using that information to batch orders and determine courier pickup routes, applies a pairing algorithm to a plurality of received orders and subsequent orders, and expressly describes multiple orders offered to the same courier for pickup i.e. Customer mobile device 102 is the claimed first computing device associated with the first pickup entity. The GPS or other detected location transmitted by that device corresponds to the first location data) (“Various customers, merchants, and couriers may transmit information related to one or more orders to the servers 312 or 314 via corresponding client devices. As previously described, such information may include order information, payment information, activity updates, timestamps, location information, or other appropriate electronic information. The system may utilize this transmitted information to batch orders and determine optimal routes to couriers for pickup and delivery of order for perishable goods”) (0068, 0109-0111),
the first message being indicative of the first estimated arrival time and the first batched order associated with the first pickup entity (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets that transmitting an order pairing to a merchant device and transmitting the predicted courier-arrival ETA to the merchant device) (“a predicted ETA for order delivery 232 may be provided to the customer device 620. As another example, at step 605, the predicted ETA for order ready 218 may be provided to the courier device 624 to notify the courier that it is ready for pickup. As a further example, at 607, the predicted ETA for arrival at merchant 226 may be provided to the merchant device 624 to notify the merchant when to expect a courier to arrive … the order pairing may be transmitted to a customer device 620 to notify the customer of information corresponding to the courier, such as identification, contact information, etc. In some embodiments, the order pairing may be transmitted to the courier device 622 to notify the courier of information corresponding to the merchant and/or customer, such as location, contact information, order information, etc. In some embodiments, the order pairing may be transmitted to the merchant device 624 to notify the merchant of information corresponding to the customer and/or courier, including contact information”) (0108-0110).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention to receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store, receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store, determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order, receiving first location data from a first computing device associated with the first pickup entity, determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store, and sending a first message to a store computing device associated with the store, as disclosed by Nelson, are to be grouped together as a first batched order, as taught by Chopra for the purpose apply batching technique to same-customer pickup orders so that the store could coordinate preparation and handoff of all orders associated with the arriving pickup entity, thereby reducing redundant handling, avoiding separate handoffs, and decreasing pickup waiting time.
Nelson specifically doesn’t disclose, the first message being indicative of the first estimated arrival time, however Gilfoyle discloses, the first message being indicative of the first estimated arrival time (Examiner interprets states that the customer device may calculate the ETA and transmit the ETA and/or customer location to the vendor “with the order.” i.e. carrying ETA information together with the corresponding order information in a vendor-directed transmission) (“the location of the customer is also transmitted to the vendor. Once the order and customer location is received by the vendor, a vendor data processing system calculates as ETA for the customer. In another embodiment, the customer device calculates the ETA based upon customer location and transmits the ETA and/or the customer location to the vendor with the order. The ETA for the customer is based upon the geographic location of the customer at the time of placing the order, and the physical location of the vendor's place of business. Other factors, such as current traffic levels and transit speeds may also be taken into consideration when calculating ETA” and “the order, location and/or calculated ETA and any subsequent updated information may be transmitted directly to the system located with the specified vendor. Alternatively, in the case of e.g. a franchised business with multiple locations, the order, location and/or calculated ETA and any subsequent updated information may be transmitted to a central data processing system, e.g. at a franchise headquarters, that thereafter transmits said information to a system located at the relevant vendor's place of business”) (0051 and 0068).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention to receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store, receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store, determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order, receiving first location data from a first computing device associated with the first pickup entity, determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store, and sending a first message to a store computing device associated with the store, as disclosed by Nelson, are to be grouped together as a first batched order, as taught by Gilfoyle for the purpose to calculate ETA information to a vendor with the associated order and transmitting the order and ETA directly or indirectly to a computing system at the relevant vendor location to enable store personnel to identify the orders associated with the arriving pickup entity and determine when those orders should be prepared or retrieved thus improve preparation and pickup coordination.
As per claims 2, 9 and 18, Nelson discloses, receiving a third pickup order made at a third time point associated with a second user, the third pickup order being directed to the store (Examiner interprets Nelson’s teaching concerning a first order and later second order as generally applicable to each customer using the multi-customer fulfillment system. Thus, the first order associated with another customer corresponds to the claimed third order associated with the second user) (“user interface 120 includes a user selectable control 122 that allows the employee to view all arriving orders (e.g., orders for which the user is on the way). The employee can select the control 122 by, for example, using a touch screen interface of the computing device 118 or one or more other input devices of or in communication with the computing device 118. The user interface 120 further includes a control 124 to allow the employee to view all placed orders … n order listing 136 indicating that a user named “Brent F.” is estimated to arrive at the store 106 in 26 minutes and includes an icon 138 indicating that Brent F. has selected in-store pickup order fulfillment. In some implementations, in place of or in addition to the indication of an estimated time until arrival, each order listing can include a time indicator indicating the predicated time of arrival for the customer (e.g., 3:15 pm). In some implementations, the order listings in the list 126 can include less or more details with respect to each order) (0034-0036, 0078);
receiving a fourth pickup order made at a fourth time point associated with the second user, the fourth pickup order being directed to the store (Examiner interprets the term “later” establishes a different, subsequent time point. Applying Nelson’s same-customer multiple-order teaching to another customer in Nelson’s multi-customer system yields the claimed fourth order associated with the second user) (“multiple active orders can be associated with a single customer. For example, a customer may place a first order for drive-up fulfillment and later realize that they would like to purchase additional items and make a second order for drive-up fulfillment. The field 272 indicates a second active order associated with the customer. The field 272 includes a checkbox 274 that functions in a similar manner to the checkbox 262. For example, the employee can select both checkboxes 262 and 274 to take actions with respect to both orders for the customer. The sub-field 276 nested under the field 272 indicates that the second order is located at storage location “SD-A023,” which can be, for example, an indication of bin A023 at a secondary staging area (e.g., for use when the front of store staging area is full, or a staging area for refrigerated and/or frozen items). The sub-field 276 includes an indicator 278 indicating that there are four bags for the second order located at storage bin SD-A023”) (0078);
