Deshpande, Ajay Ashok. et al.Download PDFPatent Trials and Appeals BoardMar 9, 202014542232 - (D) (P.T.A.B. Mar. 9, 2020) Copy Citation UNITED STATES PATENT AND TRADEMARK OFFICE UNITED STATES DEPARTMENT OF COMMERCE United States Patent and Trademark Office Address: COMMISSIONER FOR PATENTS P.O. Box 1450 Alexandria, Virginia 22313-1450 www.uspto.gov APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO. 14/542,232 11/14/2014 Ajay Ashok Deshpande YOR920140511US1 9410 48150 7590 03/09/2020 MCGINN INTELLECTUAL PROPERTY LAW GROUP, PLLC 8321 OLD COURTHOUSE ROAD SUITE 200 VIENNA, VA 22182-3817 EXAMINER HENRY, MATTHEW D ART UNIT PAPER NUMBER 3683 MAIL DATE DELIVERY MODE 03/09/2020 PAPER Please find below and/or attached an Office communication concerning this application or proceeding. The time period for reply, if any, is set in the attached communication. PTOL-90A (Rev. 04/07) UNITED STATES PATENT AND TRADEMARK OFFICE ____________________ BEFORE THE PATENT TRIAL AND APPEAL BOARD ____________________ Ex parte AJAY ASHOK DESHPANDE, KIMBERLY D. HENDRIX, HERBERT SCOTT MCFADDIN, and CHANDRASEKHAR NARAYANASWAMI __________________ Appeal 2018-007545 Application 14/542,232 Technology Center 3600 ____________________ Before JOSEPH A. FISCHETTI, JAMES P. CALVE, and ROBERT J. SILVERMAN, Administrative Patent Judges. CALVE, Administrative Patent Judge. DECISION ON APPEAL STATEMENT OF THE CASE Pursuant to 35 U.S.C. § 134(a), Appellant1 appeals from the decision of the Examiner to reject claims 1–8, 10–15, and 19–22. See Appeal Br. 1. Claims 9 and 16–18 are cancelled.2 Id. at 28, 30 (Claims App.). We have jurisdiction under 35 U.S.C. § 6(b). We AFFIRM. 1 “Appellant” refers to “applicant” as defined in 37 C.F.R. § 1.42. Appellant identifies International Business Machines Corporation as the real party in interest. Appeal Br. 1. 2 Claims 9 and 16–18 were cancelled by an Amendment Under 37 C.F.R. § 1.116, filed Jan. 24, 2018. Appeal 2018-007545 Application 14/542,232 2 CLAIMED SUBJECT MATTER Claims 1, 15, and 20 are independent. Claim 1 is reproduced below. 1. A method comprising: receiving, as input data in a processor of a computer, an identification and a location of a retail entity; retrieving map data relevant for said retail entity and locating said retail entity on said map data; receiving, as input data, data identifying at least one of a product, a product set, and a service or services; retrieving a listing of one or more competitors that offer said product or one or more products of said product set or said service(s) as a competitor of said retail entity for said product, product set, or service(s) and locating said one or more competitors on said map data; and calculating an affinity for consumers for said product, product set, or service(s) for said retail entity and each of said one or more competitors, wherein said calculating said affinity comprises: retrieving data from a history of location traces of a specific customer to determine travel paths of said specific customer; superimposing said travel paths on said map data; using a history of previous visits of said specific customer to said retail entity to determine a likelihood that said specific customer will visit said retail entity within a specified time period based upon detecting a current location of said specific customer; and providing output data for displaying said likelihood on a map display based on said map data. REJECTIONS Claims 1–8, 10–15, and 19–22 are rejected as directed to patent- ineligible subject matter under a judicial exception to 35 U.S.C. § 101. Claims 1–8, 10–14 and 20–22 are rejected under 35 U.S.C. § 112(a) as failing to comply with the written description requirement. Appeal 2018-007545 Application 14/542,232 3 Claims 1–8 and 10–14 are rejected under 35 U.S.C. § 112(b) as being indefinite. Claims 15, 19, 20, and 22 are rejected under 35 U.S.C. § 102(a)(1) and 102(a)(2) as anticipated by Weiss (US 2011/0099046 A1, pub. Apr. 28, 2011). Claims 1–5, 8, 10–14, and 21 are rejected under 35 U.S.C. § 103 as unpatentable over Weiss and Shim (US 2013/0226857 A1, pub. Aug. 29, 2013). Claims 6–8 are rejected under 35 U.S.C. § 103 as unpatentable over Weiss, Shim, and Maptitude (Sales Mapping Data Points, published at the Wayback Machine, July 10, 2014, and available at http://web.archive.org/ web/20140710153301/http://www.caliper.com/Maptitude/solutions/sales- mapping-data-points.htm). ANALYSIS Claims 1–8, 10–14 and 20–22 for Lack of Written Description Claims 1–8 and 10–14 The Examiner determines that the Specification does not describe “calculating an affinity for consumers . . . determine a likelihood that said specific customer will visit said retail entity within a specified time period based upon detecting a current location of said specific customer” in claim 1. Ans. 12–13; Final Act. 16–17. The Examiner finds that the Specification does not describe a likelihood of a customer visiting a retail entity within a time period using a customer’s location. Ans. 13 (“[S]pecification provides no details as to how the claimed likelihood is actually calculated using time values and current use location values.”); Final Act. 17 (no description is provided of how time and location parameters produce an affinity value). Appeal 2018-007545 Application 14/542,232 4 Appellant argues that “affinity” was described in the Specification “as a new metric to be used for defining ‘combat zones’ or ‘engagement zones’ around a preselected retail entity’s store location relative to locations of its competitors for specific products or services.” Appeal Br. 19. Appellant argues that the Specification describes calculating the likelihood a customer will purchase a specific product from customer historical purchase data and the likelihood a customer will visit a specific retail location by detecting a current location based on previous visit information for that customer. Id. (citing Spec. 9:3–6, 18:12–13 as support for this claim limitation). The Patent Laws require “[t]he specification shall contain a written description of the invention.” 35 U.S.C. § 112(a). The written description must reasonably convey to a skilled artisan that the inventor had possession of the claimed subject matter as of the filing date. Ariad Pharms., Inc. v. Eli Lilly & Co., 598 F.3d 1336, 1351 (Fed. Cir. 2010) (citations omitted). The test requires an objective inquiry into the four corners of the specification from the perspective of a person of ordinary skill in the art. Id. Although the written description requirement does not require claimed subject matter to be described identically (Ariad, 598 F.3d at 1352), “[t]he appearance of mere indistinct words in a specification or a claim, even an original claim, does not necessarily satisfy” section 112, paragraph one, if it does not put others on notice of the scope of the claimed invention and demonstrate possession of that invention (Enzo Biochem, Inc. v. Gen-Probe Inc., 323 F.3d 956, 968 (Fed. Cir. 2002)). When a written description cannot be found in the specification, as filed, the only thing the PTO can reasonably be expected to do is to point out its non-existence. Hyatt v. Dudas, 492 F.3d 1365, 1377 (Fed. Cir. 2007). Appeal 2018-007545 Application 14/542,232 5 Here, claim 1 recites a step of calculating an affinity of consumers for a product by retrieving a history of location traces for a specific customer, superimposing the customer’s travel paths on map data, and using a history of previous visits of the customer to a retail entity “to determine a likelihood that said specific customer will visit said retail entity within a specified time based upon detecting a current location of said specific customer.” Appeal Br. 26 (Claims App.). The Specification describes these steps as follows: “affinity” refers to a calculated measure of likelihood that a customer will purchase a specific product, an item from a specific product set from a specific retail, or service, given identified local competing retailers offering the same product or product set