DETAILED ACTION
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 .
Status of Claims
This action is in reply to the application filed on 6 January 2025.
Claims 1-9 are currently pending and have been examined.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 6 January 2025 was filed on the mailing date of the initial disclosure. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claims 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent Claims 1, 8 and 9 recite limitations for generating purchase status information and identifying a product or product classification as a factor of change in purchase status. These limitations, as drafted, illustrate a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind. Generating purchase status information and identifying a factor of a change in status illustrate high level observation and evaluation type functions that could be done the same way mentally or manually with a pen and paper. The claims encompass a user simply observing and identifying data in their mind. The mere nominal recitation of a generic computer component such as the processor and memory of an apparatus environment does not take the claim limitations out of the mental processes grouping. Thus, the claims recite a mental process, which is an abstract idea.
This judicial exception is not integrated into a practical application. The claims recite additional elements including the ability to output the change factor information, as well as a processor configured to execute the generating status information and identifying steps. The outputting is recited at a high level of generality and amount to mere data transmission, which is a form of insignificant extra solution activity. The processor executing instructions that perform the generating status information and identifying steps is also recited at a high level of generality and merely automates those steps. Each of the additional components is no more than mere instructions to apply the exception using a generic computer component. The combination of these additional elements is no more than mere instructions to apply the exception in a generic computer environment with generic computer components. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. The claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to step 2A Prong 2, the additional elements in the claims amount to no more than mere instructions to apply the exception using a generic computer component or linking the steps to a generic computer environment. The same analysis applies here in 2B and does not provide an inventive concept.
For the outputting step that was considered extra solution activity in step 2A above, that has been re-evaluated in step 2B and determined to be well-understood, routine and conventional activity in the field. The specification does not provide any indication that the apparatus components are anything other than generic, off the shelf computer components, and the Symantec, TLI and OIP Techs. court decisions in MPEP 2106.05 indicate that the mere collection, receipt or transmission of data over a network is a well-understood, routine and conventional function when it is claimed in a merely generic manner, as it is here.
Dependent claims 2-7 include all of the limitations of claim 1 and therefore recite the same abstract idea. The claims merely narrow the recited abstract idea by describing additional observation and evaluation steps including additional identifying using a model that receives information, describing the model, identifying steps, and describing purchase factor information. The additional elements recited fail to transform the claims into a patent eligible invention but instead describe additional outputting and displaying that do not integrate the abstract idea into a practical application nor do they amount to significantly more.
Accordingly, claims 1-9 are not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-2 and 8-9 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Nagai et al. (US 2022/0284455).
As per Claim 1 Nagai teaches:
A purchase action analysis apparatus comprising:
a memory configured to store instructions; and at least one processor (Nagai in at least Fig. 1 illustrates memory and processing capabilities) configured to execute the instructions to:
generate, using purchase history information including an entity who has purchased a product, a timing at which the product has been purchased, and a purchase amount of the product, purchase status information including information about a total purchase amount that is a total amount of one or more purchase amounts of the entity in each analysis unit period (Nagai in at least [0038-0041, 0048-0049, 0051, 0062, 0064, 0065, 0069-0073] describe using sales history and customer info, sales amount, and time of sale information to analyze the purchase status of a product, e.g. purchase status information including a total purchase amount and timing information) ;
identify, as a change factor, a product or a product classification that is a factor of a change in a purchase status of an entity whose purchase status has changed, using the purchase history information and the purchase status information (Nagai in at least [0037-0041, 0048-0051, 0056, 0065, 0069-0070, 0073] describe determining indicators of change that have impacted the status of a purchase or purchase decision using history and status information analysis, a plurality of products may be associated with an ad, this is because it may contribute to sales for multiple products if multiple products are displayed in one advertisement or if the ad contributes to the brand image or corporate image instead of a single product, the contribution rate of the ad to the product may be stored for each product); and
output change factor information representing the identified change factor (Nagai in at least [0049 and 0069] describes the ability to display changes, conversion rates or other indicators in the indicator displaying area or indicator list area).
