Weis, David et al.

Patent Trials and Appeals Board

Sep 25, 2019

13951215 - (D) (P.T.A.B. Sep. 25, 2019)

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.
13/951,215 07/25/2013 David Weis 21652-00267 6588
75564 7590 09/25/2019
DANIEL M. FITZGERALD (21652)
ARMSTRONG TEASDALE LLP
7700 Forsyth Boulevard
Suite 1800
St. Louis, MO 63105
EXAMINER
ROSEN, NICHOLAS D
ART UNIT PAPER NUMBER
3625
NOTIFICATION DATE DELIVERY MODE
09/25/2019 ELECTRONIC
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.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
USpatents@armstrongteasdale.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte DAVID WEIS, GARY SOFKO,
and GARY KEARNS
____________

Appeal 2019-005188
Application 13/951,2151
Technology Center 3600
_______________

Before JOSEPH L. DIXON, HUNG H. BUI, and JON M. JURGOVAN,
Administrative Patent Judges.

BUI, Administrative Patent Judge.

DECISION ON APPEAL
Appellants seek our review under 35 U.S.C. § 134(a) from the
Examiner’s Final Rejection of claims 1, 2, 4, 5, 7–13, 15, 17, 18, and 20,
which are all the claims pending in the application. We have jurisdiction
under 35 U.S.C. § 6(b).
We AFFIRM.2

1 According to Appellants, the real party in interest is MasterCard
International Incorporated. App. Br. 1.
2 Our Decision refers to Appellants’ Appeal Brief (“App. Br.”) filed March
11, 2019; Reply Brief (“Reply Br.”) filed June 24, 2019; Examiner’s Answer
(“Ans.”) mailed April 22, 2019; Final Office Action (“Final Act.”) mailed
October 11, 2018; and original Specification (“Spec.”) filed July 25, 2013.
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STATEMENT OF THE CASE
Appellants’ invention is directed to a method and system “for
recommending merchants to a potential consumer based at least in part on
the potential consumer’s search location and payment transaction histories of
local payment cardholders” by “determin[ing] a total number of transactions
and a number of local and unique cardholders for each merchant identifier
[associated with each transaction of payment cardholders] based, at least in
part, on the transaction information and/or the cardholder residential zip
codes,” and “[b]ased on the total number of transactions and the number of
local and unique cardholders . . . generat[ing] a list of recommended
merchants.” Spec. ¶ 1; Abstract.
Claims 1, 12, and 18 are independent. Independent claim 1,
reproduced below, is exemplary of the subject matter on appeal.
1. A merchant analyzer (MA) computer system for
recommending a merchant to a candidate consumer, said MA
computer system is in communication with a payment
processor computer device and a plurality of user computer
devices, said payment processor computer device being part of
a payment processor network for processing payment card
transactions between a plurality of cardholders and a plurality
of merchants, said MA computer system comprising:
a memory device for storing data;
a database including a first data structure and a second
data structure, the database communicatively coupled to the
plurality of user computer devices, the first data structure
configured to receive and store payment card transaction
information including a merchant identifier, a type of merchant,
a zip code of each merchant involved in a payment card
transaction, an amount of purchase, a date of purchase, a
cardholder identifier, and a zip code of each cardholder
involved in the payment card transaction, the second data
structure configured to include recommendation information
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including a list of recommended merchants including merchant
information, each merchant of the list of recommended
merchants being linked to a total number of transactions for the
corresponding merchant, a number of local cardholders
associated with the corresponding merchant, and a number of
unique cardholders for the corresponding merchant; and
a processor in communication with said memory device
and the database, said processor programmed to:
collect payment card transaction information, from the
payment processor computer device associated with the
payment processor network configured to process payment card
transactions, for transactions between a plurality of cardholders
and a plurality of merchants during a predetermined time
period, the payment card transaction information including a
merchant identifier associated with each transaction;
analyze the payment card transaction information to
identify a residential zip code associated with each cardholder
included in the plurality of cardholders, each cardholder
identified by a cardholder identifier;
analyze the payment card transaction information to
identify a merchant zip code associated with each merchant
included in the plurality of merchants, wherein the plurality of
merchants includes brick and mortar merchant locations;
store, within the first data structure of the database for
each payment card transaction included in the payment card
transaction information, the identified residential zip code along
with the corresponding cardholder identifier and the merchant
zip code along with the corresponding merchant identifier;
determine the total number of transactions for each
merchant identifier based, at least in part, on the payment card
transaction information;
determine the number of local cardholders from the
plurality of cardholders associated with each merchant
identifier, wherein the number of local cardholders is
determined by comparing the residential zip code stored in the
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first data structure to the merchant zip code of each merchant
identifier stored in the first data structure;
determine the number of unique cardholders from the
plurality of cardholders associated with each merchant
identifier based, at least in part, on the payment card transaction
information, wherein the number of unique cardholders
represent a number of cardholders engaged in at least one
transaction with the corresponding merchant, wherein a
cardholder is unique when the cardholder has not previously
transacted with a particular merchant during the predetermined
time period, and wherein the at least one transaction was
performed after a predetermined time period;
generate a list of recommended merchants, wherein the
list of recommended merchants reflects the total number of
transactions for each merchant identifier, the number of local
cardholders associated with each merchant identifier, and the
number of unique cardholders associated with each merchant
identifier;
store, in the second data structure of the database, the list
of recommended merchants, wherein each merchant of the list
of recommended merchants is linked to the total number of
transactions for the corresponding merchant, the number of
local cardholders associated with the corresponding merchant,
and the number of unique cardholders for the corresponding
merchant;
receive, from a user computer device of the plurality of
user computer devices, in response to user inputs made using a
merchant recommender computer application running on the
user computer device, a geographic location to search for
recommended merchants, wherein the user computer device is
associated with the candidate consumer;
sort, based on i) the geographic location to search, ii) the
total number of transactions for each merchant identifier, iii) the
number of local cardholders associated with each merchant
identifier, and iv) the number of unique cardholders associated
with each merchant identifier, the list of recommended
merchants previously stored in the second data structure to
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generate a part of the list of recommended merchants to provide
to the candidate consumer; and
transmit, to the user computer device, the generated part
of the list of recommended merchants, wherein the user
computer device is configured to display the part of the list of
recommended merchants to the candidate consumer.
App. Br. 16–25 (Claims App.).

