IN THE UNITED STATES DISTRICT COURT
`FOR THE DISTRICT OF DELAWARE
`
`RETAILMENOT, INC.,
`
`Plaintiff,
`
`v.
`
`HONEY SCIENCE CORP.,
`
`Defendant.
`
`)
`)
`)
`)
`)
`)
`)
`)
`)
`
`C.A. No. 18-937 (CFC) (MPT)
`
`PLAINTIFF RETAILMENOT INC.’S INITIAL INVALIDITY CONTENTIONS
`
`Pursuant to the Parties’ Stipulated Order Regarding Discovery (D.I. 41) and the Delaware
`
`Default Standard for Discovery, RetailMeNot, Inc. (“RetailMeNot”) hereby submits its initial
`
`invalidity contentions concerning U.S. Patent No. 10,140,625 (“the ’625 Patent” or “the Honey
`
`Patent”), assigned to Honey Science Corp. (“Honey”).
`
`These initial invalidity contentions and accompanying documents reflect information
`
`possessed by RetailMeNot and its attorneys at the present time, without the benefit of a claim-
`
`construction order from the Court. As such, these contentions are based, at least in part, upon
`
`Honey’s apparent constructions of the asserted claims of the Honey Patent in light of the
`
`intrinsic evidence and Honey’s Initial Infringement Contentions (“IICs”), served on March 6,
`
`2019. Nothing herein, however, should be construed as an admission or acquiescence by
`
`RetailMeNot that Honey’s apparent application of the claims is correct. RetailMeNot denies
`
`infringement and expressly reserves the right to propose alternative constructions to those that
`
`Honey advocates or suggests, expressly or by inference, to rebut Honey’s actual claim-
`
`construction positions.
`
`Additional discovery may further support these invalidity contentions with respect to the
`
`Honey Patent. RetailMeNot has not, for example, received all relevant and responsive
`
`Honey Science Corp.
`Exhibit 2008
`RetailMeNot v. Honey
`IPR2019-01565
`
`Ex. 2008-0001
`
`

`

`documents from Honey or document productions and deposition testimony from third parties that
`
`are likely to have additional relevant and responsive information and materials. Accordingly,
`
`these initial invalidity contentions are made without prejudice to RetailMeNot’s right to
`
`supplement and amend as more information becomes available.
`
`RetailMeNot contends that the prior art invalidates the claims of the ’625 Patent under
`
`both the America Invents Act (“AIA”) and pre-AIA versions of 35 U.S.C. §§ 102 and 103.
`
`Nothing herein, however, should be construed as an admission or acquiescence by RetailMeNot
`
`that the ’625 Patent is entitled to a priority date before the date the AIA took effect.
`
`Additional prior art may become relevant depending on the claim-construction positions
`
`that Honey hereafter asserts and the constructions that the Court adopts. RetailMeNot’s ongoing
`
`investigations may also uncover additional prior art, and RetailMeNot further reserves the right
`
`to rely upon additional combinations of references under 35 U.S.C. § 1031 based upon arguments
`
`that Honey may hereafter raise. For example, RetailMeNot is currently unaware of the extent to
`
`which Honey may contend that elements of the claims of the ’625 patent are not disclosed in the
`
`art that RetailMeNot presents herein. RetailMeNot therefore reserves the right to supplement or
`
`modify these contentions based on further discovery and in a manner consistent with the Federal
`
`Rules of Civil Procedure and the Court’s local rules.2
`
`I. ASSERTED CLAIMS
`
`Honey asserts claims 1–5 and 7–19 of the ’625 Patent in its March 6, 2019 Initial
`
`Infringement Contentions (the “Asserted Claims”).
`
`
`1 All subsequent citations to Title 35 of the United States Code are to the pre-AIA versions of
`the relevant statutes.
`
`2 RetailMeNot anticipates asserting additional prior art based on forthcoming discovery from
`one or more third parties.
`
`
`
`2
`
`Ex. 2008-0002
`
`

