DETAILED ACTION
Status of the Application
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 09/14/2026 has been entered.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status
This action is a Non-Final Action on the merits in response to the application filed on 09/14/2026.
Claims 5 and 6 have been amended.
Claims 5 and 6 remain pending in this application.
Foreign Priority
The Examiner/office acknowledges that the applicant claims foreign priority to the date 03/02/2020.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 5 and 6 are directed towards a process of which are among the statutory categories of invention.
Claims 5 and 6 are rejected under 35 U.S.C. 101 because the claims are directed to a judicial exception without significantly more.
Step 1: This part of the eligibility analysis evaluates whether the claim falls within any statutory category. See MPEP 2106.03. The claim recites at least one step or act, including calculating an equation. Thus, the claim is to a process, which is one of the statutory categories of invention. (Step 1: YES).
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim.
With respect to claims 5, 6 the independent claim (claim 5 ) are directed to managing customer data accounts, In independent claim 5, the bolded limitations emphasized below correspond to the abstract ideas of the claimed invention:
Claim 5, A process for forming a customer plan for a sales representative, the process comprising:
retrieving the stored and processed data from at least one economy database and the CRM database;
calculating a recency, frequency, monetary and sensitivity (RFM-S) score;
preparing a visit plan for the sales representative based on the RFM-S score so as to prioritize visits to customers based on purchasing frequency and sales potential; and
using the visit plan by the sales representative to visit customers in accordance with the RFM-S score.
these steps fall within and recite an abstract ideas because they are directed to a method of organizing human activity which includes commercial interaction; managing personal behavior (See MPEP 2106.04(a)(2), subsection II).
If a claim limitation, under its broadest reasonable interpretation, covers commercial interaction; managing personal behavior, then it falls within the “method of organizing human activity” grouping of abstract ideas. Therefore, If the identified limitation(s) falls within any of the groupings of abstract ideas enumerated in the MPEP 2106, the analysis should proceed to Prong Two. (Step 2A, Prong One: YES).
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d). The claim recites the additional elements of database. The claims recite the steps are performed by the database.
The limitations of
initiating a flow of data from at least one economy database and a customer relationship management (CRM) database, the at least one economy database allowing a retrieval of data pertaining to a U.S. dollar rate of exchange and a mortgage loan rate of exchange, the CRM database storing and processing data for each customer of a plurality of customers of the sales representative;
displaying the RFM-S score to the sales representative;
are mere data gathering and output recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g) (“whether the limitation is significant”). In addition, all uses of the recited judicial exceptions require such data gathering and output, and, as such, these limitations do not impose any meaningful limits on the claim. These limitations amount to necessary data gathering and outputting. See MPEP 2106.05.
Further, the limitations are recited as being performed by database. The database are recited at a high level of generality. In limitation (a), database is used as a tool to perform the generic computer function of receiving data. See MPEP 2106.05(f). The database is used to perform an abstract idea, as discussed above in Step 2A, Prong One, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f).
Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).
Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05. As explained with respect to Step 2A, Prong Two, the additional elements are the database. The additional elements were found to be insignificant extra-solution activity in Step 2A, Prong Two, because they were determined to be insignificant limitations as necessary data gathering and outputting.
However, a conclusion that an additional element is insignificant extra solution activity in Step 2A, Prong Two should be re-evaluated in Step 2B. See MPEP 2106.05, subsection I.A. At Step 2B, the evaluation of the insignificant extra-solution activity consideration takes into account whether or not the extra-solution activity is well understood, routine, and conventional in the field. See MPEP 2106.05(g). As discussed in Step 2A, Prong Two above, the recitations of
initiating a flow of data from at least one economy database and a customer relationship management (CRM) database, the at least one economy database allowing a retrieval of data pertaining to a U.S. dollar rate of exchange and a mortgage loan rate of exchange, the CRM database storing and processing data for each customer of a plurality of customers of the sales representative;
displaying the RFM-S score to the sales representative;
are recited at a high level of generality. These elements amount to transmitting data and are well understood, routine, conventional activity. See MPEP 2106.05(d), subsection II. 10 As discussed in Step 2A, Prong Two above, the recitation of a database to perform limitations amounts to no more than mere instructions to apply the exception using a generic computer component. Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept. (Step 2B: NO).