Examiner’s Rejection
Claims 1, 2, 4, 5, 7–13, 15, 17, 18, and 20 stand rejected under
35 U.S.C. § 101 because the claimed invention is directed to an abstract idea
without significantly more. Final Act. 2–14.

ANALYSIS
In support of the § 101 rejection of claims 1, 2, 4, 5, 7–13, 15, 17, 18,
and 20, the Examiner determines Appellants’ claims are “directed to a
method of recommending merchants to a candidate consumer, which is an
abstract idea in the field of [a] fundamental economic practice,” the method
“fall[ing] under certain methods of organizing human activity, and
specifically under ‘commercial or legal interactions’, which . . . include
‘advertising, marketing or sales activities or behaviors.’” Final Act. 2–3, 16;
Ans. 15–16, 22 (citing USPTO, 2019 Revised Patent Subject Matter
Eligibility Guidance, 84 Fed. Reg. 50, 50–57 (Jan. 7, 2019) (“2019 Revised
Guidance”)).
The Examiner then determines the claim elements, when analyzed
individually and as an ordered combination, do not amount to significantly
more than the abstract idea. Final Act. 3, 8.

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Legal Framework
To determine whether claims are patent eligible under § 101, we apply
the Supreme Court’s two-step framework articulated in Alice Corp. v. CLS
Bank Int’l, 573 U.S. 208 (2014). First, we determine whether the claims are
directed to a patent-ineligible concept: laws of nature, natural phenomena,
and abstract ideas. Id. at 216. If so, we then proceed to the second step to
consider the elements of the claims “individually and ‘as an ordered
combination’” to determine whether there are additional elements that
“‘transform the nature of the claim’ into a patent-eligible application.” Id. at
217. In other words, the second step is to “search for an ‘inventive
concept’—i.e., an element or combination of elements that is ‘sufficient to
ensure that the patent in practice amounts to significantly more than a patent
upon the [ineligible concept] itself.’” Id. at 218 (alteration in original).
The Federal Circuit has described the Alice step-one inquiry as
looking at the “focus” of the claims, their “character as a whole,” and the
Alice step-two inquiry as looking more precisely at what the claim elements
add—whether they identify an “inventive concept” in the application of the
ineligible matter to which the claim is directed. See Elec. Power Grp., LLC
v. Alstom S.A., 830 F.3d 1350, 1353 (Fed. Cir. 2016); Enfish, LLC v.
Microsoft Corp., 822 F.3d 1327, 1335–36 (Fed. Cir. 2016); Internet Patents
Corp. v. Active Network, Inc., 790 F.3d 1343, 1346 (Fed. Cir. 2015).
In an effort to achieve clarity and consistency in how the U.S. Patent
and Trademark Office (the “Office”) applies the Supreme Court’s two-step
framework, the Office recently published revised guidance interpreting
governing case law and establishing a framework to govern all patent-
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eligibility analysis under Alice and § 101, effective as of January 7, 2019.
Revised Guidance, 84 Fed. Reg. at 50–57.
2019 Revised Guidance
Under the Revised Guidance, we first look under Alice step 1 or “Step
2A” to whether the claim recites:
(1) Prong One: any judicial exceptions, including certain
groupings of abstract ideas (i.e., [i] mathematical concepts,
[ii] mental processes, or [iii] certain methods of organizing
human activity such as a fundamental economic practice or
managing personal behavior or relationships or interactions
between people); and

(2) Prong Two: additional elements that integrate the judicial
exception into a practical application (see Manual of Patent
Examining Procedure (“MPEP”) §§ 2106.05(a)–(c), (e)–
(h)).3
See 2019 Revised Guidance, 84 Fed. Reg. at 51–52, 55, Revised Step 2A,
Prong One (Abstract Idea) and Prong Two (Integration into A Practical
Application). Only if a claim: (1) recites a judicial exception, and (2) does
not integrate that exception into a practical application, do we then evaluate
whether the claim provides an “inventive concept” under Alice step 2 or
“Step 2B.” See 2019 Revised Guidance at 56; Alice, 573 U.S. at 217–18.
For example, we look to whether the claim:
1) adds a specific limitation beyond the judicial exception that
is not “well-understood, routine, conventional” in the field
(see MPEP § 2106.05(d)); or

2) simply appends well-understood, routine, and conventional
activities previously known to the industry, specified at a
high level of generality, to the judicial exception.