`

`RetailMeNot’s Initial Invalidity Contentions are limited to the Asserted Claims. To the
`
`extent that Honey later asserts any additional claims, RetailMeNot reserves the right to
`
`supplement its contentions and assert any additional prior art to address those new claims.
`
`II.
`
`PRIORITY DATE
`
`A “patent may only claim priority to an earlier application if the earlier application
`
`fulfills the requirements of § 112, first paragraph, which requires, in part, that the application
`
`‘shall contain a written description of the invention, and of the manner and process of making
`
`and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art
`
`to which it pertains, or with which it is most nearly connected, to make and use the same.’”
`
`Chiron Corp. v. Genentech, Inc., 363 F.3d 1247, 1253 (Fed. Cir. 2004).
`
`The ’625 Patent issued from Appl. No. 15/824,237, a continuation that claims priority to
`
`a continuation-in-part (“CIP”) Appl. No. 15/461,101 (filed Mar. 16, 2017) [hereinafter “the ’101
`
`CIP”], which, in turn, claims priority to Appl. No. 14/074,707 (filed Nov. 7, 2013) [hereinafter
`
`“the ’707 application”]. The ’625 Patent also claims the benefit of provisional application No.
`
`61/796,345 (filed Nov. 8, 2012) [hereinafter “the ’345 provisional”]. RetailMeNot contends,
`
`however, that at least claims 1, 3, 9, 11, 13, 17, and 19 of the Honey Patent cannot claim priority
`
`to either the ’345 provisional or the ’707 application. Accordingly, the priority date for those
`
`claims is no earlier than March 16, 2017, the filing date of the ’101 CIP. (Moreover, as
`
`discussed in § V(a), infra, the disclosure of the ’101 CIP does not satisfy 35 U.S.C. § 112 with
`
`respect to claims 9 and 17.)
`
`Claims 1 and 11 of the ’625 Patent purportedly cover “identify[ing] a data entry interface
`
`on the webpage to input.” However, neither the ’345 provisional or the ’707 application
`
`provides an enabling disclosure of how to identify data entry interfaces, such as by examining
`
`HyperText Markup Language (HTML) content on the webpage. Claims 3 and 13 (which depend
`
`
`
`3
`
`Ex. 2008-0003
`
`

`

`on claims 1 and 11, respectively) specify that “identifying the data entry interface on the
`
`webpage includes examining HyperText Markup Language (HTML) content on the webpage,”
`
`yet neither the ’345 provisional nor the ’707 application provides any such disclosure. Instead,
`
`the ’345 provisional and the ’707 application state only that “the software system adds a code to
`
`the Code box on the merchant website and simulates a click, as though the customer were
`
`entering the code,” (’345 provisional at 4–5; see also ’707 application at 9–10), with no
`
`indication of how the software identifies the “Code box” prior to submission. Because the
`
`disclosures of the ’345 provisional and the ’707 application neither enable a POSITA to practice
`
`claims 1, 3, 11, and 13, nor demonstrate to a POSITA that the named inventors were in
`
`possession of the purported inventions, said claims are not entitled to the priority date of either
`
`the ’345 provisional or the ’707 application.
`
`Claims 9 and 17 of the ’625 Patent state that “the list of digital codes is generated using at
`
`least one of the following: Naïve Bayes Classifier algorithm, K Means Clustering algorithm,
`
`Support Vector Machine algorithm, linear regression, logic regression, and artificial neural
`
`networks.” As discussed in § V(a), infra, despite reciting similar language in the specification,
`
`the ’625 Patent does not enable or contain sufficient written description for these claims. Neither
`
`the ’345 provisional nor the ’707 application contains any mention of “Naïve Bayes Classifier
`
`algorithm, K Means Clustering algorithm, Support Vector Machine algorithm, linear regression,
`
`logic regression, [or] artificial neural networks,” let alone adequate written description or
`
`enablement of how to use these to generate lists of digital codes. Claim 19 of the ’625 Patent
`
`further recites that “the list is generated based on historical interactions of other users with the
`
`website.” But neither the ’345 provisional nor the ’707 application provides any description of
`
`the manner in which a list of codes is generated, whether “based on historical interactions” or
`
`
`
`4
`
`Ex. 2008-0004
`
`

