Ex Parte Hahn et al

Patent Trial and Appeal Board

Jan 27, 2015

11973053 (P.T.A.B. Jan. 27, 2015)

UNITED STATES PATENT AND TRADEMARK OFFICE
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BEFORE THE PATENT TRIAL AND APPEAL BOARD
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Ex parte JUNE IRENE HAHN and MICHAEL JOHN NORTH
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Appeal 2012-007564
Application 11/973,053
Technology Center 3600
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Before: MURRIEL E. CRAWFORD, ANTON W. FETTING, and
NINA L. MEDLOCK, Administrative Patent Judges.

CRAWFORD, Administrative Patent Judge.

DECISION ON APPEAL

STATEMENT OF THE CASE
Appellants seek our review under 35 U.S.C. § 134 of the Examiner’s
final rejection of claims 1–13. We have jurisdiction under 35 U.S.C. § 6(b).
We REVERSE.

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STATEMENT OF THE CASE
Appellants’ invention is directed generally to computer models to
simulate a consumer packaged goods market. (Spec. 1, ll. 8–9).
Claim 1 is illustrative:
1. A method of predicting product purchase volume by
consumer agents in an agent-based computer model, as an
indicium of consumer’s purchase behavior, comprising the
steps of:
(A) defining, in the agent-based computer model, consumer
agents; manufacturer agents; and retailer agents, wherein:
(a) the consumer agents comprise purchasing products
during shopper trips at the retailer agents, and
wherein each consumer agent independently
comprises:
(i) a generateable in-store product consideration
set;
wherein the in-store product consideration set
is generateable for each shopping trip
the consumer agent takes to the retailer
agent;
wherein the in-store product consideration set
optionally comprises one or more
products, wherein each product, if
present, comprises a probability that
the consumer agent selects the product
for purchase for the shopping trip;
(ii) an out-of-store product attribute consideration
set, wherein each product attribute, if
present, of the product attribute
consideration set, has a probability of
influencing the consumer agent's in-store
product consideration set;
(b) the manufacturer agents comprise at least a first
manufacturer agent and a second manufacturer
agent, wherein the first and second
manufacturer agents comprise:
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(i) manufacturing at least a first product and
second product, respectively;
(ii) distributing the first product and the second
product, respectively, to the retailer agents;
(c) the retailer agents comprise at least a first retailer
agent and a second retailer agent, wherein the
first and second retailer agents comprise:
(i) selling to consumer agents at least a first
product or second product distributed by
said manufacturer agents;
(B) defining, in the agent-based computer model, a
consumer agent purchasing decision filter;
(C) including, in the agent-based computer model, an out-
of-store influencer, or an in-store influencer, or a combination
thereof;
wherein the out-of-store influencer is capable of influencing
the out-of-store product attribute consideration set, and the in-
store influencer is capable of influencing the in-store product
consideration set;
(D) generating each consumer agent’s in-store product
consideration set for each shopping trip by the consumer agent
by applying the consumer agent purchasing decision filter to
compare the consumer agent’s out-of-store product attribute
consideration set with the products available in the retailer
agent wherein the consumer agent is shopping;
(E) running the agent based model on a computer over a
simulated defined time period to obtain the volume of products
purchased by the consumer agents from the retailer agents.

The following rejections are before us on appeal.
Claims 1–9, 11, and 12 are rejected under 35 U.S.C. § 103(a) as
unpatentable over Herz (US 2001/0014868 A1, pub. Aug. 16, 2001) and
Van Der Riet (US 2003/0126146 A1, pub. July 3, 2003).

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Claim 10 is rejected under 35 U.S.C. § 103(a) as unpatentable over
Herz, Van Der Riet, and Wrigley (US 2003/0063779 A1, pub. Apr. 3, 2003).
Claim 13 is rejected under 35 U.S.C. § 103(a) as unpatentable over
Herz, Van Der Riet, and Wagner (US 2004/0199545 A1, pub. Oct. 7, 2004).