3 All references to the MPEP are to the Ninth Edition, Revision 08.2017
(rev. Jan. 2018).
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See 2019 Revised Guidance, 84 Fed. Reg. at 56.
Alice/Mayo—Step 1 (Abstract Idea)
Step 2A–Prongs 1 and 2 identified in the Revised Guidance
Step 2A—Prong 1
Appellants argue claims 1, 12, and 18 are not directed to an abstract
idea. App. Br. 9, 11–13; Reply Br. 1–5. Appellants assert “[p]erforming
data manipulations at th[e] level of specificity [recited in claims 1, 12, and
18] is not reasonably construed as a mere method of organizing human
activity” because “the claim limitations themselves are narrowly focused on
a particular sequence of actions performed by a computer device to analyze
and aggregate actual payment card transaction data to determine which
merchants are most visited by local and unique cardholders,” such actions
being “technical limitations that involve specific data manipulations.” App.
Br. 11; see also Reply Br. 2–3. Appellants further argue the claimed
“collecting payment card transaction information is ‘not a mathematical
concept, an identified method of organizing human activity, or a mental
process’ for at least the same reasons that ‘collecting usage information’ [in
Appeal No. 2017-002898]” was found not to be “a mathematical concept, an
identified method of organizing human activity, or a mental process.” App.
Br. 11.
Appellants’ arguments are not persuasive. At the outset, we note
Appellants argue independent claims 1, 12, and 18 together, further
providing specific arguments for claim 1. See App. Br. 9, 11; Reply Br. 5.
Therefore, we select independent claim 1 as the representative claim for the
group and address Appellants’ arguments thereto. See 37 C.F.R.
§ 41.37(c)(1)(iv) (2017).
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Here, representative claim 1 recites a merchant analyzer (MA)
computer system that performs a method resulting in a list of recommended
merchants for an interested consumer. See Spec. ¶¶ 17 (describing “methods
and systems for providing cardholders objective and reputable information
for making entertainment decisions among numerous available merchants”),
96 (describing “a method and system of ranking merchants according to
purchasing behaviors of local cardholders provid[ing] a cost-effective and
reliable means for maintaining contact with a customer by merchants and a
network interchange provider” to “engage cardholders and merchants in an
enhanced purchasing experience in a cost-effective and reliable manner”).
More specifically, representative claim 1 recites the following
limitations: (1) “receive and store payment card transaction information”
including “a merchant identifier, a type of merchant, a zip code of each
merchant involved in a payment card transaction, an amount of purchase, a
date of purchase, a cardholder identifier, and a zip code of each cardholder
involved in the payment card transaction,” store “recommendation
information” including “a list of recommended merchants including
merchant information, each merchant of the list of recommended merchants
being linked to a total number of transactions for the corresponding
merchant, a number of local cardholders associated with the corresponding
merchant, and a number of unique cardholders for the corresponding
merchant,” “store . . . for each payment card transaction included in the
payment card transaction information, the identified residential zip code
along with the corresponding cardholder identifier and the merchant zip
code along with the corresponding merchant identifier,” and “store . . . the
list of recommended merchants” with “each merchant of the list of
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recommended merchants . . . [being] linked to the total number of
transactions for the corresponding merchant, the number of local cardholders
associated with the corresponding merchant, and the number of unique
cardholders for the corresponding merchant”; (2) “collect payment card
transaction information . . . for transactions between a plurality of
cardholders and a plurality of merchants during a predetermined time period,
the payment card transaction information including a merchant identifier
associated with each transaction”; (3) “analyze the payment card transaction
information to identify a residential zip code associated with each cardholder
included in the plurality of cardholders, each cardholder identified by a
cardholder identifier,” “analyze the payment card transaction information to
identify a merchant zip code associated with each merchant included in the
plurality of merchants, wherein the plurality of merchants includes brick and
mortar merchant locations,” “determine the total number of transactions for
each merchant identifier based, at least in part, on the payment card
transaction information,” “determine the number of local cardholders from
the plurality of cardholders associated with each merchant identifier,
wherein the number of local cardholders is determined by comparing the
residential zip code . . . to the merchant zip code of each merchant
identifier,” “determine the number of unique cardholders from the plurality
of cardholders associated with each merchant identifier based, at least in
part, on the payment card transaction information” wherein “the number of
unique cardholders represent a number of cardholders engaged in at least
one transaction with the corresponding merchant” and “a cardholder is
unique when the cardholder has not previously transacted with a particular
merchant during the predetermined time period, and wherein the at least one
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transaction was performed after a predetermined time period”; (4) “generate
a list of recommended merchants, wherein the list of recommended
merchants reflects the total number of transactions for each merchant
identifier, the number of local cardholders associated with each merchant
identifier, and the number of unique cardholders associated with each
merchant identifier”; (5) “receive [from a candidate consumer’s device] . . .
a geographic location to search for recommended merchants,” “sort, based
