Ex Parte Vincent

Board of Patent Appeals and Interferences

Jun 19, 2007

09750948 (B.P.A.I. Jun. 19, 2007)

The opinion in support of the decision being entered today
is not binding precedent of the Board.

UNITED STATES PATENT AND TRADEMARK OFFICE
__________

BEFORE THE BOARD OF PATENT APPEALS
AND INTERFERENCES
__________

Ex parte PERRY G. VINCENT
__________

Appeal 2007-0271
Application 09/750,948
Technology Center 3600
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Decided: June 19, 2007
__________

Before ERIC GRIMES, LORA M. GREEN, and NANCY J. LINCK,
Administrative Patent Judges.

LINCK, Administrative Patent Judge.

DECISION ON APPEAL
Appellant appeals the Examiner’s 35 U.S.C. § 102(b) rejection of
claims 1, 4-6, and 9 and her 35 U.S.C. § 103(a) rejection of claims 7, 8, and
10-20. We have jurisdiction to decide this appeal under 35 U.S.C. § 6(b).
We affirm.
Appeal 2007-0271
Application 09/750,948

STATEMENT OF THE CASE
Appellant’s invention “relates to a customer relationship management
system and, more particularly, to the use of a rules engine to determine
patterns in a customer’s multi-channel interactions with a business and to
suggest interaction strategies for a current interaction based upon observed
patterns.” (Specification (“Spec.”) 1.) The claimed subject matter is
reflected in representative claims 1 and 11, reproduced below (with the
disputed limitations highlighted):1
1. A method of suggesting an interaction strategy to a
customer service representative in a customer relationship
management environment, said method comprising the steps
of:
maintaining an interaction repository containing
customer data;
utilizing one or more data analysis tools comprising
executable instructions to analyze said customer data to
determine one or more patterns and generate a set of rules
based upon said patterns; and
using a recommendation engine to apply said rules to a
current customer interaction to recognize one or more of said
patterns in said interaction and suggest an interaction strategy
corresponding to said recognized patterns.

11. A system for recommending a strategy for
managing a customer interaction, said system comprising:
a plurality of interaction channels for capturing
customer data;

1 Appellant argues two claim limitations with respect to all of the claims.
Thus we respond to these arguments and determine the patentability of all
the appealed claims with reference to claims 1 and 11.

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one or more data analysis tools comprising executable
instructions for analyzing said customer data from said
plurality of channels and determining one or more patterns
from said data; and
a recommendation engine for analyzing a current
customer interaction and recognizing one or more of said
patterns in said interaction, said recommendation engine
recommending strategies corresponding to said recognized
patterns.
The Examiner’s 35 U.S.C. § 102(b) rejection of claims 1, 4-6, and 9 is
based on a publication entitled “Net Perceptions Alters Dynamics of
Marketing Industry with Introduction of Net Perceptions for Call Centers,”
PR Newswire 9487 (Oct. 12, 1998) (hereafter “Net Perceptions”). The 35
U.S.C. § 103(a) rejection of claims 7, 8, and 10-20 is based on Net
Perceptions and Andrews, Whit, “A Hidden Agenda,” Internet World 43, 44
(October 1, 1999) (hereafter “Andrews”).

ISSUES ON APPEAL
With respect to the § 102(b) rejection, Appellant contends:
It is not seen . . . that the Net Perceptions Publication teaches
"one or more data analysis tools comprising executable
instructions to analyze said customer data to determine one
or more patterns and generate a set of rules based upon said
patterns" as part of the Net Perceptions call center solution.
(Br. 5.)
The Examiner responds:
“Net Perceptions . . . " specifically states that Net Perceptions
"continuously builds customer profiles as each call
progresses and uses the information to prompt agents with
purchase recommendations that are unique to each customer"
(¶ 2). This means that the Net Perceptions software
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evaluates, or analyzes, each customer profile in order to
generate customized recommendations. The Net Perceptions
software must be programmed to correlate specific customer
profile data with a particular set of recommendations if the
recommendations are to be customized for each customer. As
a matter of fact, Net Perceptions' "recommendation engine
zeroes in on individual preferences by pooling information
from current and previous calls, and by drawing upon a
database of information on other customers with similar
buying patterns" (¶ 4), thereby indicating that patterns of
successful sales are gleaned from the patterns of "other
customers with similar buying patterns." Clearly, Net
Perceptions analyzes customer data to determine one or more
patterns. Then, the sales agent may be prompted to enter
additional customer information and/or be provided with
personalized recommendations for each customer. These
instructions and/or output generated by Net Perceptions are
not only based on rules, but may also be interpreted as rules
generated by Net Perceptions and presented to the sales
agent.
(Answer 8-9.2)
Based on these conflicting positions, the § 102(b) issue before us is,
does Net Perceptions disclose "one or more data analysis tools comprising
executable instructions to analyze said customer data to determine one or
more patterns and generate a set of rules based upon said patterns," as
required by claim 1?
With respect to the § 103(a) issue, Appellant contends:
Neither the Net Perceptions Publication or Andrews, taken
singularly or in combination, teaches "one or more data
analysis tools comprising executable instructions for
analyzing said customer data from said plurality of channels