`

`using the various techniques listed in claims 9 and 17. Because the disclosures of the ’345
`
`provisional and the ’707 application neither enable a POSITA to practice claims 9, 17, or 19, nor
`
`demonstrate to a POSITA that the named inventors were in possession of the purported
`
`inventions, said claims are not entitled to the priority date of either the ’345 provisional or the
`
`’707 application.
`
`RetailMeNot reserves the right to identify additional bases for this contention in response
`
`to Honey’s subsequent arguments and positions, any amendments that Honey makes to its own
`
`contentions, the Court’s claim construction, or information uncovered during further discovery.
`
`III.
`
`IDENTIFICATION OF PRIOR ART
`
`RetailMeNot identifies the following prior art against the ’625 Patent:
`
`Patent /
`Publication /
`Application
`No.
`
`US 9,639,853
`
`Date of
`Prior Art
`
`June 11,
`2012
`
`Title
`
`Devices, methods, and
`computer-readable media for
`redemption header for merchant
`offers
`
`US 9,679,296 November
`30, 2011
`
`Promotion code validation
`apparatus and method
`
`US 9,727,891 October 22,
`2012
`
`System and method of
`automated delivery of
`relevance-checked benefit-
`conveying codes during online
`transaction
`
`Reference
`Designation
`
`Shiffert I
`
`Prior Art
`Under 35
`U.S.C.
`
`§§ 102(a),
`(b), and (e)
`
`Lemphers
`
`Mezzacca
`
`§§ 102(a),
`(b), and (e)
`
`§§ 102(a),
`(b), and (e)
`
`US 9,754,274
`
`June 9,
`2009
`
`Single tag method for webpage
`personal customization
`
`Brussin
`
`§ 102(e)
`
`
`
`5
`
`Ex. 2008-0005
`
`

`

`Patent /
`Publication /
`Application
`No.
`
`US 9,881,315
`
`Date of
`Prior Art
`
`June 11,
`2012
`
`US 9,922,327 November
`1, 2012
`
`US 9,953,335
`
`June 11,
`2012
`
`US 9,965,769
`
`June 11,
`2012
`
`US
`2002/0010627
`
`January 24,
`2002
`
`US
`2002/0046109
`
`July 24,
`2000
`
`US
`2008/0021771
`
`May 31,
`2006
`
`US
`2017/0148046
`
`May 31,
`2011
`
`Title
`
`Systems, methods, and
`computer-readable media for a
`customizable redemption
`header for merchant offers
`across browser instances
`
`System, method, and computer
`program for providing a multi-
`merchant electronic shopping
`cart for a shopping service
`
`Devices, methods, and
`computer-readable media for
`redemption header for merchant
`offers
`
`Devices, methods, and
`computer-readable media for
`redemption header for merchant
`offers
`
`System and method for
`creation, distribution, exchange,
`redemption and tracking of
`digitally signed electronic
`coupons
`
`Method and system for
`administering a customer
`loyalty reward program using a
`browser extension
`
`Systems and methods for
`defining pricing conditions in
`electronic sales application
`environments
`
`System and method for
`consumer management
`purchasing and account
`information
`
`6
`
`Reference
`Designation
`
`Shiffert II
`
`Prior Art
`Under 35
`U.S.C.
`
`§§ 102(a),
`(b), and (e)
`
`Johnson
`
`§§ 102(a),
`(b), and (e)
`
`Shiffert III
`
`§ 102(e)
`
`Shiffert IV
`
`§ 102(e)
`
`Lerat
`
`§§ 102(a),
`(b), and (e)
`
`Leonard
`
`§§ 102(a),
`(b), and (e)
`
`Wu
`
`§§ 102(a),
`(b), and (e)
`
`Mashadi
`
`§ 102(e)
`
`Ex. 2008-0006
`
`