Dependent claim 6 does not contain any new additional elements. Rather, these claims offer further descriptive limitations of elements found in the independent claims. In this case, the claims are rejected for the same reasons at step 2a, prong one; step 2a, prong 2; and step 2b. Thus, the claim is not patent eligible.
Regarding the dependent claim 6 recites limitations that are not technological in nature and merely limits the abstract idea to a particular environment. Claim 6 recites database which are considered an insignificant extra-solution activities of collecting and analyzing data; see MPEP 2106.05(g). Claim 6 recites database, which merely recites an instruction to apply the abstract idea using a generic computer component; MPEP 2106.05(f). Additionally, claim 6 recites steps that further narrow the abstract idea. No additional elements are disclosed in the dependent claims that were not considered in independent claim 6. Therefore claim 6 does not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over United States Patent Publication US 20150046223, Sewak to hereinafter Sewak in view of United States Patent Publication US 20180096371, Lederman, et al. to hereinafter Lederman in view of United States Patent Publication US 20110119071, Phillips, et al.
Referring to Claim 5, Sewak teaches A process for forming a customer plan for a sales representative, the process comprising:
initiating a flow of data from at least one economy database and a customer relationship management (CRM) database (
Sewak teaches a distributed data-processing environment having a computing device, a contact-transaction database, historic data, and a network. Specifically, Sewak teaches that “[d]istributed data processing environment 100 includes computing device 110, contact transaction 120, and historic data 130, interconnected via network 150,” see paragraphs [0022–0023].
Sewak teaches that its contact-transaction repository is “a database containing data for a set of contacts that have made a transaction,” and that the transaction data includes “customer ID, timestamp of each transaction, the monetary amount of each transaction, and a calculated number of transactions per unit of time specified,” see paragraph [0024].
Sewak further teaches a second database, historic data 130, which “includes data associated with contacts that were included in previous campaign activities or solicitations,” including contact-identifying information, contact response activity or transaction information, transaction or response value, and campaign-intent or objective information, see paragraph [0030].
Accordingly, Sewak teaches a networked flow of stored customer/contact data between data sources and a scoring program, where the data sources store and process data associated with multiple customer contacts.),
the CRM database storing and processing data for each customer of a plurality of customers of the sales representative (
Contact transactions 120 is a database containing data for a set of contacts that have made a transaction.” See paragraphs [0024]. “Transaction data within contact transactions 120 includes, but is not necessarily limited to, customer ID, timestamp of each transaction, the monetary amount of each transaction, and a calculated number of transactions per unit of time specified.” See paragraphs [0024, 0032–0033].);
retrieving the stored and processed data from at least one economy database and the CRM database (
Sewak teaches retrieving contact data from its database. Sewak teaches that contact data “may reside in one or more locations and is sent to trend adjusted RFM program 300 in response to requests, or accessed by trend adjusted RFM program 300 from each of one or more data storage locations,” see paragraph [0046].
Sewak further teaches that its trend-adjusted RFM program sends a “request for contact data for a six month time period” to the contact-transactions database, and that the contact-transactions database responds by transmitting transaction information “for all contacts” during the requested interval to the scoring program “via network 150,” see paragraph [0046].
Thus, Sewak teaches retrieving stored data for a plurality of customers/contacts from one or more data-storage locations through a network.);
calculating a recency, frequency, monetary and sensitivity (RFM-S) score (
Sewak expressly teaches calculating an RFM score. Sewak teaches that “[a] computer determines an RFM score for each of a plurality of contacts,” in which “each RFM score” comprises “a recency score, a frequency score and a monetary score,” see paragraph [0005].
Sewak defines recency as “a measure of how recently a contact responded to a solicitation, such as making a purchase,” frequency as “the total number of responses a contact has made within a designated time period,” such as distinct purchases during the last six months, and monetary value as “the total value of purchases made or donations made within a designated time period,” see paragraph [0003].
Sewak further teaches sorting contact data by transaction timestamp, number of transactions, and monetary value to assign contacts to recency, frequency, and monetary-value bins, see paragraphs [0026–0029].