grouping the third pickup order and the fourth pickup order as a second batched order associated with the second user (Examiner notes that underlined limitation is disclosed by another prior art. Examiner interprets Nelson supplies association and common handling of multiple orders belonging to one customer i.e. Nelson groups multiple active orders under the customer identifier and allows the employee to select and act on both same-customer orders together) (“user interface 248 that can be displayed by the computing device 118 in response to selection of the order listing 132 (FIG. 2I) by the employee. For example, the employee can select the order listing 132 (or another order listing) to view details on the associated order and/or other orders associated with the user. For example, upon the employee selecting the order listing 132 displayed as part of the user interface 120, the computing device 118 displays the user interface 248 containing details on active orders placed by Cindy L … multiple active orders can be associated with a single customer. For example, a customer may place a first order for drive-up fulfillment and later realize that they would like to purchase additional items and make a second order for drive-up fulfillment. The field 272 indicates a second active order associated with the customer. The field 272 includes a checkbox 274 that functions in a similar manner to the checkbox 262. For example, the employee can select both checkboxes 262 and 274 to take actions with respect to both orders for the customer. The sub-field 276 nested under the field 272 indicates that the second order is located at storage location “SD-A023,” which can be, for example, an indication of bin A023 at a secondary staging area (e.g., for use when the front of store staging area is full, or a staging area for refrigerated and/or frozen items). The sub-field 276 includes an indicator 278 indicating that there are four bags for the second order located at storage bin SD-A023”) (0073-0078);
receiving second location data from a second computing device associated with the second user (Examiner interprets that Nelson’s location-acquisition process is not limited to one particular named customer. In Nelson’s multi-customer system, the mobile device of another customer corresponds to the claimed second computing device, and its transmitted location corresponds to the second location data) (“provide information on an estimated time of arrival and/or an estimated time until arrival for the user. For example, the mobile device 102 can calculate an estimated time until arrival for the user based on the estimated time for traversing the route 110 and provide this information to the server system 116 which can then provide the estimated time until arrival information to the computing device 118. As another example, the server system 116 can receive location information from the mobile device 102 and use this location information to calculate an estimated time until arrival for the user. For example, the user can give the dedicated application permission to access location information for the mobile device 102. A GPS unit or other location detection unit of the mobile device 102 can regularly determine the location for the mobile device 102. At the time of indicating to the server system 116 that the user has begun to travel along the route 110 to the store 106, the mobile device 102 can also indicate the current location of the mobile device 102. The server system 116 can then use either an internal time estimation routine, or communicate with an external routing system to identify an estimated time required for the user to travel from the current location of the mobile device 102 to the store 106 using any one of many known techniques … user travels along the route 110 (or another route) to the store 106, the server system 116 can periodically receive updated location information from the mobile device 102 (e.g., by periodically querying the dedicated application running on the mobile device 102 for current location information for the mobile device 102). Each time the server system 116 receives updated location information for the mobile device 102, the server system 116 can calculate or otherwise identify (e.g., by communicating with the external routing system) an updated estimated time until arrival for the user, based on the new location information. The server system 116 can then provide the updated estimated time until arrival for the user to the computing device 118”) (0030-0031);
determining a second estimated arrival time of the second user based at least in part on the second location data, the second estimated arrival time being indicative of when the second user will arrive at the store (Examiner notes that underlined limitation is disclosed by another prior art. Examiner interprets Nelson expressly teaches the claimed location-based second ETA i.e. Nelson calculates the estimated travel time from the current mobile-device location to store 106 and updates the ETA when new location information is received and also Nelson displays different ETAs for different users) (0033-0031, 0035-0036);
and sending a second message to the store computing device associated with the store, the second message being indicative of the second batched order associated with the second user, the second estimated arrival time, and that the second estimated arrival time is earlier than the first estimated arrival time (Examiner notes that underlined limitation is disclosed by another prior art. Examiner interprets that Nelson supplies the store-directed message and multi-user ETA information i.e. Nelson sends a notification to store computing device 118 containing ETA, customer identifier, order identifier, fulfillment type, and other order information and also provides the store employee with a multi-customer display containing respective ETAs) (“network architecture 300 includes a number of client devices 302-308 communicably connected to one or more server systems 312 and 314 by a network 310. In some embodiments, server systems 312 and 314 include one or more processors and memory. The processors of server systems 312 and 314 execute computer instructions (e.g., network computer program code) stored in the memory to perform functions of a network data exchange server. In various embodiments, the functions of the network data exchange server may include routing real-time, on-demand, delivery of perishable goods, and/or predicting and dynamically updating estimated time of arrivals (ETAs) for such deliveries”) (0040-0041, 0034-0036).
Nelson specifically doesn’t disclose, as a second batched order associated with the second user and the second message being indicative of the second batched order associated with the second user, however Chopra discloses, as a second batched order associated with the second user (Examiner interprets Chopra teaches using order, courier, merchant, timestamp, and location information to batch orders and also teaches offering multiple orders to one courier for pickup) (“Various customers, merchants, and couriers may transmit information related to one or more orders to the servers 312 or 314 via corresponding client devices. As previously described, such information may include order information, payment information, activity updates, timestamps, location information, or other appropriate electronic information. The system may utilize this transmitted information to batch orders and determine optimal routes to couriers for pickup and delivery of order for perishable goods”) (0068, 0109-0111),
the second message being indicative of the second batched order associated with the second user (Examiner interprets Chopra supplies the second batched-order or order-pairing information i.e. transmits order-pairing information to a merchant device and transmits predicted merchant-arrival ETA information to the merchant device) (0108-0110).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention to receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store, receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store, determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order, receiving first location data from a first computing device associated with the first pickup entity, determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store, and sending a first message to a store computing device associated with the store, as disclosed by Nelson, as a second batched order associated with the second user and the second message being indicative of the second batched order associated with the second user, as taught by Chopra for the purpose apply batching technique to same-customer pickup orders so that the store could coordinate preparation and handoff of all orders associated with the arriving pickup entity, thereby reducing redundant handling, avoiding separate handoffs, and decreasing pickup waiting time.