`

`
`
`Title
`
`Date of
`Publication
`
`Publisher
`
`Reference
`Designation
`
`Qualifies
`as Prior
`Art At
`Least
`Under 35
`U.S.C.
`
`Coupon Digger FAQ
`
`Coupon Digger demo video:
`https://www.youtube.com/
`watch?v=vp4PPgzG4Og
`
`Save Time with Coupon
`Mountain’s Coupon Digger
`
`Coupons at Checkout:
`animated GIF demo
`
`Coupon Follow demo
`video:
`https://www.youtube.com/
`watch?v=O5zopu1-Mg
`PriceBlink
`
`Booly FAQ
`
`Booly
`
`5 Firefox Shopping Add-
`ons to Save You Money
`
`Best Firefox Addons:
`Boo.ly shopping version
`2.240 - with new search
`engine coupon integration
`
`
`At least by
`June 6, 2013
`
`At least by
`May 2, 2013
`
`At least by
`May 11, 2011
`
`At least by
`November 19,
`2016
`
`At least by
`November 27,
`2015
`
`Coupon
`Mountain LLC
`
`Coupon
`Mountain
`
`§§ 102(a),
`(f), and (g)
`
`CouponFollow
`LLC
`
`Coupon
`Follow
`
`§§ 102(a),
`(f), and (g)
`
`At least by
`May 11, 2011 PriceBlink.com
`
`PriceBlink
`
`§§ 102(a),
`(b), (f), and
`(g)
`
`At least by
`October 1,
`2012
`
`At least by
`October 1,
`2012
`
`October 23,
`2012
`
`At least by
`August 17,
`2011
`
`Boo.ly
`
`Mozilla
`
`Nick Light
`
`Booly
`
`§§ 102(a),
`(b), (f), and
`(g)
`
`
`
`7
`
`Ex. 2008-0007
`
`

`

`IV. THE PRIOR ART ANTICIPATES AND/OR RENDERS OBVIOUS THE
`ASSERTED CLAIMS
`(a)
`
`Background
`
`RetailMeNot provides the following information detailing how each prior-art reference
`
`anticipates or renders obvious a claim of the ’625 Patent under 35 U.S.C. §§ 102 or 103. In
`
`particular, Exhibits A though M of these contentions demonstrate how each prior-art reference
`
`anticipates the claims of the ’625 Patent and/or renders them obvious, either alone or in
`
`combination with one or more other prior-art references and/or the knowledge of a person of
`
`ordinary skill in the art (“POSITA”).
`
`Although RetailMeNot has identified at least one prior-art disclosure of each claim
`
`element of the ’625 Patent, RetailMeNot’s contentions are not necessarily exhaustive. Rather, in
`
`an effort to focus the issues, RetailMeNot cites representative, exemplar portions of the prior art,
`
`even where a reference may contain additional disclosure of a given claim element. To
`
`understand and interpret any specific statement or disclosure within a prior-art reference, a
`
`POSITA would rely on the complete reference, along with other publications and the POSITA’s
`
`general scientific knowledge for context. RetailMeNot may therefore rely upon uncited portions
`
`of the prior-art references, on other publications, and/or on expert testimony to provide context
`
`and to demonstrate how a POSITA would understand and interpret the cited portions of each
`
`prior-art reference or to establish that a POSITA would have been motivated to modify or
`
`combine certain of the cited items to render the claims of the ’625 Patent obvious.
`
`Where RetailMeNot cites to a particular figure in a prior-art reference, the citation should
`
`be understood to encompass the corresponding caption and description of the figure and any text
`
`relating to the figure in addition to the figure itself. Similarly, where a cited portion of text refers
`
`to a figure, the citation should be understood to include the figure as well.
`
`
`
`8
`
`Ex. 2008-0008
`
`

`

`As the prior art cited herein demonstrates, both the alleged problems and the claimed
`
`solutions of the ’625 Patent were well known to POSITAs at the time of the alleged invention.
`
`(b)
`
`Overview of References
`
`The Asserted Claims are invalid under 35 U.S.C. § 102 as anticipated by Johnson (either
`
`expressly or under principles of inherency) or invalid under 35 U.S.C. § 103 as obvious over
`
`Johnson alone, or Johnson in light of Mashadi, Lemphers, Shiffert I, Mezzacca, Brussin, Shiffert
`
`II, Shiffert III, Shiffert IV, Lerat, Leonard, Wu, Coupon Mountain, Coupon Follow, PriceBlink,
`
`and/or Booly. (Exhibits B–M).
`
` The Asserted Claims are also invalid under 35 U.S.C. § 102 as anticipated by Mashadi
`
`(either expressly or under principles of inherency) or invalid under 35 U.S.C. § 103 as obvious
`
`over Mashadi alone, or Mashadi in light of Johnson, Shiffert I, Mezzacca, Brussin, Shiffert II,
`
`Shiffert III, Shiffert IV, Lerat, Leonard, Wu, Coupon Mountain, Coupon Follow, PriceBlink,
`
`and/or Booly. (Exhibits A, C–M).
`
`(c)
`
`Scope and Content of the Prior Art and Well-Known Elements in the Art
`
`The Asserted Claims are invalid at least because it would have been obvious for a
`
`POSITA to combine the teachings of the prior-art references and thereby obtain the alleged
`
`inventions of the ’625 Patent. Such combination is the result of at least one of the following: (1)
`
`the application of known methods to yield predictable results; (2) a simple substitution of one
`
`known element for another to obtain predictable results; (3) the application of known technique
`
`to a known method ready for improvement to yield predictable results; (4) choosing a finite
`
`number of identified, predictable solutions (i.e., obvious to try); or (5) the combination results
`
`from known work prompting a variation of it based on design incentives or other market forces,
`
`and the variations would have been predictable to one of ordinary skill in the art.
`
`9
`
`Ex. 2008-0009
`
`

