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 .
Acknowledgments
Claim 1-20 are pending
Applicant provided information disclosure statement.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more than the judicial exception itself.
Regarding Step 1 of subject matter eligibility for whether the claims fall within a statutory category (See MPEP 2106.03), claims 1-20 are directed to non-transitory computer-readable medium, system, and method.
Regarding step 2A-1, Claims 1-20 recite a Judicial Exception. Exemplary independent claim 1 and similarly claims 8 and 15 recite the limitations of
…categorize items into a category based on substitutability; calculate an elasticity of demand for each item and for the category as a whole; receive percent pricing changes for each item with a pricing change in the category; calculate a mean percent pricing change for the category, wherein the calculated mean percent pricing change excludes an item; calculate an elasticity of demand for the category, wherein the calculated elasticity of demand excludes the item; calculate a direct effect factor and a cross-effect factor for the item based on a quantified impact of a price change of the item on a sales forecast; calculate a change in forecast units for the item; determine whether the change in the forecast units needs to be calculated for other items in the category; and generate a new product assortment based, at least in part, on the calculated change in the forecast units of the item based on a pricing change of the item.
These limitations, as drafted, are a process that, under its broadest reasonable interpretation cover concepts of categorizing, receiving, calculating, determining, and generating data. The claim limitations fall under the abstract idea grouping of mental process, because the limitations can be performed in the human mind, or by a human using a pen and paper. For example, but for the language of processor and memory, the claim language encompasses simply categorizing items, calculating an elasticity for demand for items and a category, receiving price data, calculating a mean percent pricing change, direct effect and cross effect factors, and change in forecast units for an item. The claims also recite determining whether further calculating needs to be done and generating a new product assortment. Determining a product assortment and calculating an elasticity for demand is not novel and has been done before the technological age. The claims are mere data manipulation steps that do not require a computer. Given a real world example, these steps can be done by a store manager in charge of product management.
The claims recite elasticity of demand and determining change in forecasted units. These steps correspond to sales and demand of items with respect to a business such as a retailer (See para 0003 of Applicant’s Specifications). Elasticity also deals with customer behavior when purchasing items. These make the claims fall in the abstract idea grouping of certain methods of organizing human activity (sales activity, fundamental economic principles or practices; business relations, interactions between people, managing personal behavior). It is clear the limitations recite these abstract idea groupings, but for the recitations of generic computer components. The mere nominal recitations of generic computer components does not take the limitations out of the mental process and certain methods of organizing human activity grouping. The claims are focused on the combination of these abstract idea processes.
Regarding step 2A-2- This judicial exception is not integrated into a practical application, and the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The claim recites the additional elements of system, computer, processor, memory, non-transitory computer-readable medium, and software.
These components are recited at a high level of generality, and merely automate the steps. Each of the additional limitations 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 using a generic computer components or software. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Further, the claims do not provide for recite any improvements to the functioning of a computer, or to any other technology or technical field; applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition; applying the judicial exception with, or by use of, a particular machine; effecting a transformation or reduction of a particular article to a different state or thing; or applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
The dependent claims have the same deficiencies as their parent claims as being directed towards an abstract idea, as the dependent claims merely narrow the scope of their parent claims. For example, the dependent claims further describe what the categorized items comprise of such as substitutable items, classes, and subclasses. The dependent claims further recite details about the pricing such as pricing changes being in accordance with one or more of business rules, business constraints, and demands.
Regarding step 2B the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because claim 1 recites
System, computer, processor, memory
Claim 8 recites method, however method is not considered an additional element.
Claim 8 further recites processor, memory, computer
Claim 15 recites non-transitory computer-readable medium, software, computer, processor, memory
When looking at these additional elements individually, the additional elements are purely functional and generic the Applicant specification states general purpose computer configurations as seen in para 0022-0024.
When looking at the additional elements in combination, the Applicant’s specification merely states a general purpose computer configurations as seen in para 0022-0024. The computer components add nothing that is not already present when the steps are considered separately. See MPEP 2106.05
Looking at these limitations as an ordered combination and individually adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use generic computer components, recitations of generic computer structure to perform generic computer functions that are used to "apply" the recited abstract idea. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amounts to significantly more than the abstract idea itself.
Since there are no limitations in these claims that transform the exception into a patent eligible application such that these claims amount to significantly more than the exception itself, claims 1-20 are rejected under 35 U.S.C. 101.
Claim Rejections - 35 USC § 103
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 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.
Claim(s) 1, 2, 8, 9, 15, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yuan (US20150161635A1) in further view of Cereghini (US20070282668A1).