2 The paragraph numbers correspond to handwritten numbers on the
documents in the record.
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and determining one or more patterns from said data,” an
element of each one of claims 11 through 15.
(Br. 6.)
In her response to Appellant’s argument, the Examiner relies
upon the same reasoning quoted above but further elaborates on her
response to address the additional claim language “from said
plurality of channels” as follows:
Andrews teaches that Net Perceptions does offer a
recommendation engine that collects and analyzes data
regarding customer interactions among various channels,
including telephonic (i.e., physical) and online/Web (i.e., a
virtual and self-service application) interactions (¶¶ 1,4).
This capability allows merchants to more comprehensively
and successfully personalize product offerings made to
customers, especially those that interact with the merchants
through various channels (¶¶ 1, 4). As a matter of fact, the
SkyMall implementation of Net Perceptions'
recommendation engine, as disclosed by Andrews, is
embodied in a call center environment (similar to Net
Perceptions' packaged product, Net Perceptions for Call
Centers); therefore, . . . it would have been obvious to one of
ordinary skill in the art at the time of Applicant's invention to
adapt the product Net Perceptions for Call Centers to capture
customer data from a plurality of different interaction data
sources, including both physical and virtual channels (such
as a self-service application), in order to reap the full
capabilities of Net Perceptions' recommendation engine in
the call center environment, thereby allowing merchants to
more comprehensively and successfully personalize product
offerings made to customers, especially those that interact
with the merchants through various channels (as suggested in
¶¶ 1,4 of Andrews).
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(Answer 10.3 See also Answer 8-9 (quoted in relation to the
§ 102(b) issue).)
The § 103(a) issue before us is, when considered together do Net
Perceptions and Andrews disclose "one or more data analysis tools
comprising executable instructions for analyzing said customer data from
said plurality of channels and determining one or more patterns from said
data,” as required by claim 11?

FINDINGS OF FACT4
1. Net Perceptions discloses “maintaining an interaction repository
containing customer data.” (See Net Perceptions, ¶¶ 2-4 (“builds customer
profiles,” including “customer purchase histories, preferences and tastes . . .
by pooling information from current and previous calls, and by drawing
upon a database of information on other customers”).)
2. Net Perceptions discloses “utilizing one or more data analysis tools
comprising executable instructions to analyze said customer data to
determine one or more patterns.” (See Net Perceptions, ¶¶ 2-4 (“system’s
recommendation engine zeroes in on individual preferences by pooling
information from current customers and previous calls, and by drawing upon
a database of information on other customers with similar buying
patterns”).)

3 See supra note 2.
4 Findings of Fact are abbreviated “FF.”
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3. Net Perceptions discloses “generat[ing] a set of rules based upon
said patterns” in that such rules would be required for the recommendation
engine to “prompt[] agents with pertinent customer information and specific
purchase recommendations for whoever is on the line”. (Id. See also
Answer 9.)
4. One of ordinary skill in the art would equate “a rules engine”
(Spec. 1), with a “recommendation engine” (claim 11). (See also Net
Perceptions, ¶ 4; Andrew passim.)
5. Finally, Net Perceptions discloses “using a recommendation engine
to apply said rules to a current customer interaction to recognize one or more
of said patterns in said interaction and suggest an interaction strategy
corresponding to said recognized patterns.” (See Net Perceptions, ¶¶ 2-4
(“system’s recommendation engine zeroes in on individual preferences by
pooling information from current customers and previous calls, and by
drawing upon a database of information on other customers with similar
buying patterns” and “prompts agents with pertinent customer information
and specific purchase recommendations” based on the identified patterns).)
6. Andrews further describes Net Perceptions’ recommendation
engines and their versatility and identifies Net Perceptions as one company
offering recommendation engines. (See Andrews passim.)
7. Andrews discloses, or at least suggests, using “executable
instructions for analyzing customer data from [a] plurality of channels.”
(Andrews, ¶ 1 (“recommendation engines,” such as that of Net Perceptions,
“can use multiple channels”). See also Andrews, ¶ 4 (“Net Perceptions’
recommendation engine . . . provide[s] advice to consumers . . . through
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multiple channels”); ¶ 11 (Companies, such as Net Perceptions, have used
“multichannel strategy” to “match[] data collected in one place to the
originating customer in another.”).)
8. The availability and use of multiple channels in the Net
Perceptions system, as described in Andrews, combined with Net
Perceptions’ use of collected data to analyze buying patterns, would have
motivated the skilled artisan to collect such data using multiple channels
with a reasonable likelihood of success. (See FFs 5, 6; Answer 10 (quoted
above).)