of service. “Affinity” also refers to a calculated measure of likelihood that a customer, including, if desired, a specific customer, will visit the specific retailer location within a predetermined time period, which likelihood, in some cases, is calculated based on detecting the customer’s current location. The probability function can be a prediction of when a specific customer will visit the retail store within a specific time period, as can be statistically calculated based on previous visit information for that customer. Spec. 8:21–9:5, 18:10–13. Other portions of the Specification likewise sufficiently describe this subject matter. Spec. 16:12–16, 18:5–13, 24:15– 22, 26:17–28:22, 31:5–10; see Appeal Br. 19; Reply Br. 9. Thus, we do not sustain this rejection. Claims 6–8 The Examiner determines that the Specification does not describe how to calculate a radius between a retail entity and a competitor indicative of relative amounts of product purchased as claimed in claim 6. Final Act. 17– 18. The Examiner finds insufficient detail to explain how to calculate the radius or distort it based on other claimed features. Id. Appeal 2018-007545 Application 14/542,232 6 Appellant does not argue the rejection of claim 6. Appeal Br. 19–21; Reply Br. 9–10. Thus, we summarily sustain this rejection. See 37 C.F.R. § 41.37(c)(1)(iv) (failure to separately argue a claim waives argument). Claim 8 The Examiner determines that the Specification does not describe the limitation of “calculating a probability function that a specific customer will visit said retail entity” where the probability varies as a function of previous visit history by the customer as recited in claim 8. Final Act. 19. Appellant does not argue the rejection of claim 8. Appeal Br. 19–21; Reply Br. 9–10. Thus, we summarily sustain this rejection. See 37 C.F.R. § 41.37(c)(1)(iv) (failure to separately argue a claim waives argument). Claims 20–22 The Examiner determines that the Specification lacks sufficient detail to explain how to achieve “a calculated zone around a competitor” as recited in claims 20–22. Final Act. 20 (“Simply stating that the zone is calculated using a radius, customers calculated affinity value, likelihood of visiting a competitor, and relative convenience is not sufficient detail to directly relate the probability to the aforementioned variables.”). Appellant does not argue the rejection of claims 20–22. Appeal Br. 19–21; Reply Br. 9–10. Thus, we summarily sustain this rejection. See 37 C.F.R. § 41.37(c)(1)(iv) (failure to separately argue a claim waives argument). Claims 1–8 and 10–14 Rejected as Indefinite Regarding claim 1, the Examiner determines it is unclear what an “affinity” entails or what inputs are used to calculate the affinity. Final Act. 21–22. Appellant cites the same descriptions of calculating an affinity as in the written description of claim 1 above. See Appeal Br. 19; Reply Br. 9. Appeal 2018-007545 Application 14/542,232 7 For claims in a pending application that has not issued as a patent, “[a] claim is indefinite when it contains words or phrases whose meaning is unclear.” In re Packard, 751 F.3d 1307, 1310, 1314 (Fed. Cir. 2014); see Ex parte McAward, Appeal No. 2015-006416, 2017 WL 3669566, at *2 (PTAB Aug. 25, 2017) (precedential) (same). We determine the meaning of claim 1 is clear as to how an affinity is calculated for consumers of a product. Claim 1 recites various steps of this calculation as retrieving data from a history of location traces of a specific customer, superimposing said travel paths on said map data, and using a history of previous visits of said customer to said retail entity to determine a likelihood that the customer will visit the retail entity within a specified time period based on detecting a current location of the specific customer. The Examiner appears to understand the meaning of this limitation, but finds that the Specification does not explain how to calculate an affinity. See Final Act. 21–22. We determine that the Specification describes this feature sufficiently that its meaning is clear. See Spec. 8:21–9:5, 16:12–16, 18:5–13, 18:10–13, 24:15–22, 26:17–28:22, 31:5–10. Whether this feature is enabled by the Specification involves separate consideration of whether undue experimentation is required. See MANUAL OF PATENT EXAMINING PROCEDURE § 2164.01 (9th Ed. Rev. 08.2017, Jan. 2018). Merely claiming broadly does not render a claim indefinite as long as its meaning is clear. See In re Gardner, 427 F.2d 786, 788 (CCPA 1970) (“Breadth is not indefiniteness.”); see also Ultimax Cement Mfg. Corp. v. CTS Cement Mfg. Corp., 587 F.3d 1339, 1352 (Fed. Cir. 2009) (merely claiming broadly does not prevent public from understanding claim scope). Thus, we do not sustain this rejection. Appeal 2018-007545 Application 14/542,232 8 Claims 1–8, 10–15, and 19–22 Directed to a Judicial Exception to 35 U.S.C. § 101 Appellant argues the claims as a group. See Appeal Br. 10–18. We select claim 1 as representative. See 37 C.F.R. § 41.37(c)(1)(iv). Regarding claim 1, the Examiner determines that claim 1 is drawn to a process, which is a statutory category under 35 U.S.C. § 101, and is directed to “(receiving information, analyzing it, and displaying it (Electric Power Group) and collecting and comparing known information (Classen).” Final Act. 12, 13. The Examiner makes this determination based on steps in claim 1 that cover, e.g., receiving input data, retrieving map data and a listing, and calculating an affinity by retrieving data from a history of location traces, superimposing the travel paths, and using a history of previous visits, and providing output data. Id. at 12–14. The Examiner thus concludes that claim 1 recites abstract marketing actions and mathematical equations or relationships in the calculating steps/functions. Id. Appellant argues that the claims use “customer affinity” to calculate “engagement zones” around a specific retail entity as an inventive step, and the rejection does not identify any abstract ideas. Appeal Br. 11–15. In addition, Appellant argues that the rejection does not consider the claimed calculation of an affinity for consumers or the generation of an engagement zone in claims 3, 8, 21, and 22 or specific methods of calculating affinity for customers in claims 1, 2, 6, and 14. Id. at 15. Appellant further argues that the rejection fails to articulate a fundamental tool of technology that would be preempted by the claimed invention or demonstrate how the claims are a generic computerized implementation of that fundamental tool. Id. at 10, 13, 14, 16–18. Appeal 2018-007545 Application 14/542,232 9 To address these issues we apply the following analytical framework. Section 101 of the Patent Act defines patent-eligible-subject matter as: 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. 35 U.S.C. § 101 (2012). However, “[l]aws of nature, natural phenomena, and abstract ideas are not patentable.” Alice Corp. v. CLS Bank Int’l, 573 U.S. 208, 216 (2014) (citation omitted). To distinguish patents that claim laws of nature, natural phenomena, and abstract ideas from those that claim patent-eligible applications, we first determine whether the claims are directed to a patent-ineligible concept. Alice, 573 U.S. at 217. If they are, we consider the elements of each claim, individually and as an ordered combination, to determine if additional elements transform the claim into a patent-eligible application, e.g., by providing an “inventive concept” that ensures the patent amounts to significantly more than a patent on the ineligible concept. Id. at 217–18. The USPTO has issued guidance about this framework. 