on i) the geographic location to search, ii) the total number of transactions
for each merchant identifier, iii) the number of local cardholders associated
with each merchant identifier, and iv) the number of unique cardholders
associated with each merchant identifier, the list of recommended
merchants” to “generate a part of the list of recommended merchants to
provide to the candidate consumer,” and “transmit, to the user computer
device, the generated part of the list of recommended merchants”; and (6)
“display the part of the list of recommended merchants to the candidate
consumer.” App. Br. 16–18 (Claim 1). These limitations, under their
broadest reasonable interpretation, recite ranking and recommending
merchants to potential consumers to improve consumer experience and
increase the merchants’ sales, which is a fundamental economic practice that
is common in the financial and commercial industry. See Spec. ¶¶ 2–3;
Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363,
1370 (Fed. Cir. 2015) (“An advertisement taking into account the time of
day and tailoring the information presented to the user based on that
information is a[] ‘fundamental . . . practice long prevalent in our system,’”
and “the fact that the web site returns the pre-designed ad more quickly than
a newspaper could send the user a location-specific advertisement insert
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does not confer patent eligibility”); OIP Technologies, Inc. v. Amazon.com,
Inc., 788 F.3d 1359, 1362 (Fed. Cir. 2015) (the “concept of ‘offer based
pricing’ is similar to other ‘fundamental economic concepts’ found to be
abstract ideas by the Supreme Court and this court”).
For example, limitation (1) in claim 1 describes accessing and storing
payment card transaction information, merchant data including merchant
locations, consumer data including merchants frequented by the consumers,
and merchant recommendations, which is an activity ordinarily performed
by business entities (such as market research entities) that cumulate
merchant data, and by payment processing networks and credit card
networks that cumulate consumer transaction data. Limitation (2) in claim 1
describes collecting payment transaction data including cardholders’
transaction information and merchants associated with the transactions,
which is an activity ordinarily performed by businesses and other entities
associated with (or working with) a payment or card network to study
consumer interests and market segmentation. See Spec. ¶¶ 25, 27, 29, 33,
61. Limitation (3) in claim 1 describes an analysis of consumers’ transaction
information to determine consumers’ shopping locations and shopping
activity at street stores and other merchants having physical locations
identified by zip codes—activities ordinarily performed by market research
entities when cumulating and analyzing consumer data to determine
consumers’ interests and shopping behavior. Limitation (4) in claim 1
describes ranking merchants based on consumer interest, which are activities
ordinarily performed by marketing entities and services that analyze
commercial and retail activity to provide retail and shopping
recommendations to potential customers. Limitation (5) in claim 1 describes
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providing merchant lists to consumers based on consumers’ geographic
locations, which is an activity ordinarily performed by marketing entities
providing targeted shopping (and other commercial) recommendations based
on location (e.g., zip code, town, or city). See Spec. ¶ 66. Limitation (6) in
claim 1 describes displaying merchant recommendations to a consumer—an
activity ordinarily performed by a marketing service providing shopping
information to potential consumers.
Thus, limitations (1)–(6) in claim 1 recite ranking merchants and
recommending merchants to potential consumers to improve consumer
experience and increase the merchants’ sales, which is a known business
activity and a fundamental economic practice in our system of commerce,
similar to other concepts identified by the courts as abstract ideas. For
example, like the risk hedging in Bilski, the intermediated settlement in
Alice, and customizing of information based on information known about a
user in Intellectual Ventures, ranking merchants and recommending them to
consumers is a fundamental business practice long prevalent in our system
of commerce. Ans. 15–16; see Bilski v. Kappos, 561 U.S. 593, 599, 611–12
(2010) (risk hedging); Alice, 573 U.S. at 215–19 (intermediated settlement
of traded or exchanged financial obligations to mitigate the risk that one
party will not perform); Intellectual Ventures I LLC v. Capital One Bank
(USA), 792 F.3d 1363, 1369 (Fed. Cir. 2015) (“tailoring content based on the
viewer’s location or address. . . . is ‘a fundamental . . . practice long
prevalent in our system,’” similar to using “newspaper inserts [that] had
often been tailored based on information known about the customer—for
example, a newspaper might advertise based on the customer’s location”);
Affinity Labs of Texas, LLC v. Amazon.com, 838 F.3d 1266, 1269, 1271
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(Fed. Cir. 2016) (“[T]he concept of delivering user-selected media content to
portable devices [(in a method for targeted advertising in which an
advertisement is selected for delivery to the user of a portable device based
on at least one piece of demographic information about the user)] is an
abstract idea,” and “‘customizing information based on . . . information
known about the user’ is an abstract idea” (citing Intellectual Ventures, 792
F.3d at 1369).); Morsa v. Facebook, Inc., 77 F. Supp. 3d 1007, 1013 (C.D.
Cal. 2014), aff’d, 622 F. App’x 915 (Fed. Cir. 2015) (“The concept of
gathering information about one’s intended market and attempting to
customize the information then provided is as old as the saying, ‘know your
audience.’” (quoting OpenTV, Inc. v. Netflix Inc., 76 F. Supp. 3d 886, 893
(N.D. Cal. 2014))).
Ranking merchants and recommending them to consumers is also a
building block of a market economy and, like content customization and ad