`

`The prior-art references identified in Exhibits A–M demonstrate that all of the claim
`
`limitations in the Asserted Claims were well-known in the art at the time of the alleged
`
`invention. The common knowledge of elements such as “graphical triggers,” “graphical digital
`
`buttons,” and “visual indicators illustrat[ing] how much progress is being made,” as recited in
`
`claims 1, 4, 9, 11, 14, and 18, is further demonstrated by the following:
`
` Charles Petzold, Programming Windows 95 (Microsoft Press 1996).
`
`
`
`James D. Foley et al., Computer Graphics Principles and Practice (Addison-Wesley
`2d ed. 1996).
`
` Aaron Marcus et al., The Cross-GUI Handbook for Multiplatform User Interface
`Design (Addison-Wesley 1996).
`
` Aaron Marcus, Graphic Design for Electronic Documents and User Interfaces (ACM
`Press 1992).
`
` Open Software Foundation, OSF/Motif Style Guide (Prentice Hall, release 1.2, 1993).
`
` Handbook of Human Factors in Web Design (Robert Proctor and Kim Phuong Vu,
`eds., Lawrence Erlbaum Assocs. 2005).
`
` Brad A. Myers, et al., The Importance of Percent-Done Progress Indicators for
`Computer-Human Interfaces, Proceedings of the 1985 ACM Computer-Human
`Interaction Conference on Human Factors in Computing Sys. 11–17 (1985).
`
` Apple Computer Inc., Macintosh Human Interface Guidelines 209 (1995).
`
` Fiona Nah, A Study on Tolerable Waiting Time: How Long Are Web Users Willing to
`Wait?, 23(3) Behavior & Info. Tech. 285 (2003).
`
` Chris Harrison et al., Rethinking the Progress Bar, Proceedings of the 2007 ACM
`Symposium on User Interface Software & Tech. 115–18 (2007).
`
`The common knowledge of elements such as “Naïve Bayes Classifier algorithm, K
`
`Means Clustering algorithm, Support Vector Machine algorithm, linear regression, logic
`
`regression, and artificial neural networks,” as recited in claims 9 and 17, is further demonstrated
`
`by the following:
`
` Christopher M. Bishop, Pattern Recognition and Machine Learning (Springer 2006).
`
`10
`
`Ex. 2008-0010
`
`

`

` Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice
`Hall 1995).
`
` Sheldon M. Ross, Introduction to Probability Models (Academic Press 8th ed. 2005).
`
`
`
`Iain Pardoe, Applied Regression Modeling (Wiley 2d ed. 2012).
`
` Michael H. Kutner, et al., Applied Linear Regression Models (McGraw-Hill 4th ed.
`2004).
`
`(d) Motivations to Combine
`
`All of the prior art identified in Exhibits A through M relates to the same technical
`
`subject matter. Each reference describes an e-commerce system or solution that interfaces with
`
`merchant webpages during checkout through the use of browser extensions or other code added
`
`to a web browser to maximize consumer savings by identifying optimal coupon codes. Each of
`
`the references solves the same or similar problems that the inventors of the Honey Patent
`
`purportedly solved, though the prior-art systems and solutions solved these problems well before
`
`the Honey Patent. It therefore would have been obvious to a POSITA at the time of the alleged
`
`invention, based on his or her own knowledge, the explicit and implicit teachings of the prior-art
`
`references, and/or the nature of the claimed invention and the problem(s) purportedly being
`
`solved, to look to and/or combine the prior-art references to arrive at the claimed invention,
`
`rendering it obvious. To the extent that any suggestion, motivation, or teaching is required, it is
`
`provided by the identified prior art itself as well as the knowledge of a POSITA.
`
`(1)
`
`Johnson and Mashadi
`
`It would have been obvious to combine Johnson with Mashadi, both of which disclose
`
`software systems that automatically apply coupons and other promotions to save consumers
`
`money in online transactions. See, e.g., Johnson at 4:20–21 (“In certain embodiments, the multi-
`
`merchant electronic shopping cart automatically checks for coupons”), 4:29–32 (“In response to
`
`identifying one or more coupons applicable to the product, the coupon information is displayed
`
`
`
`11
`
`Ex. 2008-0011
`
`