Regarding claim 1, 8, and 15, Yuan teaches
A system…comprising: a computer, comprising a processor and a memory, the computer configured to…(See figure 1) This shows a system. (See para 0078-Example embodiments may be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of them. Example embodiments may be implemented using a computer program product (e.g., a computer program tangibly embodied in an information carrier, e.g., in a machine-readable medium for execution by, or to control the operation of, data processing apparatus, e.g., a programmable processor 1002, a computer, or multiple computers).) This shows a computer with processor and memory.
A computer-implemented method …by a computer comprising a processor and a memory (See para 0014-The description that follows includes illustrative systems, methods, techniques, instruction sequences, and computing machine program products that embody illustrative embodiments) This teaches a method.
A non-transitory computer-readable medium embodied with software…the software when executed is configured to…by a computer comprising a processor and a memory…(See para 0071-Certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code embodied (1) on a non-transitory machine-readable medium) (See para 0078-Example embodiments may be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of them. Example embodiments may be implemented using a computer program product (e.g., a computer program tangibly embodied in an information carrier, e.g., in a machine-readable medium for execution by, or to control the operation of, data processing apparatus, e.g., a programmable processor 1002, a computer, or multiple computers).) This teaches a processor and memory.
for demand planning The art of Yuan also deals with demand planning since the system determines demand curves and price elasticity curves (See para 0016- This dynamic price elasticity information can be used in a number of ways in the online marketplace, including monitoring market demand and inventory health in near real-time, helping sellers to price a listing accurately, and ranking items for search results.) (See figure 6A, 6B, 7A, 7B).
Yuan further teaches categorize items into a category based on substitutability (See para 0015-In an example embodiment, items are grouped into inferred pseudo products. An inferred pseudo product is a group of items that are similar according to some established criteria. An inferred pseudo product may comprise one or two main types of goods, and a mix of substitute and complementary items.) This shows the system categorizes items in pseudo groups based on their similarities and if they are substitutes.
calculate an elasticity of demand for each item and for the category as a whole (See figure 5) This shows that price elasticity is calculated for each pseudo grouping (i.e. category of items). The fact that the system determines a price elasticity for the group means that price elasticity is also determined for each item, since the items make up the grouping. For example, the unstructured merchandise in fig. 5 is the data for each item.
Even though Yuan teaches price elasticity for the items, it doesn’t teach percent pricing changes for items, however Cereghini teaches
receive percent pricing changes for each item (See fig. 8) This shows the system receives a displays to a user 1% price changes for an item and the effects of it with respect to profit. This can be done for each product. (See para 0007-0022- Results of a products' price elasticity, plus all cross-sell and cannibalization effects resulting from changes in the products' price are illustrated in the chart shown in FIG. 8. )
Yuan and Cereghini are analogous art because they are from the same problem solving area of price management and both belong to G06Q30 classification. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Yuan’s invention by incorporating the method of Cereghini because Yuan would also be able to see percent prices changes with items such as in historical sales data that are used to determine the price elasticity as seen in the Yuan. This would make the system of Yuan more sophisticated since it would give more detailed item information to the user who is using the system.
Yuan further teaches with a pricing change in the category (See fig. 6A, 6B, 7A, and 7B) This shows pricing change on the x-axis with respect to the pseudo group (i.e. category).
Yuan further teaches calculate a…pricing change for the category, wherein the calculated… pricing change excludes an item; (See para 0052- FIG. 3 is a graph illustrating an example of data sampled from a particular listing category, specifically a category covering various collectible and historical advertisement artifacts of a well-known oil and gas company, in accordance with an example embodiment. For the observed demand 300 in the category, strong demand is seen at the lower end of price 302 up to about $20 (at reference 304), sales then sharply decrease around $20 (at reference 306), and ultimately level off on the long tail after $200 (at reference 308). The price elasticity of demand at each price point can be computed based on fitted function of the sample points. ) (See para 0054- It is also observed that the demand curve and, hence, price elasticity changes from time to time when online inventory changes. Price elasticity can be updated by frequently sampling the sale history. This allows price elasticity to be measured and utilized in real-time.) This shows that a demand price elasticity is calculated for the category which includes price changes for the category as seen from figure 7a and 7b. The calculation can exclude some items initially such as in the sales history data since the price elasticity is updated frequently as new sales history data comes in.
However, Yuan doesn’t teach mean percent, However Cereghini teaches mean percent (See para 0180- Avg Discount %) This teaches a mean percent such as average discount percent.
Yuan and Cereghini are analogous art because they are from the same problem solving area of price management and both belong to G06Q30 classification. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Yuan’s invention by incorporating the method of Cereghini because Yuan would also be able to calculate mean percent price changes for the category since it already teaches pricing changes for the category. This would make the system of Yuan more sophisticated since it would give more detailed item information to the user who is using the system.