Nelson specifically doesn’t disclose, the second estimated arrival time being indicative of when the second user will arrive at the store, determining that the second estimated arrival time is earlier than the first estimated arrival time, the second estimated arrival time, and that the second estimated arrival time is earlier than the first estimated arrival time, however Gilfoyle discloses, the second estimated arrival time being indicative of when the second user will arrive at the store (Examiner interprets Gilfoyle similarly calculates a customer ETA to the vendor based on geographic location) (“the location of the customer is also transmitted to the vendor. Once the order and customer location is received by the vendor, a vendor data processing system calculates as ETA for the customer. In another embodiment, the customer device calculates the ETA based upon customer location and transmits the ETA and/or the customer location to the vendor with the order. The ETA for the customer is based upon the geographic location of the customer at the time of placing the order, and the physical location of the vendor's place of business. Other factors, such as current traffic levels and transit speeds may also be taken into consideration when calculating ETA”) (0051);
determining that the second estimated arrival time is earlier than the first estimated arrival time (Examiner interprets Gilfoyle generates a queue of multiple customers and prioritizes their orders using customer ETA. Its table compares respective customer ETAs, preparation durations, start times, and completion times) (“vendor data processing system generates a queue of all pending orders, where the orders are prioritized according to certain criteria. The queue facilitates processing of orders. The queue preferably is made available to the staff of the vendor through, e.g. a graphical user interface (GUI), in order to provide structure and guidance concerning the priority of pending orders. In one embodiment, the queue is arranged chronologically, and may be sorted and prioritized by a variety of criteria, such as time the order is placed, estimated time of order completion or time that the vendor should start fulfilling the order. Additional information may also be contained in and used to sort and prioritize the queue, such as time to complete the order and client ETA … he table is ordered according to estimated time of order completion, but may also be ordered according to other criteria, such as Order Start Time, to conveniently alerts the vendor when staff should initiate filling an order. Clients 1 and 3 are have physically placed their order at the vendor's place of business, and are waiting for the vendor to fulfill their orders. Clients 2, 4, 5 and 6 have placed their orders remotely according to an embodiment of the present invention, and are on route to the vendor's place of business to collect their orders. Although clients 2, 4 and 5 placed their orders earlier than clients 1 and 3, due to the calculated ETA for the remote clients, their orders do not automatically receive a higher priority in the order queue. The vendor is then able to expeditiously fulfill orders based upon anticipated arrival time of customers, rather than on when the order is initially placed. The ETA of client 6 precedes the anticipated order completion time, even if the order is processed immediately. In such a scenario, client 6 will be required to wait at the vendor's place of business, and may be directed to a waiting area”) (0052-0054);
the second estimated arrival time, and that the second estimated arrival time is earlier than the first estimated arrival time (Examiner interprets Gilfoyle supplies transmission of ETA information with the corresponding order. A message displaying the second batch with an ETA that precedes the first batch’s ETA, or positioning the second batch ahead of the first in an ETA-ordered display, is reasonably “indicative” that the second ETA is earlier) (0051, 0068).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention to receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store, receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store, determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order, receiving first location data from a first computing device associated with the first pickup entity, determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store, and sending a first message to a store computing device associated with the store, as disclosed by Nelson, the second estimated arrival time being indicative of when the second user will arrive at the store, determining that the second estimated arrival time is earlier than the first estimated arrival time, the second estimated arrival time, and that the second estimated arrival time is earlier than the first estimated arrival time, as taught by Gilfoyle for the purpose to calculate ETA information to a vendor with the associated order and transmitting the order and ETA directly or indirectly to a computing system at the relevant vendor location to enable store personnel to identify the orders associated with the arriving pickup entity and determine when those orders should be prepared or retrieved thus improve preparation and pickup coordination.
As per claims 3, 10, and 19, Nelson discloses, and sending a third message to the store computing device associated with the store, the third message including the order queue (Examiner notes that underlined limitation is disclosed by another prior art. Examiner interprets Nelson’s server communicates order and ETA information to store computing device 118, which displays the multi-order list to the employee) (“Upon determining that the user has begun to travel toward the store 106 (e.g., based on location information collected by the mobile device 102 or based on user interaction with the user interface control 112), the mobile device 102 can communicate with one or more computing devices located at and affiliated with the store 106, either directly through the network 114 or by communicating with the server system 116 which in turn communicates appropriate information and instructions to the one or more computing devices located at the store 106. For example, an employee of the store 106 can use the computing device 118, which can receive information relevant to the order from the server system 116. The mobile device 102 can communicate with the server system 116 over the network 114 to indicate to the server system 116 that the user has begun to travel toward the store 106. The server system 116 can then provide a communication to the computing device 118 of the store employee to indicate that the user of the mobile device 102 is on the way … server system 116 can provide additional information along with this notification or prior to sending the notification that the user is on the way. For example, the server system 116 can access user profile information to identify a make and model for the user's vehicle 104, a color for the user's vehicle 104, and/or other identifying information for the user's vehicle 104 (such as a whole or partial license plate number) and provide this vehicle identification information to the computing device 118 to allow the employee to more easily identify the user's vehicle 104 when the user has arrived at the designating drive-up fulfillment location at the store 106. The server system 116 can store this vehicle identification information as part of a customer profile for the user or the user can provide the information at the time of placing the order (e.g., in situations where the user is part of a multi-car family and may use different vehicles on different occasions). In some implementations, the user can be prompted to enter such vehicle identification information at the time of placing the order, at the time of selecting drive-up fulfillment for the order, or at the time of indicating that they are on their way.”) (0028-0029, 0040-0041).
Nelson specifically doesn’t disclose, the order queue listing the first batched order and the second batched order, however Chopra discloses, generating an order queue, the order queue listing the first batched order and the second batched order based at least in part on the first estimated arrival time and the second estimated arrival time (Examiner notes that underlined limitation is disclosed by another prior art. Examiner interprets Chopra converts the associated individual orders into first and second batched orders) (“Various customers, merchants, and couriers may transmit information related to one or more orders to the servers 312 or 314 via corresponding client devices. As previously described, such information may include order information, payment information, activity updates, timestamps, location information, or other appropriate electronic information. The system may utilize this transmitted information to batch orders and determine optimal routes to couriers for pickup and delivery of order for perishable goods”) (0068, 0109-0111).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention to receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store, receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store, determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order, receiving first location data from a first computing device associated with the first pickup entity, determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store, and sending a first message to a store computing device associated with the store, as disclosed by Nelson, the order queue listing the first batched order and the second batched order, as taught by Chopra for the purpose apply batching technique to same-customer pickup orders so that the store could coordinate preparation and handoff of all orders associated with the arriving pickup entity, thereby reducing redundant handling, avoiding separate handoffs, and decreasing pickup waiting time.