targeting in Intellectual Ventures I and Affinity Labs, is an “abstract idea”
beyond the scope of § 101. See Alice, 573 U.S. at 219. Thus, similar to the
concept of intermediated settlement in Alice, the concept of hedging in
Bilski, and customizing information based on information known about users
in Intellectual Ventures, the concept of ranking merchants and
recommending them to consumers (as in Appellants’ claim 1) “[is] a
fundamental economic practice long prevalent in our system of commerce.”
See Alice, 573 U.S. at 219; Bilski, 561 U.S. at 611–12 (“Claims 1 and 4 in
petitioners’ application explain the basic concept of hedging, or protecting
against risk.”).
We, therefore, conclude limitations (1)–(6) in representative claim 1,
and similar limitations in grouped claims 12 and 18, recite ranking and
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recommending merchants to consumers, which is a fundamental economic
practice and one of the certain methods of organizing human activity
identified in the Revised Guidance, and therefore, an abstract idea. Ans. 15–
16; see 2019 Revised Guidance (Revised Step 2A, Prong One), 84 Fed. Reg.
at 52 (describing an abstract idea category of “[c]ertain methods of
organizing human activity—fundamental economic principles or practices
. . . commercial or legal interactions (including . . . advertising, marketing or
sales activities or behaviors; business relations)”), 54.
Appellants argue the claimed “collecting payment card transaction
information is ‘not . . . an identified method of organizing human activity
. . .’ for at least the same reasons that ‘collecting usage information’ [in
Appeal No. 2017-002898]” was found not to be “an identified method of
organizing human activity.” App. Br. 11. We disagree because (1) Appeal
No. 2017-002898 does not have any precedential value relative to the instant
application; (2) as recognized by the Examiner, Appellants’ claimed
collection of payment card transaction information is “not fully analogous”
to the “collecting” in Appeal No. 2017-002898 (Ans. 19–20); and (3) the
claims in Appeal No. 2017-002898 were found patent eligible not because of
the “collecting usage information” but because “the claims are directed to a
technological solution to a technical problem.” See Ex Parte Fanaru,
Appeal No. 2017-002898, 2019 WL 325946, at *5 (PTAB Jan. 17, 2019).
“[C]ollecting information” alone, without more, is “within the realm of
abstract ideas.” Elec. Power Grp., 830 F.3d at 1353–54; see also Internet
Patents Corp., 790 F.3d at 1349; Digitech Image Techs., LLC v. Elecs. for
Imaging, Inc., 758 F.3d 1344, 1351 (Fed. Cir. 2014); CyberSource Corp. v.
Retail Decisions, Inc., 654 F.3d 1366, 1370 (Fed. Cir. 2011); Smart Systems
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Innovations v. Chicago Transit Auth., 873 F.3d 1364, 1371–72 (Fed. Cir.
2017) (claims to “acquiring identification data from a bankcard, using the
data to verify the validity of the bankcard, and denying access to a transit
system if the bankcard is invalid” are “directed to the formation of financial
transactions in a particular field (i.e., mass transit) and data collection related
to such transactions,” thereby “directed to the collection, storage, and
recognition of data” and thus “directed to an abstract idea”).
In conclusion, representative claim 1, and grouped independent claims
12 and 18, recite a fundamental economic practice.
Step 2A—Prong 2 (Integration into Practical Application)
Under Revised Step 2A, Prong Two of the Revised Guidance,
Appellants argue the “claims provide a specific improvement over prior
systems and are directed to a practical application, such that the present
claims are not directed to an abstract idea under the Second Prong of Step
2A.” App. Br. 12; Reply Br. 3–5. In particular, Appellants argue the claims
“recite a specific manner of electronically analyzing and aggregating actual
payment card transaction data to determine which merchants are most
visited by local and unique cardholders, providing a specific improvement
over prior systems.” App. Br. 12. Appellants assert the claims recite
“technical limitations that involve specific data manipulations” and “provide
an improvement to a specific technology”—particularly, to “merchant
recommendation system technology”—similar to technological
improvements provided by the claims in McRO and Enfish. App. Br. 11–13
(citing McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299 (Fed.
Cir. 2016); Enfish, 822 F.3d 1327); Reply Br. 4–5. According to Appellants,
“instead of relying on user-submitted scores and reviews, the systems and
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methods recited in the present claims aggregate and analyze actual payment
card transaction data to determine which merchants are most visited by
local cardholders and unique cardholders,” providing “improved and more
accurate merchant recommendations” and “an improvement to the technical
field of merchant recommendation systems.” App. Br. 12; see also Reply
Br. 3–4.
However, we discern no additional element (or combination of
elements) recited in Appellants’ claims 1, 12, and 18 that may have
integrated the judicial exception into a practical application. See 2019
Revised Guidance, 84 Fed. Reg. at 54–55. For example, Appellants’
claimed additional elements (e.g., “MA computer system,” “payment
processor computer device,” “payment processor network,” “user computer
devices,” “memory device,” “database including a first data structure and a
second data structure,” “processor,” and “computer-readable storage media”)
do not: (1) improve the functioning of a computer or other technology; (2)
are not applied with any particular machine (except for a generic computer);
(3) do not effect a transformation of a particular article to a different state;
and (4) are not applied in any meaningful way beyond generally linking the
use of the judicial exception to a particular technological environment, such
that the claim as a whole is more than a drafting effort designed to
monopolize the exception. See MPEP §§ 2106.05(a)–(c), (e)–(h); Ans. 16,