Yuan further teaches calculate an elasticity of demand for the category, wherein the calculated elasticity of demand excludes the item (See para 0054- It is also observed that the demand curve and, hence, price elasticity changes from time to time when online inventory changes. Price elasticity can be updated by frequently sampling the sale history. This allows price elasticity to be measured and utilized in real-time.) This shows that a demand price elasticity is calculated for the category which includes price changes for the category as seen from figure 7a and 7b. The calculation can exclude some items initially such as in the sales history data since the price elasticity is updated frequently as new sales history data comes in.
Even though Yuan teaches price elasticity for a category, it doesn’t teach cross and direct effects for the items in the category, however Cereghini teaches calculate a direct effect factor and a cross-effect factor for the item based on a quantified impact of a price change of the item on a sales forecast (See para 0145- Cross Selling analysis is based on the integration of Price Elasticity analysis results, in particular campaign price suggested, and affinity analysis. Cross Sell analysis is based on an Affinity model. For every product couple combination (Product A-Product B) this function returns the following coefficients) This teaches determining cross-effect factors for an item such as product B, This is based on price changes with respect to price elasticity results, an example of price elasticity results with price changes is seen in fig. 5 and 6. The system also calculates direct effect factors such as profit, revenue, and volume as seen in fig. 5 with respect to the price changing in figure 5. The price changes also correspond to a sales forecast since the system looks as profit, revenue, and volume with respect to the price change as seen in figure 5.
Yuan and Cereghini are analogous art because they are from the same problem solving area of price management and both belong to G06Q30 classification. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Yuan’s invention by incorporating the method of Cereghini because Yuan would also be able to calculate direct effect factors and cross effect factors for the items. This would allow the system of Yuan to make changes to the analysis of the pseudo groups since items with these effects make up the groups. This makes the system of Yuan more sophisticated since it is looking deeper into the individual item data.
Cereghini further teaches calculate a change in forecast units for the item (See para 0073- What If Scenario (WIS) Module 315—This module provides a mechanism to compare the planned sell quantities and prices that were calculated outside the system, with the prices and quantities that were calculated by the Price Optimization application) (See para 0163- The “What-If Analysis” presents a user with a table, shown in FIG. 29, that lists available products, planned prices and quantities (imported into the system), calculated optimal prices and quantities (results from the IS module), and then two added columns, one for “What if” Price, and “What If” Volume. In the “What If” Price column the users is able to type a new price, and the system will automatically populate the “What If” Volume. A combo box provides means for users to select products in the screen)(See para 0165- Only products having calculated elasticity are available for the What-If analysis. “What if” results are not a forecast of product demand, rather, they are a calculation of expected quantity change applied to products, ) This teaches a calculating a change in quantity with respect to price.
determine whether the change in the forecast units needs to be calculated for other items in the category The user using the system of Cereghini can determine other items that need this analysis by selecting which items to analyze. For example, a user can choose in fig. 28 which items to further analyze and which items not too.
Yuan and Cereghini are analogous art because they are from the same problem solving area of price management and both belong to G06Q30 classification. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Yuan’s invention by incorporating the method of Cereghini because Yuan would also be able to determine changes in forecasted units. This would help the system of Yuan determine future changes in price elasticities for groups based and better help the user determine optimal prices for the listing.
In addition, Even though Cereghini teaches at least in part, the calculated change in the forecast units of the item based on a pricing change of the item when the system determines changes in quantity with respect to prices changes as seen in fig. 28, Cereghini doesn’t teach generating a new product assortment, however in another section of Cereghini it teaches
and generate a new product assortment based (See fig. 10) This shows a user is able to generate a new product assortment by selecting which products to include in item 1009. A user can include and exclude whichever product they choose in the different product classes.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the user choosing a new product assortment in figure 10 of Cereghini with the change in forecasted quantities as seen in fig. 28 and 29 of Cereghini because it would let the user dynamically change which products to offer based on changes. For example, a change in quantity of a certain item may be bad for sales and profit compared to another item, so the user may choose not to include that item in the assortment. This helps the user easily make changes for the health of their business.
Yuan and Cereghini are analogous art because they are from the same problem solving area of price management and both belong to G06Q30 classification. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Yuan’s invention by incorporating the method of Cereghini because Yuan would also be able to determine changes in forecasted units and make a new product assortment. This would help the system of Yuan determine future changes in price elasticities for groups based and better help the user determine optimal prices for the listing in order to make a new product assortment.
Regarding claims 2, 9, and 16, Yuan and Cereghini teach the limitations of claims 1, 8, and 15, however Yuan further teaches
wherein the categorized items comprise substitutable items. (See para 0015- An inferred pseudo product is a group of items that are similar according to some established criteria. An inferred pseudo product may comprise one or two main types of goods, and a mix of substitute and complementary items.) This shows the category of pseudo groups have substitutable items.