Nelson specifically doesn’t disclose, generating an order queue, based at least in part on the first estimated arrival time and the second estimated arrival time, however Gilfoyle discloses, generating an order queue (Examiner interprets that the vendor data-processing system generates a queue of all pending orders and makes the queue available to vendor staff through a GUI) (“the location of the customer is also transmitted to the vendor. Once the order and customer location is received by the vendor, a vendor data processing system calculates as ETA for the customer. In another embodiment, the customer device calculates the ETA based upon customer location and transmits the ETA and/or the customer location to the vendor with the order. The ETA for the customer is based upon the geographic location of the customer at the time of placing the order, and the physical location of the vendor's place of business. Other factors, such as current traffic levels and transit speeds may also be taken into consideration when calculating ETA … vendor data processing system generates a queue of all pending orders, where the orders are prioritized according to certain criteria. The queue facilitates processing of orders. The queue preferably is made available to the staff of the vendor through, e.g. a graphical user interface (GUI), in order to provide structure and guidance concerning the priority of pending orders. In one embodiment, the queue is arranged chronologically, and may be sorted and prioritized by a variety of criteria, such as time the order is placed, estimated time of order completion or time that the vendor should start fulfilling the order”) (0051-0052);
based at least in part on the first estimated arrival time and the second estimated arrival time (Examiner interprets Gilfoyle prioritizes the pending-order queue according to customer ETA, estimated completion time, time to complete, or order-start time) (“vendor data processing system generates a queue of all pending orders, where the orders are prioritized according to certain criteria. The queue facilitates processing of orders. The queue preferably is made available to the staff of the vendor through, e.g. a graphical user interface (GUI), in order to provide structure and guidance concerning the priority of pending orders. In one embodiment, the queue is arranged chronologically, and may be sorted and prioritized by a variety of criteria, such as time the order is placed, estimated time of order completion or time that the vendor should start fulfilling the order. Additional information may also be contained in and used to sort and prioritize the queue, such as time to complete the order and client ETA … he table is ordered according to estimated time of order completion, but may also be ordered according to other criteria, such as Order Start Time, to conveniently alerts the vendor when staff should initiate filling an order. Clients 1 and 3 are have physically placed their order at the vendor's place of business, and are waiting for the vendor to fulfill their orders. Clients 2, 4, 5 and 6 have placed their orders remotely according to an embodiment of the present invention, and are on route to the vendor's place of business to collect their orders. Although clients 2, 4 and 5 placed their orders earlier than clients 1 and 3, due to the calculated ETA for the remote clients, their orders do not automatically receive a higher priority in the order queue. The vendor is then able to expeditiously fulfill orders based upon anticipated arrival time of customers, rather than on when the order is initially placed. The ETA of client 6 precedes the anticipated order completion time, even if the order is processed immediately. In such a scenario, client 6 will be required to wait at the vendor's place of business, and may be directed to a waiting area”) (0052-0054).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention to receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store, receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store, determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order, receiving first location data from a first computing device associated with the first pickup entity, determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store, and sending a first message to a store computing device associated with the store, as disclosed by Nelson, generating an order queue, based at least in part on the first estimated arrival time and the second estimated arrival time, as taught by Gilfoyle for the purpose to calculate ETA information to a vendor with the associated order and transmitting the order and ETA directly or indirectly to a computing system at the relevant vendor location to enable store personnel to identify the orders associated with the arriving pickup entity and determine when those orders should be prepared or retrieved thus improve preparation and pickup coordination.
As per claims 4, 11, and 20, Nelson discloses, determining a first preparation time for the first batched order (Examiner notes that underlined limitation is disclosed by another prior art. Examiner interprets Nelson discloses preparation and fulfillment of customer orders, but does not expressly calculate a preparation duration for a batched order) (“Upon determining that the user has begun to travel toward the store 106 (e.g., based on location information collected by the mobile device 102 or based on user interaction with the user interface control 112), the mobile device 102 can communicate with one or more computing devices located at and affiliated with the store 106, either directly through the network 114 or by communicating with the server system 116 which in turn communicates appropriate information and instructions to the one or more computing devices located at the store 106. For example, an employee of the store 106 can use the computing device 118, which can receive information relevant to the order from the server system 116. The mobile device 102 can communicate with the server system 116 over the network 114 to indicate to the server system 116 that the user has begun to travel toward the store 106. The server system 116 can then provide a communication to the computing device 118 of the store employee to indicate that the user of the mobile device 102 is on the way … server system 116 can provide additional information along with this notification or prior to sending the notification that the user is on the way. For example, the server system 116 can access user profile information to identify a make and model for the user's vehicle 104, a color for the user's vehicle 104, and/or other identifying information for the user's vehicle 104 (such as a whole or partial license plate number) and provide this vehicle identification information to the computing device 118 to allow the employee to more easily identify the user's vehicle 104 when the user has arrived at the designating drive-up fulfillment location at the store 106. The server system 116 can store this vehicle identification information as part of a customer profile for the user or the user can provide the information at the time of placing the order (e.g., in situations where the user is part of a multi-car family and may use different vehicles on different occasions). In some implementations, the user can be prompted to enter such vehicle identification information at the time of placing the order, at the time of selecting drive-up fulfillment for the order, or at the time of indicating that they are on their way.”) (0028-0029, 0040-0041).
Nelson specifically doesn’t disclose, for the first batched order, however Chopra discloses, for the first batched order (Examiner interprets Chopra tracks merchant preparation and order-ready events and coordinates courier arrival with order readiness) (“order placement 214 event may occur when the order is received at the merchant device. In some embodiments, the merchant may acknowledge the receipt of the order by transmitting a confirmation, which may trigger the order confirmation 216 event. Order confirmation 216 may signal that preparation of the order has begun by the merchant. In some embodiments, the period of time between order creation 212-A and order confirmation 216 is known as kitchen latency 240 …”) (0048-0054).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention to receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store, receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store, determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order, receiving first location data from a first computing device associated with the first pickup entity, determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store, and sending a first message to a store computing device associated with the store, as disclosed by Nelson, for the first batched order, as taught by Chopra for the purpose apply batching technique to same-customer pickup orders so that the store could coordinate preparation and handoff of all orders associated with the arriving pickup entity, thereby reducing redundant handling, avoiding separate handoffs, and decreasing pickup waiting time.