19, 21.
Here, Appellants’ claim 1 merely links the use of a judicial exception
to a particular technological environment. That is, although Appellants’
claim recites hardware components (generic processors and computer
devices, a memory, database, and storage media), the processors, computer
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devices, memory, database, and storage media are configured to perform
numerous real-world functions and operations that computer components
would normally be expected to perform, adding nothing of substance to the
underlying abstract idea. Ans. 16. It is clear from the claims and the
Specification (describing “a Windows® environment” or a “system . . . run
on a mainframe environment and a UNIX® server environment” with an
“application [that] is flexible and designed to run in various different
environments without compromising any major functionality,” “[c]lient
systems 114 [that] could be any device capable of interconnecting to the
Internet including a web-based phone, PDA, or other web-based connectable
equipment,” “a generic computing device 800 and a generic mobile
computing device 850, which may be used with the techniques described
here,” the “[c]omputing device 800 . . . intended to represent various forms
of digital computers, such as laptops, desktops, workstations, personal
digital assistants, servers, blade servers, mainframes, and other appropriate
computers,” “a standard server 820,” a “processor . . . [that] refers to central
processing units, microprocessors, microcontrollers, reduced instruction set
circuits (RISC), application specific integrated circuits (ASIC), logic
circuits, and any other circuit or processor capable of executing the functions
described herein,” “a transaction card system, such as a credit card payment
system using the MasterCard® interchange network,” a “memory 804 [that]
is a volatile memory unit or units” or “a non-volatile memory unit or units
. . . [or] another form of computer-readable medium, such as a magnetic or
optical disk,” and “a single database having separated sections or partitions”
or “multiple databases, each being separate from each other”), these
limitations require no improved processor, computer device, memory,
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database, or storage medium. See Spec. ¶¶ 26, 29, 37, 40, 55, 75–78, 80, 85,
92–94; Ans. 19, 21, 23. Thus, the claims’ limitations are not indicative of
“integration into a practical application.” Rather, the processors and
computer devices, memory, and database are readily available computing
elements using their already available basic functions as tools in executing
the claimed ranking and recommending merchants. See SAP Am., Inc. v.
InvestPic LLC, 898 F. 3d 1161 (Fed. Cir. 2018). Contrary to Appellants’
arguments (see App. Br. 11–13), claim 1 does not recite “technical
limitations” or technical improvements of electronic data manipulation and
aggregation techniques.
We are also unpersuaded by Appellants’ arguments that the claims are
“directed to a practical application” under the Step 2A, Prong Two of the
Revised Guidance because the claims improve the technical field of
merchant recommendation systems. See App. Br. 12; Reply Br. 4. For
business-centric inventions such as Appellants’ invention involving ranking
and recommending merchants to consumers, the “integration into a practical
application” prong requires consideration of whether the claims purport to
provide “a technical solution to a technical problem” as required by the
Federal Circuit’s precedential decisions in (1) DDR Holdings, LLC v.
Hotels.com, L.P., 773 F.3d 1245, 1257 (Fed. Cir. 2014) and (2) Amdocs
(Isr.) Ltd. v. Openet Telecom, Inc., 841 F.3d 1288 (Fed. Cir. 2016). See
MPEP § 2106.05(a).
For example, the Federal Circuit found DDR’s claims are patent-
eligible under section 101 because DDR’s claims: (1) do not merely recite
“the performance of some business practice known from the pre-Internet
world” previously disclosed in Bilski and Alice; but instead (2) provide a
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technical solution to a technical problem unique to the Internet, i.e., a
“solution . . . necessarily rooted in computer technology in order to
overcome a problem specifically arising in the realm of computer networks.”
DDR, 773 F.3d at 1257. Likewise, the Federal Circuit also found Amdocs’
claims patent-eligible under section 101 because like DDR, Amdocs’ claims
“entail[] an unconventional technological solution (enhancing data in a
distributed fashion) to a technological problem (massive record flows which
previously required massive databases)” and “improve the performance of
the system itself.” Amdocs, 841 F.3d at 1300, 1302.
Contrary to Appellants’ arguments (see App. Br. 12; Reply Br. 4),
providing “improved and more accurate merchant recommendations” to
consumers does not provide any “technical solution to a technical problem”
as contemplated by the Federal Circuit in DDR and Amdocs. See MPEP
§ 2106.05(a). Providing improved merchant recommendations to consumers
is neither technology nor a technical solution to a technological problem.
Ans. 16, 20–21. Instead, limitations of Appellants’ claims 1, 12, and 18
recite the abstract idea, and thus, are not “additional elements recited in the
claim beyond the judicial exception.” 2019 Revised Guidance, 84 Fed. Reg.
at 54–55 (emphasis added). In contrast to DDR and Amdocs, Appellants’
abstract idea of ranking and recommending merchants to consumers does
not provide a technical solution to a technical problem unique to the Internet,
i.e., a “solution . . . necessarily rooted in computer technology in order to
overcome a problem specifically arising in the realm of computer networks.”
DDR, 773 F.3d at 1257. Nor does Appellants’ invention entail, like Amdocs,
any “unconventional technological solution (enhancing data in a distributed
fashion) to a technological problem (massive record flows which previously
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required massive databases)” and “improve the performance of the system
itself.” Amdocs, 841 F.3d at 1300, 1302. Instead, the solution proposed by
