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
Due to communications filed 3/31/26, the following is a final office action. Claims 1, 5-8, 12-15, 19-20 are amended. Claims 2, 9, 16 are cancelled. Claims 1, 3-8, 10-15 and 17-20 are pending in this application and are rejected as follows.
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, 3-8, 10-15 and 17-20 are rejected under 35 U.S.C, 101 because the claimed invention is directed to a judicial exception (l.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
As per independent claims 1, 8 and 15, these claims as a whole is recite a judicial exception. These claims recite methods, computing systems and a non-transitory machine-readable storage medium comprising receiving groups of storage units, identifying rate rules associated with the group, receiving operational metrics, evaluating the operational metrics against the rate rules, automatically generating updated prices for storage units based on the satisfied rules, and transmitting the updated prices to a remote computing device. These limitations recite the abstract idea of managing pricing using rules and operational metrics, which falls into the “Certain Methods of Organizing Human Activity” and “Mental Processes” groupings. Thus, the claim recites an abstract idea.
Furthermore, these claims are not integrated into a practical application because the additional elements, including the one or more processors, remote computing device, and network are generic computer components performing generic computer functions of receiving, processing, generating, and transmitting data. The claim does not recite an improvement to computer technology or any other technical field.
Finally, these claims do not recite an inventive concept, and does not include significantly more than the abstract idea because the additional elements are well-understood, routine and conventional activities implemented on generic computer components. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. The claim is ineligible.
Dependent claims 3-7, 10-14 and 17-20 are also directed to same grouping of “Certain Methods of Organizing Human Activity” and “Mental Processes”. The additional elements of the method in claims 3-7; storage unit in claim 7; computing system in claims 10-14; storage units in claim 14; non-transitory machine-readable storage medium of claims 17-20; storage units in claim 20, are additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use. Accordingly, 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.
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, 3, 7-8, 10, 14-15, 17, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lieberman et al (US 20210103872 A1).
As per claim 1, Lieberman et al (US 20210103872 A1) discloses:
Receiving, by one or more processors, a group of different types of storage units, wherein the different types of storage units are grouped together based on one or more group rules, ([0024] amenities associated with each storage unit within a pricing group. Amenities may include...door type, physical condition, and the like. For example, a storage unit that requires navigating one turn from a main hallway may be more desirable than another storage unit in the same pricing group that requires navigating three turns from the main hallway [0031] The method 100 begins at step 102, where each storage unit, in a storage unit inventory for all storage units existing at the storage facility, is assigned to a pricing group. In one embodiment, a self-storage facility device assigns each storage unit within the self-storage facility to a pricing group based on the physical dimensions and other common attributes of the storage units. For example, all storage units that have a length of 5 feet, a height of 10 feet and a width of 10 feet and that are not climate controlled, may be assigned to the same pricing group; [0032] Rules can be created to associate units with these criteria and then the criteria used to automatically generate the desirability rank for each of the units);
identifying, by the one or more processors, rate rules associated with the group, ([0063] At step 308, a pricing engine associated with the VPS server assigns each of the available storage units to one of a plurality of pricing tiers within the pricing group according to the rank order of the available storage unit or, if it is a locked unit assigned to a specific pricing tier, according to the storage unit's locked pricing tier);
wherein each of the rate rules comprises:
a group-level operational metric, ([0018], each currently available storage unit is assigned to one of a plurality of pricing tiers within the pricing group based on the rank order of the storage units. Within a pricing group, units assigned to the same pricing tier have the same rental rate. The pricing tier to which a unit is assigned will vary depending on which other units in the pricing group are available. With a pricing group, the pricing tier containing the most desirable units that are available will generally have a price that is higher than the pricing tier to which the next most desirable units are assigned);