Nelson specifically doesn’t disclose, determining a first starting time based at least in part on the first estimated arrival time and the first preparation time, determining a second preparation time, determining a second starting time based at least in part on the second estimated arrival time and the second preparation time and updating the order queue based at least in part on the first starting time and the second starting time, however Gilfoyle discloses, determining a first starting time based at least in part on the first estimated arrival time and the first preparation time for the first batched order (Examiner notes that underlined limitation is disclosed by another prior art. Examiner interprets that Gilfoyle determines when the vendor should start fulfilling an order using the ETA and time required to complete the order. Table 1 expressly includes ETA, preparation duration, start time, and completion time) (“the location of the customer is also transmitted to the vendor. Once the order and customer location is received by the vendor, a vendor data processing system calculates as ETA for the customer. In another embodiment, the customer device calculates the ETA based upon customer location and transmits the ETA and/or the customer location to the vendor with the order. The ETA for the customer is based upon the geographic location of the customer at the time of placing the order, and the physical location of the vendor's place of business. Other factors, such as current traffic levels and transit speeds may also be taken into consideration when calculating ETA … vendor data processing system generates a queue of all pending orders, where the orders are prioritized according to certain criteria. The queue facilitates processing of orders. The queue preferably is made available to the staff of the vendor through, e.g. a graphical user interface (GUI), in order to provide structure and guidance concerning the priority of pending orders. In one embodiment, the queue is arranged chronologically, and may be sorted and prioritized by a variety of criteria, such as time the order is placed, estimated time of order completion or time that the vendor should start fulfilling the order”) (0051-0054);
determining a second preparation time for the second batched order (Examiner notes that underlined limitation is disclosed by another prior art. Examiner interprets Gilfoyle calculates or stores preparation durations for each of multiple different customer orders) (“vendor data processing system generates a queue of all pending orders, where the orders are prioritized according to certain criteria. The queue facilitates processing of orders. The queue preferably is made available to the staff of the vendor through, e.g. a graphical user interface (GUI), in order to provide structure and guidance concerning the priority of pending orders. In one embodiment, the queue is arranged chronologically, and may be sorted and prioritized by a variety of criteria, such as time the order is placed, estimated time of order completion or time that the vendor should start fulfilling the order. Additional information may also be contained in and used to sort and prioritize the queue, such as time to complete the order and client ETA … he table is ordered according to estimated time of order completion, but may also be ordered according to other criteria, such as Order Start Time, to conveniently alerts the vendor when staff should initiate filling an order. Clients 1 and 3 are have physically placed their order at the vendor's place of business, and are waiting for the vendor to fulfill their orders. Clients 2, 4, 5 and 6 have placed their orders remotely according to an embodiment of the present invention, and are on route to the vendor's place of business to collect their orders. Although clients 2, 4 and 5 placed their orders earlier than clients 1 and 3, due to the calculated ETA for the remote clients, their orders do not automatically receive a higher priority in the order queue. The vendor is then able to expeditiously fulfill orders based upon anticipated arrival time of customers, rather than on when the order is initially placed. The ETA of client 6 precedes the anticipated order completion time, even if the order is processed immediately. In such a scenario, client 6 will be required to wait at the vendor's place of business, and may be directed to a waiting area”) (0052-0054);
determining a second starting time based at least in part on the second estimated arrival time and the second preparation time for the second batched order (Examiner notes that underlined limitation is disclosed by another prior art. Examiner interprets Gilfoyle’s queue table assigns different order-start times based on each customer’s ETA and time to complete the respective order and applying the same calculation to the second batched order yields the claimed second starting time) (“vendor data processing system generates a queue of all pending orders, where the orders are prioritized according to certain criteria. The queue facilitates processing of orders. The queue preferably is made available to the staff of the vendor through, e.g. a graphical user interface (GUI), in order to provide structure and guidance concerning the priority of pending orders. In one embodiment, the queue is arranged chronologically, and may be sorted and prioritized by a variety of criteria, such as time the order is placed, estimated time of order completion or time that the vendor should start fulfilling the order. Additional information may also be contained in and used to sort and prioritize the queue, such as time to complete the order and client ETA … he table is ordered according to estimated time of order completion, but may also be ordered according to other criteria, such as Order Start Time, to conveniently alerts the vendor when staff should initiate filling an order. Clients 1 and 3 are have physically placed their order at the vendor's place of business, and are waiting for the vendor to fulfill their orders. Clients 2, 4, 5 and 6 have placed their orders remotely according to an embodiment of the present invention, and are on route to the vendor's place of business to collect their orders. Although clients 2, 4 and 5 placed their orders earlier than clients 1 and 3, due to the calculated ETA for the remote clients, their orders do not automatically receive a higher priority in the order queue. The vendor is then able to expeditiously fulfill orders based upon anticipated arrival time of customers, rather than on when the order is initially placed. The ETA of client 6 precedes the anticipated order completion time, even if the order is processed immediately. In such a scenario, client 6 will be required to wait at the vendor's place of business, and may be directed to a waiting area”) (0052-0054);
and updating the order queue based at least in part on the first starting time and the second starting time (Examiner interprets that the queue may be sorted according to the time the vendor should start fulfilling each order and may be ordered by “Order Start Time” to alert staff when fulfillment should begin i.e. Sorting or reordering queue entries according to their respective start times constitutes updating the queue based on the first and second starting times) (“vendor data processing system generates a queue of all pending orders, where the orders are prioritized according to certain criteria. The queue facilitates processing of orders. The queue preferably is made available to the staff of the vendor through, e.g. a graphical user interface (GUI), in order to provide structure and guidance concerning the priority of pending orders. In one embodiment, the queue is arranged chronologically, and may be sorted and prioritized by a variety of criteria, such as time the order is placed, estimated time of order completion or time that the vendor should start fulfilling the order. Additional information may also be contained in and used to sort and prioritize the queue, such as time to complete the order and client ETA … he table is ordered according to estimated time of order completion, but may also be ordered according to other criteria, such as Order Start Time, to conveniently alerts the vendor when staff should initiate filling an order. Clients 1 and 3 are have physically placed their order at the vendor's place of business, and are waiting for the vendor to fulfill their orders. Clients 2, 4, 5 and 6 have placed their orders remotely according to an embodiment of the present invention, and are on route to the vendor's place of business to collect their orders. Although clients 2, 4 and 5 placed their orders earlier than clients 1 and 3, due to the calculated ETA for the remote clients, their orders do not automatically receive a higher priority in the order queue. The vendor is then able to expeditiously fulfill orders based upon anticipated arrival time of customers, rather than on when the order is initially placed. The ETA of client 6 precedes the anticipated order completion time, even if the order is processed immediately. In such a scenario, client 6 will be required to wait at the vendor's place of business, and may be directed to a waiting area”) (0052-0054)
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention to receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store, receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store, determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order, receiving first location data from a first computing device associated with the first pickup entity, determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store, and sending a first message to a store computing device associated with the store, as disclosed by Nelson, determining a first starting time based at least in part on the first estimated arrival time and the first preparation time, determining a second preparation time, determining a second starting time based at least in part on the second estimated arrival time and the second preparation time and updating the order queue based at least in part on the first starting time and the second starting time, as taught by Gilfoyle for the purpose to calculate ETA information to a vendor with the associated order and transmitting the order and ETA directly or indirectly to a computing system at the relevant vendor location to enable store personnel to identify the orders associated with the arriving pickup entity and determine when those orders should be prepared or retrieved thus improve preparation and pickup coordination.