As per Claim 2 Nagai further teaches:
identify, as a purchase factor, a product or a product classification estimated to have led to a purchase action of an entity in each of a plurality of sectional periods set in the analysis unit period (Nagai in at least [0037-0041, 0048-0051, 0056, 0065, 0069-0070, 0073] describe determining indicators that have impacted the status of a purchase or purchase decision using history and status information, a plurality of products may be associated with an ad, this is because it may contribute to sales for multiple products if multiple products are displayed in one advertisement or if the ad contributes to the brand image or corporate image instead of a single product, the contribution rate of the ad to the product may be stored for each product); and
output, as purchase factor information, information indicating a purchase factor in each sectional period in the analysis unit period in such a way as to be displayed on a display device (Nagai in at least [0049 and 0069] describes the ability to display changes, conversion rates or other indicators in the indicator displaying area or indicator list area).
As per Claims 8-9 the limitations are substantially similar to those set forth in Claim 1 and are therefore rejected based on the same reasons and rationale set forth in the rejection of Claim 1 above.
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, 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 3-4 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Nagai et al. (US 2022/0284455) in view of Shan et al. (US 2003/0033190).
As per Claim 3 Nagai further teaches:
identify the change factor by analyzing the purchase history information and the purchase status information to output information about the change factor (Nagai in at least [0037-0041, 0048-0051, 0056, 0065, 0069-0070, 0073] describe determining indicators of change that have impacted the status of a purchase or purchase decision using history and status information, a plurality of products may be associated with an ad, this is because it may contribute to sales for multiple products if multiple products are displayed in one advertisement or if the ad contributes to the brand image or corporate image instead of a single product, the contribution rate of the ad to the product may be stored for each product) ,
Nagai does not explicitly recite using a change factor identification model generated by learning about status changes. However, Shan teaches an online shopping conversion simulation module. Shan further teaches:
identify the change factor using a change factor identification model that receives at least the purchase history information and the purchase status information to output information about the change factor, and the change factor identification model is generated by learning purchase history information about a plurality of entities whose purchase status indicates a noted change and purchase history information about a plurality of entities whose purchase status indicates a change other than the noted change (Shan in at least [0005, 0014-0018, 0024, 0038] describes modeling shopping behavior using preferences, history, demographics and other purchase information, to determining underlying patterns in customer behavior as part of the conversion process including a conversion status, the model relates customer profile information and product promotion effects to determine conversion probabilities and examines visitor status to customer status conversions as well as shopper to purchaser conversions).
Therefore, it would be obvious to one of ordinary skill in the art to modify the ability to identify a product or product classification as a change factor to include techniques for using a model to identify change factors or other features because each of the elements are known, but not necessarily combined as claimed. The technical ability existed to combine the elements as claimed and the result of the combination is predictable because each of the elements perform the same function as they did individually. By determining factors/features relevant to conversions, or change, the combination enables an accurate model for forecasting shopper behavior where a prediction a shopper being converted into an actual purchaser can be based on specific promotions, factors or interactions.
As per Claim 4 Nagai in at least [0039] describes attributes related to purchasers being used as part of the analysis and determinations taught. Nagai does not explicitly recite but Shan further teaches:
identify, using attribute information of an entity who has purchased a product or a product in a product classification to be analyzed, a feature of a person who has purchased the product or the product in the product classification to be analyzed, and the at least one processor is further configured to execute the instructions to output, in response to an information request for requesting purchaser feature information indicating a feature of a person who has purchased the product, the purchaser feature information about a purchaser who has purchased the product or the product in the product classification to be analyzed (Shan in at least [0002, 0007, 0017-0019, 0021, 0023-0024, 0026, 0039, 0041, 0065] describe using customer profile information to identify features or attributes of customer via a customer class of multi attribute vector of characteristics and outputting that information).
Shan is combined based on the reasons and rationale set forth in the rejection of Claim 4 above.