Appellants is simply to improve merchant recommendations and consumer
experience, and not to improve the technology.
We also note Appellants’ reliance on McRO and Enfish is misplaced.
See App. Br. 12. For example, McRO’s ’576 patent (U.S. Patent No.
6,307,576) describes computer software for matching audio to a 3D
animated mouth movement to provide lip-synched animation. McRO’s
claims contain (i) specific limitations regarding a set of rules that “define[ ] a
morph weight set stream as a function of phoneme sequence and times
associated with said phoneme sequence” to enable computers to produce
“accurate and realistic lip synchronization and facial expressions in animated
characters” (McRO, 837 F.3d at 1313) and, when viewed as a whole, are
directed to (ii) a “technological improvement over the existing, manual 3–D
animation techniques” that uses “limited rules in a process specifically
designed to achieve an improved technological result in conventional
industry practice.” Id. at 1316. Enfish’s data storage and retrieval method
and system recites a “self-referential table . . . [for a computer database]
[which] is a specific type of data structure designed to improve the way a
computer stores and retrieves data in memory.” Enfish, 822 F.3d at 1336,
1339.
In contrast to Enfish and McRO, Appellants’ Specification and claims
do not describe technological improvements, or a specific improvement to
the way computers store and retrieve data in memory. See Enfish, 822 F.3d
at 1336, 1339; Ans. 16, 20–21. Rather, Appellants’ Specification and claims
describe “methods and systems for recommending merchants to a potential
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consumer based at least in part on the potential consumer’s search location
and payment transaction histories of local payment cardholders.” See Spec.
¶¶ 1, 17 (“methods and systems for providing cardholders objective and
reputable information for making entertainment decisions among numerous
available merchants”), 96 (“method and system of ranking merchants
according to purchasing behaviors of local cardholders provid[ing] a cost-
effective and reliable means for maintaining contact with a customer by
merchants and a network interchange provider” to “engage cardholders and
merchants in an enhanced purchasing experience in a cost-effective and
reliable manner”).
For these reasons, we agree with the Examiner’s determination that
Appellants’ claims 1, 2, 4, 5, 7–13, 15, 17, 18, and 20 are directed to an
abstract idea that does not integrate into a practical application. See Ans.
15–21.
Alice/Mayo—Step 2 (Inventive Concept)
Step 2B identified in the Revised Guidance
In the second step of the Alice inquiry, Appellants argue claims 1, 12,
and 18 recite significantly more than a judicial exception for the reasons
that: (1) “[l]ike the filtering system of BASCOM, the specific arrangement
and distribution of functionality provided in the pending claims facilitates
the practical application” of “analyzing electronic payment transaction
information and data signals from a payment network to generate merchant
recommendations for displaying to a consumer” using a “novel combination
of correlating electronic data signals, at a central location (e.g., the MA
computer device), transmitted by merchant computing devices to the
payment processing network” (App. Br. 13–14 (citing Bascom Glob.
Internet Servs., Inc. v. AT&T Mobility LLC, 827 F.3d 1341 (Fed. Cir. 2016));
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Reply Br. 5–6); (2) similar to Bascom, the claims include an “inventive
concept . . . in the non-conventional and non-generic arrangement of pieces”
(App. Br. 13); and (3) the “claims do not merely recite an MA computer
device that is a server computer that collects and sends data as part of
routine and conventional Internet activities,” rather “the MA computer
device is more than a generic server computer that collects and sends data”
and “the MA computer device is recited as part of a specific computer
architecture” in which the “MA computer system is in communication with a
payment processor computer device and a plurality of user computer
devices,” thereby “enabl[ing] the MA computer device to leverage actual
payment card transaction data to generate a list of recommended merchants”
(Reply Br. 5–6).
Appellants’ arguments are not persuasive. As recognized by the
Revised Guidance, an “inventive concept” under Alice step 2 can be
evaluated based on whether an additional element or combination of
elements:
(1) “[a]dds a specific limitation or combination of limitations
that are not well-understood, routine, conventional
activity in the field, which is indicative that an inventive
concept may be present;” or
(2) “simply appends well-understood, routine, conventional
activities previously known to the industry, specified at a
high level of generality, to the judicial exception, which
is indicative that an inventive concept may not be
present.”
See 2019 Revised Guidance, 84 Fed. Reg. at 56.
In this case, however, we find no element or combination of elements
recited in Appellants’ claim 1 that contains any “inventive concept” or adds
anything “significantly more” to transform the abstract concept into a patent-
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eligible application. Alice, 573 U.S. at 221. For example, Appellants’
abstract idea of ranking and recommending merchants is not rooted in
computer technology, and does not provide a technical solution to a
technical problem unique to the Internet, i.e., a “solution . . . necessarily
rooted in computer technology in order to overcome a problem specifically
arising in the realm of computer networks” as the claims in DDR. DDR, 773
F.3d at 1257. Rather, Appellants’ claim 1 addresses a business problem
(presenting better recommendations of merchants, e.g., restaurants) with a
business solution (recommending restaurants based on local residents’
interactions with those restaurants, and based on new clients’ interactions
with the restaurants) rather than a technological solution. Ans. 20; see Spec.
¶¶ 1, 3, 20–23, 63, 73, 96. Appellants also have not demonstrated their