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019) (“Revised Guidance”). Under the Revised Guidance, to determine whether a claim is “directed to” an abstract idea, we evaluate whether the claim recites (1) any judicial exceptions, including certain groupings of abstract ideas listed in the Revised Guidance (i.e., mathematical concepts, certain methods of organizing human activities such as a fundamental economic practice, or mental processes); and (2) additional elements that integrate the judicial exception into a practical application (see MPEP §§ 2106.05(a)–(c), (e)–(h)). See Revised Guidance, 84 Fed. Reg. at 52–55. Appeal 2018-007545 Application 14/542,232 10 Only if a claim (1) recites a judicial exception and also (2) does not integrate that exception into a practical application, do we then consider whether the claim (3) adds a specific limitation beyond the judicial exception that is not “well-understood, routine, conventional” in the field (see MPEP § 2106.05(d)) or (4) simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. Id. at 56. Is Claim 1 to a Statutory Category? We agree with the Examiner that claim 1 recites a method that falls within the “process” category of 35 U.S.C. § 101. See Final Act. 12. Are Judicial Exceptions Recited? We also agree with the Examiner that claim 1 recites abstract ideas of marketing activities and mathematical calculations/relationships. Final Act. 12–14. The Revised Guidance enumerates these ideas as judicial exceptions as (1) mathematical concepts––mathematical relationships and calculations and (2) certain methods of certain methods of organizing human activity–– fundamental economic practices, commercial interactions of advertising, marketing, and sales activities. See Revised Guidance, 84 Fed. Reg. at 52. Appellant’s Specification describes these abstract ideas as calculating, updating, and displaying “combat zones” and “retail customer engagement zones” as spatiotemporal areas that are used to analyze competition among merchants for the business of individual customers or customer groups. See Spec. 1:1–12. Marketing, merchandising, and/or operations strategies can be developed and adjusted dynamically from the competition zones. Id. This filtered data of individual customers at specific stores enriches marketing data for that location and targets customers who shop there. Id. at 2:7–14. Appeal 2018-007545 Application 14/542,232 11 [A]n . . . objective of this invention is to provide a system and method for retailers to increase their market share and customer loyalty by effectively using analytics in conjunction with contextual information to understand spatiotemporal zones of competition among merchants for retaining or inducing the business of individual shoppers or of groups of shoppers and to discover new opportunities to personalize incentives for shoppers to choose their store over that of a competitor for a given shopping trip, to better plan merchandising and pricing strategies, and to optimize store operations. Id. at 2:15–22 (emphasis added). The first four steps of claim 1 recite certain methods of organizing human activity of fundamental economic practices, commercial interactions of advertising, marketing, and sales activities. See Revised Guidance, 84 Fed. Reg. at 52. These steps are “receiving, as input data” “an identification and a location of a retail entity,” “receiving, as input data, data identifying at least one of a product, a product set, and a service or services,” “retrieving map data relevant for said retail entity and locating the retail entity on said map data,” and “retrieving a listing of one or more competitors that offer said product or one or more products of said product set or said service(s) as a competitor of said retail entity . . . and locating said one or more competitors on said map data.” These steps obtain “a set of input parameters 302 that incorporate one or more of a customer or customer set, a time or time period, a merchant or merchant category, product set or product features, and/or service(s).” Spec. 17:19–22, Fig. 3. This marketing/sales data is analyzed by a mathematical “probability function” to determine the likelihood of a customer visiting the specified merchant and/or shopping for the indicated product/product set as a “numerical probability function.” Id. at 17:19–18:13. Appeal 2018-007545 Application 14/542,232 12 Appellant’s Figure 1, reproduced below, illustrates this concept of a spatiotemporal “combat zone” / “engagement zone” for a Customer X. Figure 1 above uses consumer contextual data as a marketing tool for retail Store A. Store A calculates a combat zone relative to Customer X and Store B, which competes with Store A in a specific product or product set. Spec. 5:1–2, 6:21–8:20. By monitoring contextual data of Customer X, to include updating the combat zone if appropriate, Store A can determine whether it might be useful to take marketing action to persuade Customer X to shop at Store A rather to shop at a competitor’s Store B. Id. at 8:3–14, see id. at 10:9–14, 16:7–16, 19:2–21, 23:9–16, 25:1–9. The final steps organize consumer activity data to “calculat[e] an affinity for consumers for said product, product set, or service(s) for said retail entity and each of said one or more competitors” by “retrieving data from a history of location traces of a specific customer to determine travel paths of said specific customer,” “superimposing said travel paths on said map data,” “using a history of previous visits of said specific customer to said retail entity to determine a likelihood that said specific customer will visit said retail entity within a specified time period based upon detecting a current location of said specific customer.” Appeal Br. 26 (Claims App.). Appeal 2018-007545 Application 14/542,232 13 These steps thus involve certain methods of organizing human activity of fundamental economic practices, commercial interactions of advertising, marketing, and sales activities. See Revised Guidance, 84 Fed. Reg. at 52. They also involve mathematical concepts––mathematical relationships and calculations to calculate an affinity of consumers for a product/product set and determine a likelihood of a specific customer visiting a retail entity. First, customer location traces are a type of “contextual data.” They can be used to determine a customer’s current location, as well as provide data for determining the shopping path or vicinity of travel by time of day and day of week for each customer, whether by foot or by motor vehicle or by public transport, by mining a history of location traces over a period of time such as recurring travel paths between home and work, home and a retail store, home and a point of interest. Spec. 11:3–8, 28:11–22. Second, the Specification describes a customer affinity as follows: Note that the combat zone can be time, merchant, customer, and product specific according to the input parameters. The output can be returned as a numerical probability function, as a subdivision of the original spatiotemporal area into subparts, each of which represents a range of likelihoods with the original area, as a visual representation (see the figures), or as a combination of all of the above. Thus, the output of the combat zone analyzer comprises a consumer affinity toward local competing retailers. The probability function can be a prediction of when a specific customer will visit the retail store within a specific time period, as can be statistically calculated based on previous visit information for that customer. Spec. 18:5–13 (emphasis added). “[T]he probability function can be based upon previous visit history for that customer.” Id. at 24:15–22, Fig. 6. The resulting data is displayed to a user. Spec. 17:19–20:4, Fig. 3. Appeal 2018-007545 Application 14/542,232 14 The probability function can be used to calculate a likelihood that a specific customer will visit a different retail store at a specific time when detected at any specific location. Spec. 31:5–10. The probability function can be calculated statistically based on previous visit information for the customer. Id. at 18:9–13. Furthermore, “[o]ther statistical or analytical methods can also be used to calculate specific affinity values since the present invention merely needs any mechanism that provides a quantitative value for each product/product set/service that indicates relative amounts for