Sewak also teaches that, after contacts are assigned to recency, frequency, and monetary-value bins, its program “applies weighting and determines an RFM score for each contact,” and that the three corresponding bin values “combine to form an RFM score of the contact,” see paragraph [0054].);
displaying the RFM-S score to the sales representative (
Sewak states that scores are used “to more effectively choose contacts for promotion or retention campaigns, or determine actions and strategies that more effectively apply to groups of contacts.” See paragraphs [0061].
Sewak teaches a computing architecture having a display for presentation of data to a user. Sewak teaches that its input/output interfaces connect to “a display 420,” and that “[d]isplay 420 provides a mechanism to display data to a user and may be, for example, a computer monitor,” see paragraphs [0068–0069].);
preparing a visit plan for the sales representative based on the RFM-S score so as to prioritize visits to customers based on purchasing frequency and sales potential (
Sewak expressly teaches customer prioritization based on transaction frequency and likelihood of sales/campaign response. Sewak teaches sorting customer contacts by recency, frequency, and monetary value, and states that “the highest amount of responses in a defined time period is the best frequency value,” see paragraph [0033].
Sewak further teaches that higher-score customer groups have greater commercial-response potential: “This method produces 125 bins with RFM scores ranging from 111 to 555, in which the higher the score, the higher the probability of a contact responding to solicitation,” see paragraph [0038].
Sewak teaches that the tRFM output can be used to “choose contacts for promotion or retention campaigns” and to “determine actions and strategies” applicable to customer groups, see paragraph [0061].
Accordingly, Sewak teaches prioritizing multiple customers based upon purchasing frequency and predicted likelihood of responsive purchasing behavior, i.e., sales potential.); and
Sewak does not explicitly teach using the visit plan by the sales representative to visit customers in accordance with the RFM-S score.
However, Lederman teaches using the visit plan by the sales representative to visit customers in accordance with the RFM-S score (See Sewak) (
Lederman teaches that customer-event response models may be used for seller planning. Lederman teaches that its transaction-data-based customer grouping system permits “sellers” to use customer groupings “to help plan promotions, plan inventory, and optimize placement of items or signage within a store,” see paragraph [0005].
Lederman further teaches that the segmentation module estimates purchase likelihood and determines groups of customers responding to similar sets of events, see paragraph [0033].
Thus, Lederman teaches using modeled customer purchasing response and customer segments to support planned commercial actions, in which the Examiner is interpreting as us a visit plan by a sales rep. to visit a customer.).
Sewak and Lederman are both directed to the analysis of customer data (See Sewak at 0010-0012; Lederman at 0003-0006, 0018-0027). Sewak discloses additional elements such as formula calculations can be considered (See Sewak at 0043, 0060). It would have been obvious for one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Sewak, which teaches detecting and calculating customer data with the RFM scoring problems in view of Lederman, to efficiently apply analysis of customer data to enhancing the capability to include the planning of customer’s events. (See Lederman at 0005, 0066).
Sewak in view of Lederman does not explicitly teach the at least one economy database allowing a retrieval of data pertaining to a U.S. dollar rate of exchange and a mortgage loan rate of exchange.
However, Phillips teaches these limitations the at least one economy database allowing a retrieval of data pertaining to a U.S. dollar rate of exchange and a mortgage loan rate of exchange (
Phillips: Sec. 0025, Price sensitivity scorer 104 calculates a price sensitivity score for prospect 100 using data associated with prospect 100. The data associated with the prospect is obtained from provider 102 and/or from third party database 108 via network 106. It is not necessary to have prospect data from both sources in order to calculate a price sensitivity score… As an example of prospect data from third party database 108, third party database 108 may be a credit bureau (such as TransUnion, Equifax or Experian) and the prospect data may include information about credit history, previous or current accounts, past due information, etc. Some examples of data are described in further detail below.