As per claims 5, Nelson discloses, wherein the first pickup entity comprises at least one of a pickup service provider, a deliverer, or a non-human entity (Examiner notes that underlined limitation is disclosed by another prior art. Examiner interprets Nelson’s principal embodiment uses the customer as the pickup entity, although it also recognizes delivery by an employee or third-party service) (“the user can specify that the order is for delivery. An employee of the retailer or a third-party service can travel to the user's home or another drop-off location designated by the user to deliver the items in the order to the user”) (0024).
8. Claims 6-8 and 12-17 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Pub. 20200410421 (“Nelson”) in view of U.S. Pub. 20220156696 (“Chopra”).
As per claims 6 and 15, Nelson discloses, method for managing multiple pickup orders, the method comprising (Examiner interprets that a network-based system and corresponding processes for managing drive-up and in-store pickup orders at a store. The server receives online orders, identifies the appropriate store, and provides order data to an employee computing device at that store) (“system 100 for facilitating order fulfillment for drive-up pickup by user's. In the system 100, a user, such as a customer who wishes to complete an online order for items by picking up the items using a drive-up service, can access a dedicated application executing on a mobile device 102”) (0017-0022):
receiving a first pickup order associated with a first user, the first pickup order being directed to a store (Examiner interprets Nelson describes receiving an online order from a user, identifying store 106 as the fulfillment location, and transmitting the order information to computing device 118 used by a store employee. Nelson further explains that the user may select drive-up fulfillment and travel to store 106 to receive the order) (“The server system 116 can facilitate fulfillment of the order by providing details of the order, such as ordered items, identity of the user, an order number, time that the order was placed, etc. to one or more computing devices located at a fulfillment center such as a store 106. For example, the store 106 can be part of a chain of affiliated stores associated with a retailer and the server system 116 can be a server system associated with the retailer. Upon receiving an on-line order from the user, the server system 116 can identify the store 106 as an appropriate fulfillment location for the order based on information such as, an indication of a preferred location for fulfillment indicated by the user at the mobile device 102 or another computing device, a current location of the mobile device 102, another location associated with the user (e.g., home or work address information entered by the user into a customer profile), based on item availability (e.g., by identifying a store where all or a majority of the items in the order are in stock), or based on a combination of these and one or more other factors … At the time of placing the order, or at a different time, such as when logging into the dedicated application, the user of the mobile device 102 can indicate a desired order fulfillment method for the order. For example, the user can specify that the order is for drive-up fulfillment. A drive-up fulfillment allows the user to drive to a fulfillment location, such as a retail store location, a warehouse, or another location where an employee of the retailer can meet the user at the user's vehicle 104, verify that the user is receiving the proper order, and provide the items to the user without the user being required to exit his vehicle. For example, the user can travel to the store 106, park in a designated area of the parking lot of the store 106, notify an employee that they have arrived”) (0020-0022);
receiving a second pickup order associated with the first user, the second pickup order being directed to the store (Examiner interprets that multiple active orders can be associated with one customer. A customer may place a first drive-up order and later place a second drive-up order for additional items. The second order is displayed as another active order for that same customer in the store employee interface i.e. the second pickup order and its association with the same first user. Because both are drive-up orders displayed and fulfilled in the store 106 workflow, the second order is directed to the same store) (“multiple active orders can be associated with a single customer. For example, a customer may place a first order for drive-up fulfillment and later realize that they would like to purchase additional items and make a second order for drive-up fulfillment. The field 272 indicates a second active order associated with the customer. The field 272 includes a checkbox 274 that functions in a similar manner to the checkbox 262. For example, the employee can select both checkboxes 262 and 274 to take actions with respect to both orders for the customer. The sub-field 276 nested under the field 272 indicates that the second order is located at storage location “SD-A023,” which can be, for example, an indication of bin A023 at a secondary staging area (e.g., for use when the front of store staging area is full, or a staging area for refrigerated and/or frozen items). The sub-field 276 includes an indicator 278 indicating that there are four bags for the second order located at storage bin SD-A023”) (0078),
grouping the first pickup order and the second pickup order as a first batched order associated with the first user (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets that Nelson’s employee interface is organized under a customer identifier and displays the customer’s active orders. The employee may select one or more orders associated with that customer and, specifically, may select both the first and second orders to take action on both orders) (“the employee can select the order listing 132 (or another order listing) to view details on the associated order and/or other orders associated with the user. For example, upon the employee selecting the order listing 132 displayed as part of the user interface 120, the computing device 118 displays the user interface 248 containing details on active orders placed by Cindy L. … user interface 248 indicates that the customer indicated in the header 250 has arrived and includes a timer 254 indicating the amount of time that has elapsed since the customer has arrived. In some implementations, prior to arrival of the customer, the field 252 will include an indicator of “order placed” or “on the way” to indicate the customer's status. For example, the field 252 can indicate that the customer is on the way and the timer 254 can indicate an ETA for the customer. The field 252 further includes vehicle identification information for the customer to allow the employee to more easily identify the customer's vehicle when bringing the customer's order items to the drive-up fulfillment location in the parking lot of the store 106. The field 252 further includes an icon 258 indicating that the order(s) for the customer are drive-up fulfillment orders (rather than in-store pickup, delivery, etc.)”) (0073-0075, 0078);
and sending a first message to a store computing device associated with the store, the first message being indicative of the first batched order associated with the first user (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets that Nelson’s server sends order information to computing device 118 used by the store employee. The information includes ordered items, user-identifying information, order number, pickup time, and fulfillment information. The employee device displays the customer’s active orders and permits joint action on selected orders) (“the server system 116 can identify the store 106 as an appropriate location for fulfilling the user's order. The server system 116 can transmit information on the order to a computing device 118 in the possession of, or being used by, an employee of the store 106. The computing device 118 can be a mobile computing device, such as, for example, a mobile phone, a tablet device, a touch screen computer, a laptop computer, a PDA, a smart watch, or other mobile device. In some implementations, the computing device 118 can be a non-mobile or semi-mobile device such as a server, a desktop computer, a cash register, a smart TV, or other computing device. The server system 116 can provide appropriate information for the order to the computing device 118 such as items in the order, identifying information for the user who placed the order, time the order was placed, a desired pickup time for the order (e.g., as indicated by the user at the time of placing the order), an order number, and other relevant information…”) (0021, 0073-0078).