a logical operator, ([0066] Table 5 describes several of the key parameters and variables used within the core algorithm. Those skilled in the art can appreciate that there are variety of parameters that are not shown below but may be used to implement the core algorithm, (TABLE-US-00005 TABLE 5...Locked storage units to top VPTOut will be set to the Deluxe pricing tier (4). level Condition Storage unit 0, 1, 2, 3 0 = “OK”, 1 = minor issue, 2 = more Condition major issue, 3 = unrentable DR_IN Input Desirability 1 . . . Tot_Units Best to worst unit within PG (initially Ranking based on the field audit). DR_OUT Output Desirability 1 . . . Tot_Units Best to worst unit within PG (output Ranking from module based on update rules) DR_AVG In PG, mean value 1 . . . Tot_Units Average calculated across storage units of DR_OUT “avail to rebalance” (in Num_ARB) MAU Minimum >=1 Threshold value for Num_ARB, below Available storage which special conditions may apply);
a comparison direction, ([0004] the storage facility may automatically set the move-in price of a pricing group to increase once the percentage of units that are occupied in the pricing group has reached a certain level; [0132] A third party sales channel may include a web service comparatively advertising available storage units based on prices, such as Sparefoot.com or Storageseeker.com);
a target or threshold value, (TABLE-US-00005 TABLE 5... MAU Minimum >=1 Threshold value for Num_ARB, below Available storage which special conditions may apply; TABLE-US-00006 TABLE 6 Parameter Default Setting Comment MAU 4 “Sparse” conditions below MAU may have special rules DR_T4_PCT 80% Ensures Deluxe storage units are above average desirability A3_PCT 60% Determines target mix between Best Value and Deluxe NMIN1 4 Min threshold for numarb = 1 special case NMIN2 8 Max threshold for numarb = 1 special case B 80% B % value for numarb = 1 special case);
and an outcome specifying how to update a pricing parameter for units in the group, (Abstract: The server computer then assigns each of the available storage units to one of a plurality of pricing tiers within the pricing group according to the desirability rank order and generates an updated sales plan containing the available storage unit inventory grouped by the pricing group and by the pricing tiers; [0002] The present invention relates generally to a computer implemented method and system for periodically updating a pricing structure and, more specifically, to dynamically pricing self-storage storage units based on availability and desirability); and
retrieving, by the one or more processors, current operational metrics for the group, ([0029] Availability Data: Data concerning the current occupancy status of the storage units located at a storage facility.TABLE-US-00005 TABLE 5...For at the storage example, ‘S’ is “self-storage,” ‘P’ is facility “Parking,” etc. Num_Avail Number of >=0 Total within PG with UnitStatusID = 0 available/Ready (available). Units with other Units UnitStatusID codes are not included. Num_ARB Number of >=0 Total within PG after locked (available) available storage units and lower 2 tiers are removed. units that are pre- assigned to a pricing tier and available to rent);
and evaluating the current operational metrics against the rate rules associated with the group to determine whether the current operational metrics satisfy all conditions of any of the rate rules associated with the group, ([0132] In another embodiment, the sales plan may also be accessible or transmitted to a third party computing device (not shown) that is not associated with the self-storage facility or the self-storage corporate entity. For example, the sales plan may be accessed by or transmitted to a computing device used by a commissioned non-company independent sales representative or a machine capable of carrying out a complex series of actions automatically, such as a kiosk. In another example, the sales plan may be accessible or transmitted to a third party sales channel. A third party sales channel may include a web service comparatively advertising available storage units based on prices, such as Sparefoot.com or Storageseeker.com; TABLE-US-00005 TABLE 5 Units with other Units UnitStatusID codes are not included. Num_ARB Number of >=0 Total within PG after locked (available) available storage units and lower 2 tiers are removed. units that are pre- assigned to a pricing tier and available to rent Tot_Units Total number of >=Num_Avail Total within PG (includes occupied, units damaged, etc.) VPTLocked Storage unit locked 1, 0 A locked flag = 1. Locked storage units to top VPTOut will be set to the Deluxe pricing tier (4). level Condition Storage unit 0, 1, 2, 3 0 = “OK”, 1 = minor issue, 2 = more Condition major issue, 3 = unrentable DR_IN Input Desirability 1 . . . Tot_Units Best to worst unit within PG (initially Ranking based on the field audit). DR_OUT Output Desirability 1 . . . Tot_Units Best to worst unit within PG (output Ranking from module based on update rules) DR_AVG In PG, mean value 1 . . . Tot_Units Average calculated across storage units of DR_OUT “avail to rebalance” (in Num_ARB) MAU Minimum >=1 Threshold value for Num_ARB, below Available storage which special conditions may apply units DR_T4_PCT Factor for Min Top 0%-100% Used in conjunction with DR_AVGunit Tier DR to qualify for top VPTOut level T2 Target num of >=1 Will vary by Num_Avail within PG storage units with VPTOut = 2 A3_PCT Target Alloc % to 0%-100% Target allocation of “free” storage units VPT = Best Value within PG to VPT = 3 A4_PCT Target Alloc % to (100%- Target allocation of “free” storage units VPT = Deluxe A3_PCT) within PG to VPT = 4; [0065] In an exemplary embodiment, the VPS may initiate a core algorithm to dynamically price available storage units within a self-storage facility based on desirability rank). [Here, the desirability rank is derived from rules, therefore, it is obvious to evaluating the current operational metrics against the rate rules associated with the group to determine whether the current operational metrics satisfy all conditions of any of the rate rules, since in Lieberman, the storage units are priced based on desirability]);