ANALYSIS
We are persuaded by the Appellants’ argument that Herz and Van Der
Riet, alone or in combination, fail to disclose “generating each consumer
agent’s in-store product consideration set for each shopping trip by the
consumer agent by applying the consumer agent purchasing decision filter to
compare the consumer agent’s out-of-store product attribute consideration
set with the products available in the retailer agent wherein the consumer
agent is shopping,” because Herz, paragraphs 53–57, instead merely groups
shopper profiles according to similarity. (App. Br. 4).
The claim terminology at issue is that of an “in-store product
consideration set,” which is generated by using a “purchasing decision filter”
to compare the “out-of-store product attribute consideration set” with “the
products available in the retailer agent.”
In support of the rejection for this limitation, the Examiner cites to
Herz paragraphs 27, 53–57, 143, and 240–42. (Ans. 7, 16–17). The
Examiner appears to indicate that promotional product offers, in Herz
paragraphs 27 and 241, correspond to the “in-store product consideration
set” of claim 1, because finding the in-store product consideration set in
Herz, the Examiner states “paragraph 0053-0057, regarding offer profiles
including product attributes; paragraph 0240-0241, regarding selecting
offers of products to maximize vendor profit.” (Id. at 7).
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However, confusingly, the Examiner also finds that “product
selection” in paragraph 39 of Herz discloses “the in-store product
consideration set.” (Ans. 6). In this cited paragraph, Herz discloses
updating a customer profile with information about customer product
preferences, based on both “active feedback” from the customer about the
product, and “passive feedback” about the product. (Herz para. 39). Active
feedback is an explicit indication from the customer about interest in the
product, and passive feedback is based on monitoring a customer’s on-line
viewing behavior. (Id.).
The Examiner thus equates both product interest/selection in a
customer profile, and generated promotional product offers, to the “the in-
store product consideration set.”
In claim 1, the recited comparing is done by a “consumer agent
purchasing decision filter.” The Examiner finds this filter at paragraph 143
of Herz. (Ans. 6, 16). There, Herz discloses that “collaborative filtering” is
used by “adjusting the associating weights” of products to favor less
frequently purchased items. (Herz paras. 143–46).
Claim 1 recites that the filter is applied to compare available products
with an “out-of-store product attribute consideration set.” According to
claim 1, the “out-of-store product attribute consideration set” is made of a
set of product attributes, where each product attribute “has a probability of
influencing the consumer agent’s in-store product consideration set.” The
Examiner indicates the “out-of-store product attribute consideration set”
corresponds to “sway products” in paragraph 298 of Herz. (Ans. 6).
Paragraph 298 of Herz discloses using historical data, to time promotional
product offers to be presented just prior to a historically repeating purchase
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time, at which point the consumer may be more open to being swayed to
consider purchasing a rival product instead of the one normally purchased.
(Herz para. 298). The Examiner, thus, implies that offers for rival products
are attributes that influence the “in-store product consideration set,” which
resulting set is either the same promotional product offers that are the
attributes that influence, or are product interests of a consumer.
When addressing the “generating” limitation, in the Response to
Arguments section of the Answer, the Examiner states:
Herz teaches collection of consumer profiles and tracking of
shopper behavior, including product attributes of purchased
products (paragraph[s] 0053-0057). The shopping can occur in
any of number of venues or retail establishments to form an in
store and out of store product consideration set based on the
retailer (paragraph 0027). What web pages were used to
purchase the items are also tracked (paragraph 0242). The
system of Herz compares this information and present product
offers that maximize profit (paragraph[s] 00240-0241). Herz
further teaches making recommendations regarding a product
using collaborative filtering. (paragraph 0143).
(Ans. 17).
Mapping this onto the claim language, one of two scenarios emerges
from the Examiner’s statements. In the first scenario, the “in-store product
consideration set” is the updated profiles with active and passive product
interest preferences of Herz paragraph 39. (Ans. 6). In this scenario,
customer product interest preferences are not generated by applying a filter
to “out-of-store product attribute consideration set” (offers for rival
products) and a set of available products, as claimed, because they instead
are determined through active customer feedback and monitoring on-line
viewing. (Herz para. 39).
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In the second scenario, the “in-store product consideration set” is
promotional product offers. These, therefore, must be determined by
applying the filter of increasing the weight of less-purchased products, to a
set of available products and timing an offer for a rival product, by a
comparison that takes place at paragraphs 240–41. However, the Examiner
does not show where Herz applies “sway products,” or offers for rival
products, in paragraph 298, with the claimed “available” products, filtered
by popularity to arrive at offers, because paragraphs 240–41 disclose instead
both “group[ing] shoppers together to predict how likely each shopper is to
purchase a given offer,” and varying offers by clusters of shoppers to
improve profit. Clustering shoppers and varying offers by customer clusters
does not generate offers by applying a filter to “compare the consumer
agent’s out-of-store product attribute consideration set with the products
available in the retailer agent.”
In both scenarios, the Examiner’s reasoning does not hold up to relate
consistent and meaning portions of Herz to the claim elements in the
limitation of “generating each consumer agent’s in-store product
consideration set for each shopping trip by the consumer agent by applying
the consumer agent purchasing decision filter to compare the consumer
agent’s out-of-store product attribute consideration set with the products
available . . . .” For this reason, the Examiner has failed to establish a prima
facie case of obviousness of claim 1. Therefore, we will not sustain the
rejection of claim 1 under 35 U.S.C. § 103(a). We also will not sustain the
rejections of claims 2–13 that depend from claim 1.

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DECISION
We reverse the rejections of claims 1–13 under 35 U.S.C. § 103(a).

REVERSED

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