As per Claim 7 Nagai in at least [0039] describes attributes related to purchasers being used as part of the analysis and determinations taught. Nagai does not explicitly recite but Shan further teaches:
identify, using attribute information about an entity who has purchased a product or a product in a product classification to be analyzed, a feature of a person who has purchased the product or the product in the product classification to be analyzed, and the at least one processor is further configured to execute the instructions to: output purchaser feature information in response to an information request for requesting information indicating a feature of a person who has purchased a product that is a purchase factor displayed on the display device (Shan in at least [0002, 0007, 0017-0019, 0021, 0023-0024, 0026, 0039, 0041, 0065] describe using customer profile information to identify features or attributes of customer via a customer class of multi attribute vector of characteristics and outputting that information).
Shan is combined based on the reasons and rationale set forth in the rejection of Claim 4 above.
Claims 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over Nagai et al. (US 2022/0284455) in view of Konishi (US 2022/0044287).
As per Claim 5 Nagai in at least [0037-0041, 0048-0051, 0056, 0065, 0069-0070, 0073] describe determining indicators that have impacted the status of a purchase or purchase decision using history and status information, a plurality of products may be associated with an ad, this is because it may contribute to sales for multiple products if multiple products are displayed in one advertisement or if the ad contributes to the brand image or corporate image instead of a single product, the contribution rate of the ad to the product may be stored for each product and in at least [0049 and 0069] describes the ability to display changes, conversion rates or other indicators in the indicator displaying area or indicator list area.
Nagai does not explicitly recite a time series pattern. However, Konishi teaches a sales support apparatus and destination list creation apparatus that pertains to assisting efficient sales activities. Konishi further teaches:
wherein the purchase factor information includes information for display, on a display device, a purchase factor time series pattern in which purchase factors in respective sectional periods in the analysis unit period are disposed in time series (Konishi in at least [0014, 0091-0095, 0100-0101, 0135, 0138-0140] and Figs. 6-12 describes information including displayable information such product sales patterns based on transaction data including time, see also [0035-0039, 0046-0047, 0076-0077, 0079-0086).
Therefore, it would be obvious to one of ordinary skill in the art to modify the ability to utilize purchase factor information in displayable analyses to include factors such as time series patterns and adjacent or similar factors in a pattern because each of the elements are known, but not necessarily combined as claimed. The technical ability existed to combine the elements as claimed and the result of the combination is predictable because each of the elements perform the same function as they did individually. By utilizing time series patterns and identifying similarities in factors of a patterns, the combination enables more accurate identification of particular customers based on features thereby supporting efficient sales activities (Konishi [0011-0012]).
As per Claim 6 Nagai in at least [0037-0041, 0048-0051, 0056, 0065, 0069-0070, 0073] describe determining indicators that have impacted the status of a purchase or purchase decision using history and status information, a plurality of products may be associated with an ad, this is because it may contribute to sales for multiple products if multiple products are displayed in one advertisement or if the ad contributes to the brand image or corporate image instead of a single product, the contribution rate of the ad to the product may be stored for each product and in at least [0049 and 0069] describes the ability to display changes, conversion rates or other indicators in the indicator displaying area or indicator list area.
Nagai does not explicitly recite adjacent, e.g. similar purchase factors in a pattern. However, Konishi teaches a sales support apparatus and destination list creation apparatus that pertains to assisting efficient sales activities. Konishi further teaches:
wherein the purchase factor information includes information indicating the number of entities having the same combination of adjacent purchase factors in the purchase factor time series pattern (Konishi in at least [0014, 0091-0095, 0100-0101, 0135, 0138-0140] and Figs. 6-12 describes information including displayable information such product sales patterns where similar or related customers or attribute information are identified see also [0035-0039, 0046-0047, 0076-0077, 0079-0086).
Konishi is combined based on the same reasons and rationale set forth in the rejection of Claim 5 above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Shayeb (US 12417476) Methods for Group Purchase of Access to Information
Krishnamurthy (US 20190102793) Generating Media Content Using Connected Vehicle Data
Eder (US 20090018891) Market Value Matrix for flexibly integrating organization related data, information, knowledge and systems into a market value matrix.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to STEPHANIE Z DELICH whose telephone number is (571)270-1288. The examiner can normally be reached on Monday - Friday 7-3:30.
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/STEPHANIE Z DELICH/Primary Examiner, Art Unit 3623