which Customer X visits/purchases from Store A.” Id. at 30:2–5. Thus, the claims recite and describe the calculated affinity at a high level of generality. If recently received, filtered data for Customer X indicates a location closer to Store B than Store A on a Saturday morning after Customer X has been searching for kitchen tiles and related products, the claimed process allows Store A to send an email and SMS text to Customer X suggesting a visit to Store A to see their tiles with a personalized offer to receive 20% off kitchen tile project purchases made that weekend only. Spec. 18:14–19:21. Therefore, claim 1 organizes consumer activity for the commercial interactions of advertising, marketing, and sales activities by filtering user locations in reference to an engagement zone defined around the locations of Stores A and B. It targets advertising to consumers based on their location. Filtering a consumer’s location near retail stores where the consumer may shop is an abstract idea. See BASCOM Glob. Internet Servs., Inc. v. AT&T Mobility LLC, 827 F.3d 1341, 1348 (Fed. Cir. 2016) (“We agree with the district court that filtering content is an abstract idea because it is a longstanding, well-known method of organizing human behavior”). Appeal 2018-007545 Application 14/542,232 15 Furthermore, “[t]he practice of conveying regional content to out-of- region recipients has been employed by nearly every form of media that has a local distribution.” Affinity Labs of Tex. LLC v. DIRECTV, LLC, 838 F.3d 1253, 1258 (Fed. Cir. 2016). The calculated consumer affinity simply allows Store A to send advertisements to Customer X when Customer X is located closer to rival Store B. Spec. 18:5–19:21, 25:1–9; Affinity Labs of Tex. LLC v. Amazon.com Inc., 838 F.3d 1266, 1269 (Fed. Cir. 2016) (“[W]e hold that the concept of delivering user-selected media content to portable devices is an abstract idea, as that term is used in the section 101 context.”). This process organizes consumer activity by location for marketing/advertising. The courts also have held the concept of sending advertisements to consumers based on their location is an abstract idea. Intellectual Ventures admitted that tailoring content based on the viewer’s location or address would satisfy the “as a function of the user’s personal characteristics” limitation. This sort of information tailoring is “a fundamental [economic] practice long prevalent in our system [of commerce and taught in any introductory finance class].” [Alice, 573 U.S. at 219]. There is no dispute that newspaper inserts had often been tailored based on information known about the customer—for example, a newspaper might advertise based on the customer’s location. Providing this minimal tailoring—e.g., providing different newspaper inserts based upon the location of the individual—is an abstract idea. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1369 (Fed. Cir. 2015); see also Bridge and Post, Inc. v. Verizon Commc’ns, Inc., 778 F. App’x 882, 887 (Fed. Cir. 2019) (“Targeted marketing is a form of ‘tailoring information based on [provided] data,’ which we have previously held is an abstract idea.”) (citation omitted). Appeal 2018-007545 Application 14/542,232 16 Bridge and Post held that tailoring advertisements based on real-time information about a user and user location allows a publisher to “maximize their advertising revenues” which is an abstract idea. Bridge and Post, 778 F. App’x at 884, 887–88. The patents recited steps of “tracking a user on a network and serving tailored advertisements.” Id. at 885. This concept of tailoring ads based on user profile data “dates back at least to local radio and television advertisements, which played only for users located in specific cities” and is a fundamental practice. Id. at 884, 887–88. Alternatively, claim 1 uses mathematical calculations to organize consumer location data via as a “consumer affinity,” which calculation is an abstract idea as discussed above. SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163 (Fed. Cir. 2018) (holding claims to a “series of mathematical calculations based on selected information” are directed to abstract ideas); Digitech Image Techs., LLC v. Elecs. for Imaging, Inc., 758 F.3d 1344, 1350 (Fed. Cir. 2014) (holding that claims to a “process of organizing information through mathematical correlations” are directed to an abstract idea); see also Bancorp Servs., L.L.C. v. Sun Life Assurance Co. of Can. (U.S.), 687 F.3d 1266, 1278 (Fed. Cir. 2012) (holding the use of a computer for its most basic function of making calculations or computations does not circumvent the prohibition against patenting abstract ideas and mental processes); Ans. 4 (determining a consumer affinity via mathematical relationship is abstract). Based on the foregoing, we determine that claim 1 recites certain methods of organizing human activity of fundamental economic practices, commercial interactions of advertising, marketing, and sales activities and mathematical concepts––mathematical relationships and calculations to calculate consumer affinity, which concepts are abstract ideas. Appeal 2018-007545 Application 14/542,232 17 Dependent claim 2 recites that the “affinity comprises a calculation of one of: a probability that a consumer will purchase said product or said service(s) or a product of said product set from said retail entity or from a competitor; and a probability that a consumer will visit said retail entity within a preset time period.” Appeal Br. 26–27 (Claims App.) (emphasis added). Claim 2 thus recites mathematical concepts and calculations. Dependent claim 3 recites organizing human activity for advertising, marketing, and sales by generating an engagement zone for a consumer, product, and competitor(s) in “an area determined to warrant a marketing action directed to said specific consumer to attempt to persuade said specific consumer to visit said retail entity to possibly purchase an item at said retail entity rather than from a competitor.” Appeal Br. 27. Dependent claim 6 recites steps of calculating a consumer affinity as a calculation of a radius between a retail entity and each competitor indicating relative amounts of the product or product set or services purchased at the retail entity and each competitor and distorting the radius based on features of map data and a measure of convenience to travel. Appeal Br. 27–28. This step involve mathematical calculations and organizing human activity for commercial interactions of advertising, marketing, and sales activities. Dependent claim 8 recites the calculation of a probability function that a customer will visit the retail entity. Appeal Br. 28. This step thus recites a mathematical relationship or calculation as an abstract idea. Claims 20–22 recite some of the abstract concepts of claim 1 in a system and database that filter data from multiple data sources, store, retrieve, and analyze the data to generate a marketing action to a customer determined to be in an engagement zone with a competitor. Id. at 30–31. Appeal 2018-007545 Application 14/542,232 18 The Examiner identifies each limitation that recites an abstract idea such as the retrieving, receiving, and calculating steps of claim 1 as reciting marketing concepts and mathematical equations and relationships. Final Act. 12–14; Ans. 3–4. Appellant admits “individual claim limitations may indeed define one or more underlying abstract concepts.” Reply Br. 1; see Appeal Br. 12. The Revised Guidance identifies these concepts as abstract ideas. Revised Guidance, 84 Fed. Reg. at 52 (“Guidance extracts and synthesizes key concepts identified by the courts as abstract ideas.”). Thus, the Examiner analyzes claim limitations as Appellant admits. See Appeal Br. 14–16. “Consumer affinity” and “engagement zones” are recited at high levels of generality as location-based, probability concepts used to provide targeted marketing. Providing customized, dynamic content such as advertisements) based on a user’s navigation history and