Claim(s) 3, 4, 5, 6, 7, 10, 11, 12, 13, 14, 17, 18, 19, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yuan (US20150161635A1) in further view of Cereghini (US20070282668A1) in further view of Delurgio (US20020165760A1).
Regarding claims 3, 10, and 17 Yuan and Cereghini teach the limitations of claims 1, 8, and 15, however they do not teach constraints, however Delurgio teaches
wherein the category has one or more associated constraints. (See para 0052- FIG. 35 is a diagram depicting contents of a rules/constraints menu within the currently defined scenarios window of FIG. 34.) This teaches rules/constraints.
Yuan and Delurgio are analogous art because they are from the same problem solving area of price management and both belong to G06Q30 classification. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Yuan’s invention by incorporating the method of Delurgio because the pseudo groups defined in Yuan could also have constraints such as product constraints within the group. This would make the system of Yuan more sophisticated because it would be able to look at certain constraints of the group when determining the optimal price for the listing. The optimal price would be more tailored to the actual product than just similar products because of the product constraints.
Regarding claims 4, 11, and 18 Yuan and Cereghini teach the limitations of claims 1, 8, and 15, however they do not teach
wherein the category is associated with a hierarchy of one or more classes and one or more subclasses.
However, Delurgio teaches wherein the category is associated with a hierarchy of one or more classes and one or more subclasses. (See figure 10) This teaches item class such as soap and item subclasses such as bar and liquid soap.
Yuan and Delurgio are analogous art because they are from the same problem solving area of price management and both belong to G06Q30 classification. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Yuan’s invention by incorporating the method of Delurgio because the pseudo groups defined in Yuan could also have classes and subclasses within the group. This would make the system of Yuan more sophisticated because it would be able to look at certain classes and subclasses of the group when determining the optimal price for the listing. The optimal price would be more tailored to the actual product than just similar products. The classes and subclasses would categorize the items more finely.
Regarding claims 5, 12, and 19 Yuan, Cereghini, and Delurgio teach the limitations of claims 4, 11, and 18, however Delurgio further teaches
wherein the one or more classes and the one or more sub- classes of the hierarchy comprise groupings of items that are sorted according to their substitutability with other items. (See fig. 10 and 11) This shows the class of soap are sorted with subclass of liquid and bar soap which are substitutable items. The subclasses of bar soap and liquid soap are sorted with a list as seen in item 1111 in figure 11. The bar soaps have different varieties that are substitutable with each other. For example, Irish spring bar soap is substitutable with dove bar soap.
Yuan and Delurgio are analogous art because they are from the same problem solving area of price management and both belong to G06Q30 classification. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Yuan’s invention by incorporating the method of Delurgio because the pseudo groups defined in Yuan could also have classes and subclasses within the group. This would make the system of Yuan more sophisticated because it would be able to look at certain classes and subclasses of the group when determining the optimal price for the listing. The optimal price would be more tailored to the actual product than just similar products. The classes and subclasses would categorize the items more finely.
Regarding claims 6, 13, and 20, Yuan and Cereghini teach the limitations of claims 1, 8, and 15, however they do not teach
wherein the pricing change is in accordance with one or more of: business rules, business constraints and demands.
However Delurgio teaches optimizing price and takes in account business constraints, wherein the pricing change is in accordance with one or more of: business rules, business constraints and demands. (See para 0051- FIG. 34 is a diagram featuring a rules summary window for an optimization scenario that is highlighted within a currently defined scenarios window.) This teaches business rules with respect to the price optimizing scenario.
Yuan and Delurgio are analogous art because they are from the same problem solving area of price management and both belong to G06Q30 classification. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Yuan’s invention by incorporating the method of Delurgio because Yuan can also incorporate business rules when determining a price. These business rules can be unique to each group of items to make sure the price that is determined is optimal for the user to use. This adds another layer of analysis of Yuan making it more sophisticated.
Regarding claims 7 and 14, Yuan, Cereghini, and Delurgio teach the limitations of claims 6 and 13, however Delurgio further teaches
wherein the one or more business rules, business constraints and demands are based, at least in part, on location. The business rule can also be with respect to location. Figure 12 shoes the business rule for the scenario of only selecting certain store locations when determining the optimal price.
Yuan and Delurgio are analogous art because they are from the same problem solving area of price management and both belong to G06Q30 classification. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Yuan’s invention by incorporating the method of Delurgio because Yuan can also incorporate business rules when determining a price. These business rules can be unique to each group of items to make sure the price that is determined is optimal for the user to use. This adds another layer of analysis of Yuan making it more sophisticated.
Conclusion
The prior art made of record and not relied upon considered pertinent to Applicant’s disclosure.
Sills (US20180089707A1) Discloses systems and computer-readable media for generating dynamic pricing rules to govern offered price-volume break points.
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/MUSTAFA IQBAL/Primary Examiner, Art Unit 3625