Phillips: Sec. 0026, Price sensitivity scorer 104 calculates a price sensitivity score for prospect 100 and returns it to provider 102, for example by entering data associated with the prospect into a scoring function which outputs a score. In some embodiments, provider 102 uses the price sensitivity score to calculate or adjust a price for prospect 100. For example, a less price sensitive prospect may be offered a (slightly) higher price or a price at the higher end of a range of prices being considered for that prospect. In some embodiments, a price calculated based on a price sensitivity score is a rate, such as an interest rate for a mortgage, loan, credit card, line of credit, etc. In some embodiments, a price calculated based on a price sensitivity score is in units of some currency (e.g., in US dollars, Canadian dollars, British pounds, etc.). In some embodiments, provider 102 uses one or more other pieces of additional information in calculating a price. For example, provider 102 may use both a price sensitivity score and a credit score (e.g., a FICO score) in calculating a price. In one example, a nominal or initial price is first calculated using a credit score and the price sensitivity score is used to adjust the nominal/initial price (e.g., adjust it by [0,Δ] or [−Δ/2,Δ/2])
Phillips: Sec. 0037, Updating a training data set and regenerating a scoring function may permit the scores to respond to changes in market and/or economic conditions (which may cause people to become more or less price sensitive). In general, it is not necessary to recalculate a new scoring function for each prospect.
Phillips: Sec. 0051, the set of non-scoreable variables has four categories: pricing data, product/provider data, market data and macroeconomic data. Pricing data includes the price at which a transaction was approved (by the provider, for final approval by the prospect), competitor and market benchmark prices (specifically in this example: APR, competitor APR and prime rate). Product/provider data includes type (e.g., whether the transaction is associated with an auto loan, an unsecured loan, a home equity loan, etc.), an amount (e.g., in US dollars, Canadian dollars, etc.), a term or length (e.g., 60 months, 24 months, 30 years, etc.) and a rate type (e.g., whether the rate is variable or fixed or some combination thereof (e.g., a 5-year ARM). Market data may include (but is not limited to) channel (e.g., how the prospect came to or contacted the provider, for example by way of a dealer/broker, Internet/website, branch, telephone, etc.) and HHI. HHI (Herfindahl-Hirschman Index) is a measure of market concentration (e.g., how much or to what degree a market is monopolized); other measures of market concentration may be used. Macroeconomic data may include but is not limited to macroeconomic indicators describing the state of the market at the time of the transaction. In training data set 400, macroeconomic data includes unemployment (e.g., at the time the transaction occurred and/or at any level including local or state level such as unemployment rates in the state or metropolitan area in which the transaction occurred or the prospect resides) and credit or liquidity risk premium.),
Phillips describes severs and databases the stores and process customer information pertaining to customers, economics, USD, and mortgage information
The type of database constitutes nonfunctional descriptive material and should not be given further patentable weight. The type of database, without positive functional recitation as to its distinctive use, amounts to mere labeling of data and does not functionally alter the method of managing customer data. See MPEP 2106.01 [R-5]. Nonfunctional descriptive material cannot lend patentability to an invention that would otherwise have been anticipated by the prior art. When descriptive material is not functionally related to the substrate, the descriptive material will not distinguish the invention from the prior art in terms of patentability (see In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 404 (Fed. Cir. 1983); In re Lowry, 32 F.3d 1579, 32 USPQ2d 1031 (Fed. Cir. 1994)). Thus, this further purported limitation of claim 4-6 fails to further limit the invention as claimed.
Sewak, Lederman, Phillips and are all directed to the analysis of customer data (See Sewak at 0010-0012; Lederman at 0003-0006, 0018-0027; Phillips at 0027, 0052). Sewak discloses additional elements such as formula calculations can be considered (See Sewak at 0043, 0060). It would have been obvious for one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Sewak view of Lederman, which teaches detecting and calculating customer data with the RFM scoring problems in view of Phillips, to efficiently apply analysis of customer data to improving the processing of various customer’s information to calculate value scores. (See Phillips at 0031, 0034, 0036, 0043, 0044).
Referring to Claim 6, Sewak teaches the RFM-S scoring process according to claim 5 wherein the equation is defined as (Recency Score * 1000) + (Sensitivity Score * 100) + (Frequency Score * 10) + (Monetary Score) (
Sewak: Sec. 0029, 0038, 0041, 0043, 0054, 0059, 0060
Anyone skilled in the art will see the interpretation of the arithmetic; can be mathematically applied to this form of simple calculations. Mathematically using an equation or a formula to performing a marketing model is known to those skilled in the art. Additionally, the Examiner wants to point out that the neither Claim 5 or 6 actually discloses what a recency score, frequency score, monetary score and sensitivity score actually, that further support broadest reasonable interpretation on anything that discloses calculation, because the Applicant does not have anything in the claims that teaches what a recency score, frequency score, monetary score and sensitivity score is.)