`

`in the user interface. In response to the user purchasing the product, any identified coupons are
`
`applied to the purchase.”); Mashadi ¶ 58 (“[T]he present invention allows for consumer to
`
`manage online purchases and account information. The system allows the consumer to discover,
`
`collect, aggregate, collect, optimize, and automatically apply all kinds of coupons, rewards, gift
`
`cards, loyalty programs, . . . in real time at the point of purchase.”), ¶ 65 (“[T]he optimization
`
`portal module applies a pre-determined algorithm to determine maximum discounts through the
`
`coupon application module. In one embodiment, the coupon application module automatically
`
`applies available coupons in the universal shopping cart.”).
`
`Johnson and Mashadi disclose complementary means of achieving the shared goal of
`
`making the process of checking coupons against the contents of an online shopping cart simpler
`
`and more efficient. See Johnson at 1:38–43 (“The present invention is directed to a system,
`
`method, and computer program for providing a multi-merchant electronic shopping cart . . .
`
`within a web browser for a shopping service.”); Mashadi ¶ 58. For example, Mashadi discloses
`
`detailed algorithms for identifying and calculating the best possible coupon combination, which
`
`would extend Johnson’s enhanced visual shopping cart user interface, APIs, and browser
`
`extension that automatically apply coupons. See, e.g., Mashadi ¶¶ 63, 65, 75, 173; Johnson at
`
`1:38–43, 1:52–65, 2:56–66, 3:10–16, 3:48–52, 6:40–52. A POSITA would have seen the
`
`benefits (e.g., a more efficient shopping experience and better pricing) of combining Johnson’s
`
`multi-merchant shopping cart, with its ability to transact purchases on the customer’s behalf,
`
`with Mashadi’s enhanced portal for viewing and applying optimized shopping plans based on
`
`coupons to provide the maximum discount. See, e.g., Johnson at 1:38–43, 2:1–25, 3:10–41;
`
`Mashadi ¶¶ 169–174 & Figs. 2–6. And this would have required nothing more than the
`
`combination of conventional elements using known methods to yield predictable results.
`
`
`
`12
`
`Ex. 2008-0012
`
`

`

`(2)
`
`Johnson and Shiffert
`
`It would have been obvious to combine Johnson with Shiffert I, Shiffert II, Shiffert III,
`
`and Shiffert IV (collectively, “Shiffert”). Both Johnson and Shiffert disclose software systems
`
`that search for and apply coupons and other promotions to save consumers money online. See,
`
`e.g., Johnson at 4:20–21 (“In certain embodiments, the multi-merchant electronic shopping cart
`
`automatically checks for coupons”), 4:29–32 (“In response to identifying one or more coupons
`
`applicable to the product, the coupon information is displayed in the user interface. In response
`
`to the user purchasing the product, any identified coupons are applied to the purchase.”); Shiffert
`
`I3 at 1:22–24 (“This invention relates generally to merchant offers for goods and service and,
`
`more particularly, to redemption of certain offers such as online coupons.”). Johnson and
`
`Shiffert both teach systems that make the process of finding and using relevant discounts simpler
`
`and more efficient. See, e.g., Johnson at 2:15–25 (“For each product to be purchased, a purchase
`
`transaction is conducted, on behalf of the user, with the merchant . . . . [A] coupon may be
`
`applied in a purchase transaction to a product or to a corresponding merchant.”); Shiffert I at
`
`2:4–10 (“The method further includes inserting . . . a redemption header in a webpage element of
`
`the merchant webpage, the redemption header including the offer identifier associated with the
`
`selected offer and the redemption header being displayed on the merchant webpage.”).
`
`A POSITA would have been motivated to combine Johnson and Shiffert because
`
`Shiffert’s detailed disclosure of dynamic website inspection and modification using server-based
`
`customization would enhance Johnson’s automatic testing of coupon codes by assisting the
`
`Johnson algorithm in identifying relevant pricing information and providing a more user-friendly
`
`interface to elect or inspect coupons. See, e.g., Shiffert I at 21:23–33, 21:45–22:1, 22:9–47,
`
`
`3 Unless otherwise noted, substantially identical disclosures exist in Shiffert II, Shiffert III, and/or Shiffert IV.
`
`
`
`13
`
`Ex. 2008-0013
`
`