profile, without more, is an abstract idea. See Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d at 1369–70 (providing tailored advertisements). Claim 1 calculates consumer affinity from historical location traces of customer paths to predict a likelihood a customer will visit a retail entity in a time period without specifying any details of that process or improvements to computer or software technology. See Spec. 9:2–13. Then, this data is used to target personalized ads to a consumer. Id. at 2:7–14, 16:20–17:6. In Bridge and Post, a claim to retrieving historic usage location and time patterns of a user, generating a user profile (affinity) for such location- centric information, and providing directed media based on that location and profile recited an abstract idea. Bridge and Post, 778 F. App’x at 886–87. Thus, we determine that claim 1 and other claims argued by Appellant with claim 1 (see Appeal Br. 15) recite the abstract ideas identified above. Appeal 2018-007545 Application 14/542,232 19 Are the Abstract Ideas Integrated into a Practical Application? We next consider whether claim 1 recites additional elements that integrate the abstract ideas into a practical application. Revised Guidance, 84 Fed. Reg. at 54–55 (Revised Step 2A, Prong Two). We agree with the Examiner that additional elements recited in claim 1 implement the abstract ideas with generic computer components that perform generic computer functions without significantly more to make the abstract ideas into patent ineligible ones. Ans. 8–9. A “computer” and “processor” perform generic functions of receiving input data, retrieving map data, a list of competitors, and other data, and performing calculations. Final Act. 14–15; Ans. 7–9. Reciting generic computer components that simply perform generic computer tasks to carry out an abstract idea does not make the abstract idea patent-eligible. Moving to step two of the Alice framework, it is clear that the claims contain no inventive concept. The recited elements, e.g., a database, a user profile (“a profile keyed to a user identity,” ’137 patent col. 10 l. 5), and a communication medium, are all generic computer elements. Instructing one to “apply” an abstract idea and reciting no more than generic computer elements performing generic computer tasks does not make an abstract idea patent-eligible. See Alice, 134 S.Ct. at 2359–60 (holding patent-ineligible claims that “amount to nothing significantly more than an instruction to apply the abstract idea . . . using some unspecified, generic computer” and in which “each step does no more than require a generic computer to perform generic computer functions” Capital One Bank, 792 F.3d at 1368; see also buySAFE Inc. v. Google, Inc., 765 F.3d 1350, 1354 (Fed. Cir. 2014) (“The Court in Alice made clear that a claim directed to an abstract idea does not move into section 101 eligibility territory by ‘merely requir[ing] generic computer implementation.’”). Appeal 2018-007545 Application 14/542,232 20 The Specification’s description of the technology used to implement these abstract ideas makes clear that these abstract ideas are not tied to a particular machine that is integral to the claims. Nor do the claims recite improvements to computers, networks, or other technology. The claimed “computer” includes personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing systems of any of these devices. Spec. 43:12–21. It also may be a general-purpose computing device with one or more processors. Id. at 44:10–14. The Specification describes a cloud computing embodiment, but the “implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, embodiments of the present invention are capable of being implemented in conjunction with any other type of computing environment now known or later developed.” Id. at 39:18–22; see id. at 40:1–3 (“Turning now [to] the possible hardware implementations that would support the methods of the present invention, it is previously noted that the invention could be supported with most computer architectures, including a cloud-based architecture.”). Merely reciting an abstract idea in a physical environment, without more, is insufficient to make the abstract idea patent-eligible. See SAP Am., 898 F.3d at 1168 (“Here, in contrast, the focus of the claims is not a physical-realm improvement but an improvement in wholly abstract ideas— the selection and mathematical analysis of information, followed by reporting or display of the results.”) (emphasis added). Appeal 2018-007545 Application 14/542,232 21 Essentially, Appellant argues that the abstract ideas recited in claim 1, and other claims, namely “consumer affinity” and “engagement zones” add significantly more to the claims. See Appeal Br. 13–14. However, “[i]t has been clear since Alice that a claimed invention’s use of the ineligible concept to which it is directed cannot supply the inventive concept that renders the invention ‘significantly more’ than that ineligible concept.” BSG Tech LLC v. Buyseasons, Inc., 899 F.3d 1281, 1290 (Fed. Cir. 2018). If the concepts involve advances in database structures or functions, the advances are not claimed. Claim 1 recites collecting and processing of information, which is not patent-eligible. Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1355 (Fed. Cir. 2016) (“[M]erely selecting information, by content or source, for collection, analysis, and display does nothing significant to differentiate a process from ordinary mental processes.”). Consumer affinity is recited at a high level of generality and described as a generic “probability function.” Spec. 18:5–13. It recites the idea that a consumer who has visited a store on a certain day/time is likely to do so in the future. Id. 7:1–8:7, 10:2–11:8, 17:5–13, 24:21–22. An engagement zone is an area based on a consumer’s affinity for a retailer and the idea that a retailer must compete for a customer. Id. at 1:5–12, 16:12–16, 18:5–13. Merely adding one abstract concept to another does not make a claim to those combined abstract ideas patent eligible. See RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327 (Fed. Cir. 2017) (“Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract.”). Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151 (Fed. Cir. 2016) (“[A] claim for a new abstract idea is still an abstract idea.”). Appeal 2018-007545 Application 14/542,232 22 Even if we assume such abstract techniques are “[g]roundbreaking, innovative, or even brilliant,” that is not enough for eligibility. Ass’n for Molecular Pathology v. Myriad Genetics, Inc., 569 U.S. 576, 591 (2013); accord buySAFE, 765 F.3d at 1352. Nor is it enough that an abstract concept is novel and nonobvious over prior art. SAP Am., 898 F.3d at 1163. BASCOM, cited in the Appeal Brief, supports the foregoing analysis and illustrates why claim 1 is not patent-eligible. Appeal Br. 11–12. The court in BASCOM found an inventive concept in an improved filtering tool provided at a central location, remote from end-users, but also customizable with filtering features specific to each end user, thus providing the benefits of a filter on a local computer and on an ISP server. BASCOM, 827 F.3d at 1350). Here, claim 1 recites no comparable improvement to filtering or other technology. Instead, it uses computers as tools to apply abstract ideas. Here, merely receiving, storing, and communicating information for a marketing transaction is not inventive. See Elec. Power Grp., 830 F.3d at 1355 (holding that using off-the-shelf, conventional computer, network, and display technology to gather, send, and present desired information did not provide an inventive concept). Claims to dynamically analyzing consumer status information, without more, recite abstract ideas. See id. at 1351–52, 1354 (“[W]e have treated analyzing information by steps people go through in their minds, or by mathematical algorithms, without more, as essentially mental processes within the abstract-idea category.”). Accordingly, we determine that claim 1 does not recite any