Response to Arguments
Applicant’s arguments filed 09/14/2026 have been fully considered but they are not persuasive. Applicant’s arguments will be addressed hereinbelow in the order in which they appear in the response filed 09/14/2026.
Regarding the 35 U.S.C. 101 rejection, at pg. 4 -6 Applicant argues with respect to claims at issue are not directed to an abstract idea
In response to the 35 USC § 101 claim rejection argument, the Examiner respectfully disagrees. The Examiner did consider each claim and every limitation both individually and as a whole, since the grounds of rejection clearly indicates that an abstract idea has been identified from elements recited in the claims. Using the two-part analysis, the Office has determined there are no elements, in the claim sufficient enough to ensure that the claims amounts to significantly more than the abstract idea itself. As recited, the claims are directed towards:
A process for forming a customer plan for a sales representative, the process comprising:
initiating a flow of data from at least one economy database and a customer relationship management (CRM) database, the at least one economy database allowing a retrieval of data pertaining to a U.S. dollar rate of exchange and a mortgage loan rate of exchange, the CRM database storing and processing data for each customer of a plurality of customers of the sales representative;
retrieving the stored and processed data from at least one economy database and the CRM database;
calculating a recency, frequency, monetary and sensitivity (RFM-S) score;
displaying the RFM-S score to the sales representative;
preparing a visit plan for the sales representative based on the RFM-S score so as to prioritize visits to customers based on purchasing frequency and sales potential; and
using the visit plan by the sales representative to visit customers in accordance with the RFM-S score.
The claim(s) does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the computer as recited is a generic computer component that performs functions.
Examiner finds the claim recite concepts which are now described in the 2019 PEG as certain methods of organizing human activity. In particular the claims recites limitations for managing customer data, which constitutes methods related to include commercial interaction such as marketing or sales activities; managing personal behavior such as social activities and following rules or instructions which are still considered an abstract idea under the 2019 PEG. The database is comprised of generic computer elements to perform an existing business process. Examiner finds the claims recite mere instructions to implement the abstract idea on a computer and uses the computer as a tool to perform the abstract idea without reciting any improvements to a technology, technological process or computer-related technology. Additionally, the following arguments at pg. 5, is the Applicant admitting that the claims are directed towards human activities as the sale representative is to perform these steps.
(at pg.5 “his visit plan is then used by the sales representative to visit customers in accordance with the RFM-S score. Applicant respectfully contends that this language is no longer an "abstract idea" but rather a process for forming a plan which allows the sales representative to optimize the amount of travel required for visiting customers in order to improve returns on the sales representative's travels.”)
Then at pg. 6 the Applicant admission that the application is directed to improving the user’s experience and not the computer itself:
(at pg.6 “creates a visit plan in accordance with the language of independent claim 5. This visit plan improves the efficiency of customer visits in the manner”;
“With the method of the invention, it is possible to follow the visit plan of the customers, which are more value in terms of purchase frequency and sales potential, and thus, the most ideal plan in terms of customer relations is provided and an efficient journey planning is realized. [Emphasis supplied]
As such, it is clear that the present invention is not a mere grouping of human behavior or a method of organizing human behavior, but a method of planning which improves consumer satisfaction and increases sales efficiency.”)
Additionally, the Examiner would like to point the Applicant to the 2019 PEG, in which integrating macroeconomic data into customer scoring will fall under. The 2019 PEG which states:
Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)
Regarding the 35 U.S.C. 103 rejection, Applicant’s arguments with respect to claims has been considered but are moot in view of the new grounds of rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Gilbert., W.O. Pub. WO2008064343, (discussing the modeling of customer interest on e-commerce products).
Saboo et al., Using Big Data To Model Time-Varying Effects For Marketing Resource (Re) Allocation, https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=02767783&AN=119473690&h=Q%2BoRbzOCkTaeFrs4iHNgYuHu%2B8J4%2BfdXBsD1zLFweS9ZZ22xBf51j9ssjYjgl2T9MSEx0F3b0xyermPRtNQsbw%3D%3D&crl=c, MIS quarterly, 2016 (discussing the processing of customer data).
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/UCHE BYRD/Examiner, Art Unit 3624