Nelson specifically doesn’t disclose, as a first batched order associated with the first user, the first message being indicative of the first batched order associated with the first user, however Chopra discloses, as a first batched order associated with the first user (Examiner interprets that Chopra expressly teaches that information concerning customers, merchants, couriers, orders, timestamps, and locations may be used to batch orders. Chopra also describes a pairing algorithm operating on a plurality of received orders and multiple orders being offered for common pickup by one courier) (“Various customers, merchants, and couriers may transmit information related to one or more orders to the servers 312 or 314 via corresponding client devices. As previously described, such information may include order information, payment information, activity updates, timestamps, location information, or other appropriate electronic information. The system may utilize this transmitted information to batch orders and determine optimal routes to couriers for pickup and delivery of order for perishable goods”) (0068, 0109-0111),
the first message being indicative of the first batched order associated with the first user (Examiner interprets that Chopra transmits the order pairing to the merchant device and expressly teaches batch formation i.e. message containing identifiers for the constituent orders, their association with the same user, and data causing the store interface to present them together for common action reasonably indicates the batched order) (“a predicted ETA for order delivery 232 may be provided to the customer device 620. As another example, at step 605, the predicted ETA for order ready 218 may be provided to the courier device 624 to notify the courier that it is ready for pickup. As a further example, at 607, the predicted ETA for arrival at merchant 226 may be provided to the merchant device 624 to notify the merchant when to expect a courier to arrive … the order pairing may be transmitted to a customer device 620 to notify the customer of information corresponding to the courier, such as identification, contact information, etc. In some embodiments, the order pairing may be transmitted to the courier device 622 to notify the courier of information corresponding to the merchant and/or customer, such as location, contact information, order information, etc. In some embodiments, the order pairing may be transmitted to the merchant device 624 to notify the merchant of information corresponding to the customer and/or courier, including contact information”) (0108-0110, 0068).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention to receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store, receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store, determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order, receiving first location data from a first computing device associated with the first pickup entity, determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store, and sending a first message to a store computing device associated with the store, as disclosed by Nelson, as a first batched order associated with the first user, the first message being indicative of the first batched order associated with the first user, as taught by Chopra for the purpose by applying batching technique to same-customer pickup orders would formalize and automate the coordinated treatment thus allowing store personnel to identify, prepare, retrieve, and hand off the associated orders together thus to reduce redundant employee handling, avoid separate handoffs, and reduce the likelihood that the customer must wait for a later-added order.
As per claims 7 and 16, Nelson discloses, wherein the first user is associated with at least one of a username, a phone number, an email address, an address, an order identifier, or a transaction identifier (Examiner interprets Nelson discloses that the user logs into the order-fulfillment application using a user name or other identifier. Nelson further discloses transmitting to the store device a user identifier, such as a name, user ID, or customer number and an order identifier, such as an order number) (“user logs into the dedicated application by entering a user name or other identifier and a password. Alternatively, the user can log into the dedicated application by providing biometric information using one or more sensors of the mobile device 102 such as by scanning a fingerprint using a fingerprint scanner of the mobile device 102 or using a retina scanner of the mobile device 102 to scan the user's retina information. In some implementations, the user may be already logged into the dedicated application from a previous session”) (0018, 0040).
As per claims 8 and 17, Nelson discloses, receiving first location data from a first computing device associated with the first user (Examiner interprets Nelson’s customer mobile device corresponds to the first computing device associated with the first user. Its GPS or other detected location corresponds to the claimed first location data i.e. Nelson receives location information from customer mobile device 102. The location may be obtained by a GPS or another location-detection unit, and the server periodically receives updated locations while the user travels toward store 106) (“he mobile device 102 can calculate an estimated time until arrival for the user based on the estimated time for traversing the route 110 and provide this information to the server system 116 which can then provide the estimated time until arrival information to the computing device 118. As another example, the server system 116 can receive location information from the mobile device 102 and use this location information to calculate an estimated time until arrival for the user. For example, the user can give the dedicated application permission to access location information for the mobile device 102. A GPS unit or other location detection unit of the mobile device 102 can regularly determine the location for the mobile device 102. At the time of indicating to the server system 116 that the user has begun to travel along the route 110 to the store 106, the mobile device 102 can also indicate the current location of the mobile device 102 …”) (0030-0031);
and determining a first estimated arrival time of the first user or a third party based at least in part on the first location data, the first estimated arrival time being indicative of when the first user or the third party will arrive at the store (Examiner interprets Nelson calculates an estimated time from the current location of mobile device 102 to store 106, either at the mobile device, server system, or through an external routing system. Nelson recalculates the ETA from subsequently received locations and Nelson further calculates estimated time until arrival at store 106 expressly indicates when the first user will arrive at the store) (0030-0031);
wherein the first message is further indicative of the first estimated arrival time (Examiner interprets Nelson sends a notification to store computing device 118 containing the user ETA, user identifier, order identifier, fulfillment type, and associated order information) (“determining that the user has begun to travel toward the store 106, the server system 116 provides a notification to the computing device 118 to prompt the computing device 118 to provide a notification to the employee that the user is on the way via the user interface 204. The notification from the server system 116 communicated to the computing device 118 can include additional information such as the ETA for the user, an identifier for the user (e.g., name, user id, customer number, etc.), an identifier for the order (e.g., an order number), information on the type of fulfillment for the order (e.g., drive-up fulfillment or in-store pickup fulfillment) and/or other information associated with the order …”) (0040-0041).
As per claims 12, Nelson discloses, wherein the third party comprises at least one of a pickup service provider, a deliverer, or a non-human entity (Examiner notes that underlined limitation is disclosed by another prior art. Examiner interprets Nelson’s principal embodiment uses the customer as the pickup entity, although it also recognizes delivery by an employee or third-party service) (“the user can specify that the order is for delivery. An employee of the retailer or a third-party service can travel to the user's home or another drop-off location designated by the user to deliver the items in the order to the user”) (0024).