additional elements that are sufficient to integrate the abstract ideas recited therein into a practical application. Appeal 2018-007545 Application 14/542,232 23 Is an Inventive Concept Recited? We next consider whether claim 1 recites any elements, individually, or as an ordered combination, that provide an inventive concept. Alice, 573 U.S. at 217–18. “The second step of the Alice test is satisfied when the claim limitations involve more than performance of well-understood, routine [and] conventional activities previously known to the industry.” Berkheimer v. HP Inc., 881 F.3d 1360, 1367 (Fed. Cir. 2018) (internal quotations and citation omitted); see also Revised Guidance, 84 Fed. Reg. at 56 (explaining that the second step of the Alice analysis considers whether a claim adds a specific limitation beyond a judicial exception that is not “well-understood, routine, conventional” activity in the field). We agree with the Examiner that claim 1 recites a combination of abstract idea processes that gather and analyze information of a specified content and display results without using inventive technology. Ans. 3–5. The generic computer components perform their basic functions of storing, retrieving, processing, and displaying. Ans. 6. As an ordered combination, the elements do not amount to more than the abstract ideas. Id. at 7. USPTO Memorandum of April 19, 2018, “Changes in Examination Procedure Pertaining to Subject Matter Eligibility, Recent Subject Matter Eligibility Decision (Berkheimer v. HP, Inc.),” available at https://www.uspto.gov/sites/default/ files/documents/memo-berkheimer- 20180419.PDF (Berkheimer memo) explains the Specification may describe additional elements in a manner that indicates the elements are sufficiently well-known that the specification does not need to describe their particulars to satisfy 35 U.S.C. § 112(a). Berkheimer memo at 3–4. This is such a case as discussed above and illustrated by the description at Spec. 39:18–47:10. Appeal 2018-007545 Application 14/542,232 24 There is nothing unconventional about the “ordered combination” that is not merely the sum of the parts. See In re TLI Commc’ns LLC Patent Litig., 823 F.3d 607, 615 (Fed. Cir. 2016) (holding that where “recited physical components behave exactly as expected according to their ordinary use,” through “steps that generically spell out what it means to ‘apply it on a telephone network’ also cannot confer patent eligibility”); Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 715 (Fed. Cir. 2014) (sequence of receiving, selecting, offering for exchange, display, allowing access, and receiving payment recited an abstraction.); BSG, 899 F.3d at 1287–88 (use of “summary comparison usage information” rather than “historical usage information” to make database entries did not improve databases or other computer technology but instead are benefits that flow from performing an abstract idea on a well-known database structure). Where, as here, we determine that the claims are directed to patent- ineligible subject matter, Appellant’s preemption concerns (see Appeal Br. 10–17) are addressed fully and made moot by that determination. Ariosa Diagnostics, Inc. v. Sequenom, Inc., 788 F.3d 1371, 1379 (Fed. Cir. 2015) (“The Supreme Court has made clear that the principle of preemption is the basis for the judicial exceptions to patentability” however “questions on preemption are inherent in and resolved by the § 101 analysis.”). Accordingly, we determine that claim 1 does not recite any elements, considered individually, or as an ordered combination, that provide an inventive concept sufficient to transform the abstract idea into patent-eligible subject matter. Thus, we sustain the rejection of claims 1–8, 10–15, and 19– 22 as directed to patent-ineligible subject matter under 35 U.S.C. § 101. Appeal 2018-007545 Application 14/542,232 25 Claims 15, 19, 20, and 22 as Anticipated by Weiss Claims 15 and 19 Appellant argues that Weiss is directed to the problem of analyzing consumer behavior using consumer location data rather than detecting a current location of a specific consumer and determining whether to prepare and transmit marketing actions to that specific consumer based on a specific competitor for a specific product. Appeal Br. 21. Appellant also argues that paragraph 112 of Weiss does not send out a marketing action based on knowing the consumer’s current location relative to a specific competitor for a specific product and therefore does not teach “retrieving data for one or more competitors for said identified product . . . superimposing said one or more competitors on said map data, receiving data indicating a current location of said customer; determining whether said current location warrants a marketing action to be directed to said customer.” Id. at 21–22. Appellant’s arguments are not persuasive for several reasons. First, quoting a list of limitations of a claim such as the last seven limitations of claim 15 and asserting “in Weiss there is no teaching or suggestion off [sic]” these limitations as Appellant has done (Appeal Br. 21–22) does not identify error in the Examiner’s findings that Weiss does disclose these features. The rules governing appeals to the PTAB require an appellant to file an appeal brief presenting the following: The arguments of appellant with respect to each ground of rejection, and the basis therefor, with citations of the statutes, regulations, authorities, and parts of the Record relied on. The arguments shall explain why the examiner erred as to each ground of rejection contested by appellant. 37 C.F.R. § 41.37(c)(1)(iv). Appeal 2018-007545 Application 14/542,232 26 This rule requires arguments to identify error in a rejection. See Ex parte Frye, 94 USPQ2d 1072, 1075 (BPAI 2010) (precedential) (a panel reviews rejections for error based on the issues identified by an appellant). Our reviewing court has upheld this PTAB practice of requiring an appellant to identify examiner error in a rejection. In re Jung, 637 F.3d 1356, 1365 (Fed. Cir. 2011) (approving of Board’s practice as set forth in Ex parte Frye of requiring appellants to identify Examiner error in a rejection). Appellant does not address the Examiner’s findings for claim 15 and therefore does not apprise us of error in those findings. The Examiner relies on many teachings of Weiss to disclose limitations of claim 15 as Appellant recognizes. Appeal Br. 21. Appellant’s sole focus on paragraph 112 does not address other portions of Weiss relied on by the Examiner to anticipate claim 15. See id. at 21–22. Moreover, Weiss tracks consumer historical location traces to identify consumers who purchase a particular product at a particular store so that a business can choose promotions or advertisements to entice the consumer to visit that particular store and purchase a particular product. Weiss ¶¶ 36–49. Weiss tracks consumer preferences for a competitor of a business. Id. ¶¶ 29–33, 108–10. Weiss evaluates consumer responses to advertisements via goods and services that they purchase at businesses associated with those advertisements to include “businesses consumers view as alternatives” (i.e., competitors). Id. ¶¶ 110–12. Weiss identifies consumer preferences for a business versus its competitors in the same geographic area and targets ads to attract consumers away from a competitor. Id. ¶¶ 143–45, 185. Weiss targets appropriate ads in real-time based on a consumer’s location relative to a business to entice a consumer to visit that business. Id. ¶¶ 49–52, 112. Appeal 2018-007545 Application 14/542,232 27 Thus, we sustain the rejection of claim 15 and claim 19, which is not argued separately by Appellant. See 37 C.F.R. § 41.37(c)(1)(iv). Claims 20 and 22 Regarding claim 20, Appellant argues that Weiss does not disclose to “generate and transmit a marketing action to a customer determined to be in an engagement zone with one of said competitors, wherein said engagement zone comprises a calculated zone around a competitor offering a specific product, product