`

`22:57–62, 24:60–65, 30:9–18 & Figs. 4D, 4E; Shiffert II (only) at 23:10–22, 25:50–65, 26:64–
`
`27:4, 27:21–24, 27:53–28:27, 28:34–45, 29:50–53, 29:65–30:8 & Figs. 5B, 6B, 7, 9; Johnson at
`
`2:1–10, 2:15–18, 2:23–25, 4:20–43. Moreover, a POSITA would have seen the benefit of using
`
`Johnson’s enhanced visual shopping cart user interface, browser extension, and APIs to extend
`
`Shiffert’s customizable webpage modification techniques. For example, a POSITA would have
`
`appreciated that users find visual interfaces easier to use because, among other reasons, they
`
`present information in an easily understandable and usable manner. Using additional visual
`
`features with Shieffert’s techniques would improve the user experience while offering more
`
`functionality, a result that a POSITA would have sought to achieve. See, e.g., Johnson at 1:38–
`
`43, 1:52–65, 2:56–66, 3:10–16, 3:48–52, 6:40–52; Shiffert I at 17:37–54, 18:43–59, 19:36–56,
`
`21:3–20, 21:23–33, 25:1–8, 25:23–28, 25:40–44 & Figs. 4A–E. A POSITA would thus have
`
`viewed the two references as complementary and would have appreciated that the combination is
`
`nothing more than the combination of conventional elements using known methods to yield
`
`predictable results.
`
`(3)
`
`Johnson and Lemphers
`
`It would have been obvious to combine Johnson with Lemphers, both of which disclose
`
`software systems that automatically apply coupons and other promotions to save consumers
`
`money in online transactions. See, e.g., Johnson at 4:20–21 (“In certain embodiments, the multi-
`
`merchant electronic shopping cart automatically checks for coupons”), 4:29–32 (“In response to
`
`identifying one or more coupons applicable to the product, the coupon information is displayed
`
`in the user interface. In response to the user purchasing the product, any identified coupons are
`
`applied to the purchase.”); Lemphers at 1:6–8 (“This invention relates generally to the field of
`
`online shopping and customer discounts, such as through the use of promotion codes.”), 2:2–4
`
`(“the method can be used to determine whether a promotion code, such as an online coupon, is
`
`
`
`14
`
`Ex. 2008-0014
`
`

`

`valid”), 2:58–59 (“the invention includes a method and apparatus that can automatically validate
`
`one or more promotion codes”).
`
`A POSITA would have been motivated to combine Johnson and Lemphers because
`
`Lemphers’s detailed disclosure of automatic code testing and validation using graph-based
`
`neural networks and machine learning would enhance Johnson’s automatic testing and
`
`application of coupon codes in the online checkout process by assisting the Johnson algorithm in
`
`more rapidly and efficiently identifying relevant coupon codes. See, e.g., Lemphers at 4:30–55,
`
`5:44–61, 6:4–11, 6:21–28, 6:48–63, 8:1–51 & Fig. 5; Johnson at 2:1–10, 2:15–18, 2:23–25,
`
`4:20–43. Moreover, a POSITA would have seen the benefit of using Johnson’s enhanced visual
`
`shopping cart user interface, browser extension, and APIs to extend Lemphers’s mechanism for
`
`searching and inspecting merchant websites to dynamically test and validate coupon codes. For
`
`example, a POSITA would have appreciated that users find visual interfaces easier to use
`
`because, among other reasons, they present information in an easily understandable and usable
`
`manner. Using additional visual features with Johnson’s techniques would improve the user
`
`experience while offering more functionality, a result that a POSITA would have sought to
`
`achieve. See, e.g., Johnson at 1:38–43, 1:52–65, 2:56–66, 3:10–16, 3:48–52, 6:40–52; Lemphers
`
`at 2:58–3:5, 3:11–30, 3:61–4:14, 4:30–35, 5:4–9, 5:22–24, 5:32–34, 5:44–61, 6:4–11, 6:21–28,
`
`6:48–63, 7:24–42, 8:1–51, 8:61–9:4 & Figs 1, 3, 5. A POSITA would thus have viewed the two
`
`references as complementary and would have appreciated that the combination is nothing more
`
`than the combination of conventional elements using known methods to yield predictable results.
`
`(4)
`
`Johnson and Mezzacca
`
`It would have been obvious to combine Johnson and Mezzacca, which both disclose
`
`automated methods and systems for providing and applying the best digital coupon code to a
`
`purchase on a merchant webpage during checkout. See, e.g., Johnson at 4:20–24 (“In certain
`
`
`
`15
`
`Ex. 2008-0015
`
`