DISCUSSION
With respect to the rejection of claim 1 under § 102(b), Appellant
disputes a single limitation, i.e., the step of “utilizing one or more data
analysis tools comprising executable instructions to analyze said customer
data to determine one or more patterns and generate a set of rules based
upon said patterns.” (Br. 5, 6.) We find this limitation is fully disclosed in
Net Perceptions. See FF 2, 3. While the express terms “data analysis tools,”
“executable instructions,” and “set of rules” do not appear in Net
Perceptions, they are necessarily and inherently present, as would have been
recognized by the skilled artisan.
Under “35 U.S.C. § 102, every limitation of a claim must identically
appear in a single prior art reference for it to anticipate the claim,” Gechter
v. Davidson, 116 F.3d 1454, 1457, 43 USPQ2d 1030, 1032 (Fed. Cir. 1997).
Nevertheless, a limitation can be satisfied through inherency. See, e.g., In re
Ludke, 441 F.2d 660, 663, 169 USPQ 563, 566 (CCPA 1971) (affirming a
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§ 102 rejection based on parachute’s “inherent operating characteristics”),
cited with approval in In re King, 801 F.2d 1324, 1327, 231 USPQ 136, 138
(Fed. Cir. 1986). Clearly, “data analysis tools” and “executable
instructions” would have been necessary to analyze the customer
information in Net Perceptions’ recommendation engine and a “set of rules”
would have been necessary to then provide agents with “pertinent customer
information and specific purchase recommendations” for a specific
customer. Appellant has not provided any evidence sufficient to “prove that
the subject matter shown to be in the prior art does not possess the
characteristic relied on.” In re Swinehart, 439 F.2d 210, 212, 169 USPQ
226, 229 (CCPA 1971), cited with approval in King, 801 F.2d at 1327, 231
USPQ at 138. Thus, we affirm the Examiner’s § 102(b) rejection of claim 1.
With respect to claim 11, rejected under § 103(a), Appellant again
argues a single limitation is not met, i.e., "one or more data analysis tools
comprising executable instructions for analyzing said customer data from
said plurality of channels and determining one or more patterns from said
data.” (Br. 6.)
We have discussed this limitation with respect to the § 102(b)
rejection, except for the “from said plurality of channels” language. We find
this additional language would have been expressly taught, or at least
suggested, by the combination of Net Perceptions and Andrews. (See FFs 5,
6.) One of ordinary skill in the art would have been motivated to use the
disclosed multiple channels, as described in Andrews, to collect data to
analyze buying patterns, as described in both Net Perceptions and Andrews,
and would have had a reasonable likelihood of success. (See FFs 5, 6, 7.)
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See KSR Int’l v. Teleflex Inc., 127 S. Ct. 1727, 1742, 82 USPQ2d 1385, 1397
(“person of ordinary skill is also a person of ordinary creativity, not an
automaton”). Thus, the invention of claim 11 would have been obvious to
one of ordinary skill in the art at the time Appellant’s invention was made.
We affirm the Examiner’s rejection of claim 11 under § 103(a).
Appellant did not separately argue the patentability of the remaining
claims on appeal. Thus, we also affirm their rejection pursuant to 37 C.F.R.
§ 41.37(c)(1)(vii).

CONCLUSION
We affirm the § 102(b) rejection of claims 1, 4-6, and 9 and the
§ 103(a) rejection of claims 7, 8, and 10-20.
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) (2006).
AFFIRMED

smsc

JAMES M. STOVER
NCR CORPORATION
1700 SOUTH PATTERSON BLVD, WHQ4
DAYTON, OH 45479
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