set, or service also offered by said retail entity” because the descriptions in paragraphs 34, 69, 110, and 112 do not relate to calculation of engagement zones of a competitor for a specific product. Appeal Br. 22. We agree with the Examiner that Weiss stores information for a retail entity such as information about customers, products, product sets, services, and its competitors. Final Act. 27. Weiss stores a consumers’ interactions with a business and other businesses of the same type in a geographic area. See Weiss ¶¶ 36–49, 108–12, 143–45, 184, 185. The information may be retrieved from locations visited by a customer such as a particular point of interest like a sponsor’s store that a consumer visited. Id. ¶¶ 26, 29, 45, 67, 177; Final Act. 29. Weiss characterizes geographical areas of stores and locations where consumers spend a lot of time as “anchors.” Weiss ¶¶ 68, 69; Final Act. 29–30. Weiss uses this information to identify competitors in the same area based on consumers with similar interests and characteristics visiting other businesses in the area instead of the retail store. Weiss ¶ 185. Weiss also considers past interactions of a consumer(s) with a particular business and “other businesses of the same type” in the same geographical area. Weiss ¶¶ 108–12, 143–45. Thus, Weiss defines engagement zones of competitive retailers in an area frequented by buyers. Appeal 2018-007545 Application 14/542,232 28 Geographic areas where a business and its competitors are located in Weiss thus teach the claimed engagement zone “calculated” to encompass a business and competitors that offer a similar product, product set, or service as the business. The “engagement zone” is an area around a retailer where a consumer buys goods and services at that or another retailer. Spec. 9:2–8. Weiss uses past interactions of a consumer with a business and “other businesses of the same type” in the same geographical area to identify a zone for direct marketing actions as claimed. Weiss ¶¶ 34–52, 108–12, 143–45. Consumer interactions include purchases (affinity) at businesses in a zone. Id. Businesses use the predictive calculation of a zone in Weiss to generate and transmit marketing actions (marketing campaigns, business promotions, or advertisements) to a customer based on location and analyze the location data to determine whether a consumer was enticed to purchase a particular product at a store that offered the advertisement. Id. ¶¶ 34–49, 108–12. The advertisements can sway a consumer to visit a store that a consumer does not visit regularly in their normal travel routine. Id. ¶¶ 49, 52. The system also tracks whether the consumer went to an advertised business, or business that sells an advertised product, to determine if the advertising was effective in enticing a consumer to visit a business associated with the advertisement to include a first time visit by the consumer. Id. ¶¶ 108–12, 185. Weiss uses this location, time-based (spatiotemporal) information to categorize activities and stores, which would include competitors within a category. Weiss ¶ 86. Weiss analyzes advertisements based on consumer activity to identify which goods and services were purchased at businesses associated with the advertisement and which businesses are competitors for consumers to visit or purchase those same goods and services. Id. ¶ 110. Appeal 2018-007545 Application 14/542,232 29 “Once competitors are identified, decisions can be made regarding how to attract consumers away from competitors.” Weiss ¶ 145. The activities include advertising, marketing, and business promotions discussed above within the engagement zone. Weiss thus analyzes consumer location history and purchasing data in relation to particular goods and services available at a retail entity and at its competitors in a geographical area (engagement zone) and engages in certain marketing activities to specific customers in that area with ads for specific competing products and services offered by the retail entity, as claimed, to try to sway the consumer to shop at the retail entity. Id. ¶¶ 34–52, 108–12, 143–45; see Reply Br. 12–13. Accordingly, we sustain the rejection of claim 20 and claim 22, which is not argued separately. See 37 C.F.R. § 41.37(c)(1)(iv). Claims 1–5, 8, 10–14, and 21 as Unpatentable over Weiss and Shim Claim 1 Regarding claim 1, the Examiner finds that Weiss teaches a method substantially as claimed including calculating a relationship of consumers for a product, product set, or service(s) for a retail entity and a competitor(s) but does not calculate an affinity or determine a likelihood that a specific customer will visit the retail entity within a specified time period as claimed. Final Act. 33–37. The Examiner relies on Shim to teach these features as probabilities of a user visiting a place or category of place within a specified time period. Id. at 37. The Examiner determines that it would have been obvious to a skilled artisan to modify Weiss to incorporate Shim’s teachings “to better determine how a customer location will perform thereby allowing a location to better prepare for demand needs” (id. at 38) and predict affinity of a customer better to improve advertising success (Ans. 20–21). Appeal 2018-007545 Application 14/542,232 30 Appellant argues that Shim determines a probability that a user visited a specific location and does not calculate a consumer’s affinity for a specific product and specific competitor. Appeal Br. 22. Appellant argues that the claimed method uses an entirely different probability for a different purpose thereby making Shim non-analogous art. Id. at 23. Appellant argues that there is no reason to modify Weiss to incorporate the location determination of Shim because precise location of a consumer is not an issue in Weiss. Id. Appellant further argues that such modification of Weiss would not arrive at the claimed invention because neither reference calculates an affinity value for products relative to competitors of specific products. Id. Appellant’s arguments are not persuasive for the following reasons. First, we agree with the Examiner that Weiss calculates a relationship of a consumer for a product/product set/service of a retail entity and competitors as recited in claim 1 to determine which products/services each consumer purchases at which business in a geographical area as discussed above for claims 15 and 20. See Weiss ¶¶ 34–52, 108–12, 143–45; Final Act. 22–31. This relationship as taught by Weiss also corresponds to the claimed affinity of consumers for a product/product set/service for the retail entity and its competitor(s). The Specification defines “affinity” as “a calculated measure of likelihood that a customer will purchase a specific product, an item from a specific product set from a specific retailer, or service, given identified local competing retailers offering the same product or product set or service.” Spec. 8:21–9:2. “Affinity” also is a calculated measure of the likelihood that a customer/a specific customer, will visit a specific retailer location within a predetermined time period, and may be “calculated based on detecting the customer’s current location.” Id. at 9:2–6. Appeal 2018-007545 Application 14/542,232 31 Weiss calculates a customer’s “affinity” for a specific product using a history of previous visits to a retail entity and determines a likelihood that the specific customer will visit the retail entity within a specified time period based on detecting the current location of the specific customer as claimed. First, Weiss uses a customer’s current location and history of no visits to a retail entity (i.e., no/zero affinity for the retail entity) to determine there is no or little likelihood of the customer stopping at the retail entity so advertising must be issued to that specific customer to entice them to stop at the retail entity for which their past history demonstrates no affinity. Weiss ¶¶ 49 (ad to sway consumer to visit grocery store 132 that consumer does not regularly visit), 52 (same), 108 (consumers who visited businesses associated with an ad for the first time), 110 (same), 144, 145, 184, 185. Second, Weiss also uses a customer’s current location and history of visits to specific retailers (coffee shop, gas station, restaurant, grocery store) from location traces to determine whether a customer will visit a retailer in a predetermined time or “go to a competitor coffee shop” so coffee shop 122 can use ads to encourage the consumer to visits its store. Weiss ¶¶ 48–52. Third, Weiss determines consumer affinity for a retail entity and its competitors by tracking visits (frequency, times) and purchases of items at a particular store(s) in clusters. See Weiss ¶¶ 48–52, 67–76, 100–10, 143–45. Weiss determines a likelihood of a consumer visiting a particular point of interest (POI) based on past visits to certain other POIs. Id. ¶¶ 79–93. Like Appellant’s claims, Weiss performs this affinity analysis to determine if a consumer can be swayed to visit a POI that is passed but not visited, e.g., by issuing advertisements to incentivize the consumer to visit and buy goods or services at the business. Weiss ¶¶ 91–94, 108–12. Appeal 2018-007545 Application 14/542,232 32 We agree with the Examiner that Shim also generates a probability of a particular user visiting a particular place rather than merely a probability of a user’s location as Appellant argues. See Final Act. 37–38; Appeal Br. 22. Shim uses an inference model or pipeline “to generate the probabilities of a user visiting a place” or “the probability of a user visiting a place and the time user has spent at a place.” Shim ¶¶ 15, 18, 19. Shim identifies a cluster of places as candidate places and ranks them by probability that a particular user will visit each place, given the day or time of day. Id. ¶¶ 58–61, 71, 83. Shim is reasonably pertinent to the problem addressed by Appellant of using an inference model/pipeline to generate a probability (likelihood) that a user who is located at a particular retail location (store) in a cluster of such stores can be swayed by targeted advertising/promotions to visit a particular retail establishment and other suggested related places. See Shim ¶¶ 3, 15– 19, 61, 71, 83, 148, Fig. 7. Shim thus is reasonably pertinent to Appellant’s targeted advertising and marketing operations between competitors. See Spec. 1:5–12, 30:20–32:21. Both methods are dynamic rather than static. The Examiner reasonably determines that a skilled artisan would have been motivated to improve Weiss with Shim’s probability inference model “to better determine how a customer location will perform thereby allowing a location to better prepare for demand needs” (Final Act. 38) and improve advertising success (Ans. 20–21). Using Shim’s probability technique to improve the accuracy of Weiss’s consumer probability determination and targeted advertising similarly would provide similar benefits to Weiss of greater accuracy in predicting whether a consumer would visit a particular store in a cluster/engagement zone, e.g., a retail entity or a competitor’s location. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 417 (2007). Appeal 2018-007545 Application 14/542,232 33 Claims 2–5, 10, and 11 Appellant’s arguments regarding the rejection of dependent claims 2– 5, 10, and 11 largely comprise a recitation or summary of the limitations of those claims and a conclusory assertion that Weiss or Shim do not teach the claimed features. Appeal Br. 23–24. These arguments are not persuasive. “A statement which merely points out what a claim recites will not be considered an argument for separate patentability of the claim.” 37 C.F.R. § 41.37(c)(1)(iv); see also In re Lovin, 652 F.3d 1349, 1357 (Fed. Cir. 2011) (holding that the Board reasonably interpreted 37 C.F.R. § 41.37(c)(1)(vii) (predecessor to § 41.37(c)(1)(iv)) to require “more substantive arguments in an appeal brief than a mere recitation of the claim elements and a naked assertion that the corresponding elements were not found in the prior art.”). Moreover, as discussed above, Weiss determines a probability that a consumer will purchase a product/product set/services from a retail entity or from a competitor in a geographical area (engagement zone) and visit a retail entity within a preset time period. Shim also determines a probability that a consumer will visit a retail entity within a preset time period and purchase a product or service from a retail entity or a competitor as recited in claim 2. Regarding claim 3, Weiss and Shim generate engagement zones for a retail entity and its competitors as geographical areas or clusters as discussed above. Weiss does so in order to determine whether to transmit a marketing message to a specific consumer currently located in an engagement zone as recited in claim 4. Shim teaches the use of targeted marketing messages to consumers based on their location. Shim ¶ 3. Weiss monitors responses of specific customers to a targeted marketing action in a preset time period and store as recited in claims 5 and 11. Weiss ¶¶ 29–52, 108–12. Appeal 2018-007545 Application 14/542,232 34 Weiss dynamically updates consumer contextual data indicative of events or conditions that would influence a specific customer to purchase at a retail entity as recited in claim 10. Weiss ¶¶ 48–52, 100–12, 143–45. Accordingly, we sustain the rejection of claims 1–5, 10, and 11, and claims 8, 12–14, and 21, which are not argued separately by Appellant. See 37 C.F.R. § 41.37(c)(1)(iv). Claims 6–8 as Unpatentable over Weiss, Shim, and Maptitude As discussed above, Weiss tracks the purchases of particular products at a retail entity and/or its competitors in a geographical area to determine if marketing, promotions, or advertising should be sent to particular consumers to induce them to shop at a particular retail entity rather than a competitor’s store. Weiss does not display the relative amounts of products purchased at a retail entity or a competitor’s store using a radius that may be distorted by features of the map data or a measure of convenience to travel to the retail entity or a competitor’s store, or contextual data as recited in claim 6. The Examiner cites Maptitude to teach calculation and display of radii indicative of relative amounts of product/services purchased at a retail entity or a competitor in an area with distortions for map features or contextual data such as drive time to each store. Final Act. 49–50; Ans. 23–24. Appellant’s argument that Maptitude does not calculate a radius based on relative amounts of products purchased at a retail entity or a competitor (Appeal Br. 24–25) is unpersuasive because the Examiner relies on the combined teachings of the references to render claim 6 obvious. See In re Merck & Co., 800 F.2d 1091, 1097 (Fed. Cir. 1986) (“Non-obviousness cannot be established by attacking references individually where the rejection is based upon the teachings of a combination of references.”). Appeal 2018-007545 Application 14/542,232 35 Weiss teaches tracking relative purchases, and Maptitude teaches displaying that data for different stores on a map with distortions to account for contextual data such as drive times (i.e., convenience), which account for terrain and other geographical and contextual features. Accordingly, we sustain the rejection of claim 6 and dependent claims 7 and 8, which are not argued separately. See 37 C.F.R. § 41.37(c)(1)(iv). CONCLUSION Claims Rejected 35 U.S.C. § Reference(s)/Basis Affirmed Reversed 1–8, 10–15, 19–22 101 Judicial Exception 1–8, 10–15, 19–22 1–8, 10–14, 20–22 112(a) Written Description 6–8, 20–22 1–5, 10–14 1–8, 10–14 112(b) Indefiniteness 1–8, 10–14 15, 19, 20, 22 102(a)(1) 102(a)(2) Weiss 15, 19, 20, 22 1–5, 8, 10– 14, 21 103 Weiss, Shim 1–5, 8, 10– 14, 21 6–8 103 Weiss, Shim, Maptitude 6–8 Overall Outcome 1–8, 10–15, 19–22 No time period for taking any subsequent action in connection with this appeal may be extended under 37 C.F.R. § 1.136(a)(1)(iv). AFFIRMED Copy with citationCopy as parenthetical citation