claimed generic processors, memory, database, and storage media are able to
perform functions that are not merely generic, as the claims in DDR. See
DDR Holdings, 773 F.3d at 1258. Appellants’ claim 1 merely recites
generic processor, computer system, user devices, memory, and database
structures storing, sending and receiving data by generic data
communication techniques, and analyzing data to produce merchant
recommendations. Thus, we are not persuaded that claim 1 recites an
improved computer architecture, or an “MA computer device [that] is more
than a generic server computer that collects and sends data” as Appellants
assert. See Reply Br. 5–6.
With respect to Bascom, Appellants’ reliance on Bascom is also
misplaced. For example, Bascom’s patent-eligible ordered combination of
claim limitations contains an “inventive concept [that] harnesses [a] . . .
technical feature of network technology in a filtering system by associating
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individual accounts with their own filtering scheme and elements while
locating the filtering system on an ISP [(Internet Service Provider)] server.”
See Bascom, 827 F.3d at 1350. Bascom’s claimed ordered combination
“improve[s] the performance of the computer system itself” with a
“technology-based solution . . . to filter content on the Internet that
overcomes existing problems with other Internet filtering systems.” See
Bascom, 827 F.3d at 1351–52 (internal citation omitted). Appellants’
abstract idea of ranking and recommending merchants for consumers does
not provide any particular practical application as required by Bascom.
Instead, Appellants’ invention uses generically-claimed and arranged
computing elements to perform the abstract idea. Ans. 21–23. Appellants
assert that “[s]imilar to BASCOM, Appellant[s’] recited system includes the
use of elements at a unique location that provides an advantage over the
prior art” and, thus, “Appellant[s] ‘[are] not claiming the idea of
[recommending merchants to a candidate consumer] simply applied to the
Internet. . . . [but] is instead claiming a technology-based solution.” App.
Br. 14 (citing Bascom, 827 F.3d at 1350–51). We remain unpersuaded
because Appellants’ claim 1 does not recite specific locations as in Bascom’s
claims. Particularly, Bascom’s inventive concept includes “the installation
of a filtering tool at a specific location, remote from the end-users, with
customizable filtering features specific to each end user” thereby “giv[ing]
the filtering tool both the benefits of a filter on a local computer and the
benefits of a filter on the ISP server” and “giv[ing] users the ability to
customize filtering for their individual network accounts.” See Bascom, 827
F.3d at 1350, 1352. The Federal Circuit recognized that Bascom’s
installation of an Internet content filter at a particular network location is “a
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technical improvement over prior art ways of filtering such content” because
such an arrangement advantageously allows the Internet content filter to
have “both the benefits of a filter on a local computer and the benefits of a
filter on the ISP server” and “give[s] users the ability to customize filtering
for their individual network accounts.” Bascom, 827 F.3d at 1350, 1352.
In contrast, Appellants’ claim 1 recites a MA computer system that “is
in communication with a payment processor computer device and a plurality
of user computer devices” and “collect[s] payment card transaction
information, from the payment processor computer device associated with
the payment processor network,” which is dissimilar from Bascom’s
inventive concept [that] harnesses this technical feature of
network technology [installation of a filtering tool at a specific
location, remote from the end-users, with customizable filtering
features specific to each end user] in a filtering system by
associating individual accounts with their own filtering scheme
and elements while locating the filtering system on an ISP
server.
See Bascom, 827 F.3d at 1350. Thus, we disagree with Appellants that
claim 1 recites a “non-conventional and non-generic arrangement of pieces,”
or that it “claim[s] a technology-based solution” similar to Bascom because
Appellants’ claimed “system includes the use of elements at a unique
location” and “correlate[s] electronic data signals, at a central location.”
See App. Br. 13–14 (emphasis added).
Additionally, Appellants’ Specification describes generic computing
elements performing generic data processing, storage, and display functions,
and Appellants’ claim 1 uses generic technology to perform data analysis
and calculating steps. See Spec. ¶¶ 26, 29, 37, 40, 55, 75–78, 80, 85, 92–94.
“[T]he use of generic computer elements like a microprocessor or user
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interface” to perform conventional computer functions “do not alone
transform an otherwise abstract idea into patent-eligible subject matter.”
FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1096 (Fed. Cir.
2016) (citing DDR Holdings, 773 F.3d at 1256). As our reviewing court has
observed, “after Alice, there can remain no doubt: recitation of generic
computer limitations does not make an otherwise ineligible claim patent-
eligible.” DDR Holdings, 773 F.3d at 1256 (citing Alice, 573 U.S. at 222–
23).
Because Appellants’ independent claims 1, 12, and 18 are directed to
a patent-ineligible abstract concept and do not recite an “inventive concept”
by providing a solution to a technical problem under the second step of the
Alice analysis, we sustain the Examiner’s § 101 rejection of independent
claims 1, 12, and 18, and their dependent claims 2, 4, 5, 7–11, 13, 15, 17,
and 20 not separately argued.

CONCLUSION
On the record before us, we conclude Appellants have not
demonstrated the Examiner erred in rejecting claims 1, 2, 4, 5, 7–13, 15, 17,
18, and 20 under 35 U.S.C. § 101.
DECISION
As such, we AFFIRM the Examiner’s rejection of claims 1, 2, 4, 5, 7–
13, 15, 17, 18, and 20 under 35 U.S.C. § 101.
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