As per claims 13, Nelson discloses, receiving a fourth message from the store computing device associated with the store, the fourth message being indicative of a state of the first batched order (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets Nelson describes communication between store employee computing device 118 and server system 116 in the store-order-fulfillment environment. Nelson also contemplates store and server communications that produce notifications on the customer device) (“The server system 116 can facilitate fulfillment of the order by providing details of the order, such as ordered items, identity of the user, an order number, time that the order was placed, etc. to one or more computing devices located at a fulfillment center such as a store 106. For example, the store 106 can be part of a chain of affiliated stores associated with a retailer and the server system 116 can be a server system associated with the retailer. Upon receiving an on-line order from the user, the server system 116 can identify the store 106 as an appropriate fulfillment location for the order based on information such as, an indication of a preferred location for fulfillment indicated by the user at the mobile device 102 or another computing device, a current location of the mobile device 102, another location associated with the user (e.g., home or work address information entered by the user into a customer profile), based on item availability (e.g., by identifying a store where all or a majority of the items in the order are in stock), or based on a combination of these and one or more other factors … At the time of placing the order, or at a different time, such as when logging into the dedicated application, the user of the mobile device 102 can indicate a desired order fulfillment method for the order. For example, the user can specify that the order is for drive-up fulfillment. A drive-up fulfillment allows the user to drive to a fulfillment location, such as a retail store location, a warehouse, or another location where an employee of the retailer can meet the user at the user's vehicle 104, verify that the user is receiving the proper order, and provide the items to the user without the user being required to exit his vehicle. For example, the user can travel to the store 106, park in a designated area of the parking lot of the store 106, notify an employee that they have arrived”) (0020-0022),
and sending a fifth message to a first user device, the fifth message being indicative of the state of the first batched order (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets Nelson’s mobile device 102 corresponds to the first user device. The electronic notification sent to that device corresponds to the fifth message. “Sending” encompasses causing the user device to receive or display an electronic notification through the server and network) (“information collected at the first user's device (e.g., from user input or via a location detection unit such as a GPS unit of the user's device) can be transmitted to the worker's device to cause the worker's device to provide an indication that the first user has begun to travel to the fulfillment location. The worker's device can also display an estimated arrival time or estimated time until arrival at the fulfillment location for the first user. For example, the first user's device can determine that the first user has begun to travel to the fulfillment location. The first user's device can transmit a communication to the worker's device indicating that the first user has begun traveling to the fulfillment location. The worker's device can provide an estimated time until arrival at the fulfillment location for the first user. Upon the user arriving at or near the fulfillment location, the first user's device can transmit a communication to the worker's device indicating that the user has arrived”) (0005).
Nelson specifically doesn’t disclose, the fourth message being indicative of a state of the first batched order, the fifth message being indicative of the state of the first batched order, however Chopra discloses, the fourth message being indicative of a state of the first batched order (Examiner interprets that a store-generated message indicative of an order state. Nelson and Chopra, as applied to claim 6, group the first and second orders as the first batched order. It would have been obvious to apply Chopra’s known state-tracking operation to the resulting batch so that the system determines and communicates the fulfillment state of the coordinated pickup unit. For example, the batch may be designated ready when its constituent orders are ready for common pickup) (“order placement 214 event may occur when the order is received at the merchant device. In some embodiments, the merchant may acknowledge the receipt of the order by transmitting a confirmation, which may trigger the order confirmation 216 event. Order confirmation 216 may signal that preparation of the order has begun by the merchant. In some embodiments, the period of time between order creation 212-A and order confirmation 216 is known as kitchen latency 240 … the events that occur on a courier timeline 211 may overlap or correspond with one or more events on a merchant timeline 210. The events on courier timeline 211 may include order creation 212-B, order assignment 222, parked at merchant 224, arrival at merchant 226, order pickup 220-B, return to vehicle 228, parked at customer 230, and order delivered 232”) (0048-0050, 0073),
the fifth message being indicative of the state of the first batched order (Examiner interprets that Chopra expressly states that the customer may be provided information regarding the status of the order, events, or milestones i.e. that status-notification process to the batched order created under claim 6 would result in the fifth message indicating the state of the batch) (“the delivery platform may determine the estimated time arrival (ETA) of delivery of the order to the customer once the order has been placed. This ETA may be provided to the customer. The ETA of delivery of an order may be estimated based on tracked events or milestones corresponding to the order. As used herein, the terms “events” may be used interchangeably with “milestones.” The customer may also be provided with information regarding the status of the order, events, or milestones. The customer may also be provided with other information, such as information corresponding to the courier, etc. Information regarding the status of the order, events, or milestones may also be provided to the merchants and the couriers”) (0045, 0107).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the applicant’s invention to receiving a first pickup order made at a first time point associated with a first pickup entity, the first pickup order being directed to a store, receiving a second pickup order made at a second time point associated with the first pickup entity, the second pickup order being directed to the store, determining, based on pickup entity information associated with the first pickup entity, that the first pickup order and the second pickup order, receiving first location data from a first computing device associated with the first pickup entity, determining a first estimated arrival time of the first pickup entity based at least in part on the first location data, the first estimated arrival time being indicative of when the first pickup entity will arrive at the store, and sending a first message to a store computing device associated with the store, as disclosed by Nelson, the fourth message being indicative of a state of the first batched order, the fifth message being indicative of the state of the first batched order, as taught by Chopra for the purpose by applying batching technique to same-customer pickup orders would formalize and automate the coordinated treatment thus allowing store personnel to identify, prepare, retrieve, and hand off the associated orders together thus to reduce redundant employee handling, avoid separate handoffs, and reduce the likelihood that the customer must wait for a later-added order.
As per claims 14, Nelson discloses, wherein the state comprises at least one of a ready state, a processing state, or a waiting state (Examiner interprets Nelson expressly provides order-status notifications to the customer device, and does not limit the status to a specifically named ready, processing, or waiting state.) (“worker's device can also display an estimated arrival time or estimated time until arrival at the fulfillment location for the first user. For example, the first user's device can determine that the first user has begun to travel to the fulfillment location. The first user's device can transmit a communication to the worker's device indicating that the first user has begun traveling to the fulfillment location. The worker's device can provide an estimated time until arrival at the fulfillment location for the first user. Upon the user arriving at or near the fulfillment location, the first user's device can transmit a communication to the worker's device indicating that the user has arrived. This can cause the worker's device to display a count up timer indicating how long the first user has been waiting for her order after arriving at the fulfillment location. In some implementations, if the count up timer reaches a preset threshold, a customized notification can be provided to the first user's device to indicate a status of the order, indicate additional instructions for the first user, or communicate another message to the first user”) (0005).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
U.S. Pub. No. 20140074743 (“Rademaker”)
Rademaker discloses, methods of processing orders are provided. In some embodiments, a retailer for fulfilling an order is chosen, and a predicted time of arrival for the customer to arrive at the retailer is determined. An order notification is transmitted to the retailer, which inserts the order into a preparation queue to be prepared and delivered to a pickup location by the predicted time of arrival. In some embodiments, the location of the customer is monitored and the predicted time of arrival may be updated if the location of the customer deviates from an expected location. In some embodiments, a string of orders is created. A set of retailers capable of fulfilling orders for a set of products is determined. A set of pickup locations associated with the set of retailers is determined, and path.
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/GAUTAM UBALE/Primary Examiner, Art Unit 3689
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