`

`embodiments, the multi-merchant electronic shopping cart automatically checks for coupons”),
`
`4:29–45 (“In response to identifying one or more coupons applicable to the product, the coupon
`
`information is displayed in the user interface. In response to the user purchasing the product, any
`
`identified coupons are applied to the purchase.”); Mezzacca at 2:45–57 (“In one aspect, the
`
`present disclosure provides a system and method of in-context automated delivery of relevance-
`
`checked benefit-conveying codes. In particular, the disclosed system and method provides means
`
`to incorporate a benefit-conveying code aggregator system into an e-commerce website on which
`
`a user is making contemporaneous online purchases, such that the aggregator system, via one or
`
`more client software modules, realize a seamless in-context of automated delivery of one or
`
`more benefit-conveying codes of the e-commerce website that are relevance-checked against the
`
`user's current pending order for the e-commerce website.”).
`
`Johnson and Mezzacca also provide complementary means of achieving the shared goal
`
`of maximizing consumer savings at checkout by applying the best coupon code or other reward.
`
`In particular, Mezzacca discloses a user interface for displaying and applying coupon codes to an
`
`electronic shopping cart, and Johnson provides further implementation details as to the manner in
`
`which such coupons are submitted from such a shopping cart. See, e.g., Mezzacca at 18:19–27
`
`(“At block 405, browser extension 321 or browser 311 renders a GUI element—such as a GUI
`
`panel rendered, e.g., near the engaged BC code input field 701, with the GUI panel displaying
`
`acquired BC codes—that is configured to display information about the acquired or finalized BC
`
`codes and let the user select one or more acquired BC codes. FIG. 7D, in illustrating block 405
`
`(as well as block 406), displays three pictorials showing a sequence of exemplary UIs
`
`surrounding block 405.”); Johnson at 4:20–44 (“In certain embodiments, the multi-merchant
`
`electronic shopping cart automatically checks for coupons. For each product displayed in the
`
`
`
`16
`
`Ex. 2008-0016
`
`

`

`user interface, the electronic shopping cart determines if any coupon applies to the product or the
`
`corresponding merchant. For example, the electronic shopping cart may check for any coupons
`
`for a particular store, then check whether any of those coupons are applicable to the product
`
`based on the product's description, validity period of the coupon, and terms of the coupon, etc. In
`
`response to identifying one or more coupons applicable to the product, the coupon information is
`
`displayed in the user interface. In response to the user purchasing the product, any identified
`
`coupons are applied to the purchase. Determining if the coupon applies may include identifying
`
`any potentially applicable coupons and for each potentially applicable coupon, initiating an
`
`online purchase transaction with the applicable merchant to identify any price savings related to
`
`the coupon, where the purchase transaction is terminated before completion of a purchase. In
`
`certain embodiments, determining if a coupon applies includes identifying any potentially
`
`applicable coupons and sending an application programming interface (API) request to the
`
`merchant to determine whether any potentially applicable coupons may be used in the purchase
`
`transaction.”), Figs. 7a–7e. A POSITA would have recognized the combination of Johnson and
`
`Mezzacca as nothing more than the combination of conventional, well-known elements using
`
`known methods to yield predi