in response to determining that the current operational metrics satisfy all conditions of a rate rule associated with the group, automatically generating, by the one or more processors, an updated price for at least one storage unit in the group in accordance with the outcome specified in the satisfied rate rule, (TABLE-US-00005 TABLE 5...“ Num_ARB Number of >=0 Total within PG after locked (available) available storage units and lower 2 tiers are removed. units that are pre- assigned to a pricing tier and available to rent Tot_Units Total number of >=Num_Avail Total within PG (includes occupied, units damaged, etc.) VPTLocked Storage unit locked 1, 0 A locked flag = 1. Locked storage units to top VPTOut will be set to the Deluxe pricing tier (4). level Condition Storage unit 0, 1, 2, 3 0 = “OK”, 1 = minor issue, 2 = more Condition major issue, 3 = unrentable DR_IN Input Desirability 1 . . . Tot_Units Best to worst unit within PG (initially Ranking based on the field audit). DR_OUT Output Desirability 1 . . . Tot_Units Best to worst unit within PG (output Ranking from module based on update rules) DR_AVG In PG, mean value 1 . . . Tot_Units Average calculated across storage units of DR_OUT “avail to rebalance” (in Num_ARB) MAU Minimum >=1 Threshold value for Num_ARB, below Available storage which special conditions may apply units DR_T4_PCT Factor for Min Top 0%-100% Used in conjunction with DR_AVGunit Tier DR to qualify for top VPTOut level T2 Target num of >=1 Will vary by Num_Avail within PG storage units with VPTOut = 2 A3_PCT Target Alloc % to 0%-100% Target allocation of “free” storage units VPT = Best Value within PG to VPT = 3 A4_PCT Target Alloc % to (100% - Target allocation of “free” storage units VPT = Deluxe A3_PCT) within PG to VPT = 4)); and
transmitting, by the one or more processors, the updated price for the at least one storage unit in the group to a remote computing device via a network, ([0064] At step 310, the VPS server
computer generates an output of an updated sales plan containing the available storage unit inventory
grouped by the pricing group and by the pricing tiers within the pricing groups. This output may be
communicated to the requesting party, and in some embodiments, delivered to a property management
software platform used by the storage facility for display and printing).
It would have been obvious to one of ordinary skill in the art at the time the invention was made to include the above limitations as taught by Lieberman et al, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 3, Lieberman et al discloses:
further comprising: determining to increase the price of a storage unit type based on one or
more key performance indicators and one or more metrics; and establishing the increased price for the
storage unit type, ([0054] In some circumstances, it may be desired to assign only a few units to the
standard pricing tier at any one time. This allows for a majority of the available storage units within a
pricing group to be classified in a higher pricing tier such as the best value pricing tier or the deluxe
pricing tier. Classifying most of the available storage units in higher pricing tiers allows a storage facility
employee to focus their sales pitch of available storage units in higher pricing tiers to inquiring
customers while simultaneously ensuring that the self storage facility is able to provide a competitive
standard price for those customers who are primarily price-driven rather than service-oriented when
choosing their self-storage unit).
As per claim 7, Lieberman et al discloses:
wherein the group of different types of storage units includes a name, a description, and the storage unit types in the group, and the one or more rate rules that are used to determine individual unit type pricing for each group, (Fig 4).
As per claim 8, this claim recites limitations similar to those disclosed in independent claim 1
and is therefore rejected for similar reasons.
As per claim 10, please see the rejection of claim 3.
As per claim 14, please see the rejection of claim 7.
As per claim 15, this claim recites limitations similar to those disclosed in independent claim 1
and is therefore rejected for similar reasons.
As per claim 17, please see the rejection of claim 3.
As per claim 20, please see the rejection of claim 7.
Claim(s) 4, 11, 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Liebermane al
(US 20210103872 A1), and further in view of Shoen et al (US 20060206342 A1).
As per claim 4, Lieberman et al does not disclose the following, however, Shoen et al discloses:
further comprising: generating a change set for a storage unit type with a date the change set is
executed; determining one or more ledgers affected by the change set based on one or more key
performance indicators and one or more metrics; and applying a rate change formula to one or more
tenants of the storage unit type, (Shoen et al (US 20060206342 A1 ) [0083] In a preferred embodiment
of the invention, as shown in FIG. 29, after applying the payment, the system provides the user with an
updated fees due summary 480 that lists the charges that remain outstanding. The system also provides
the user with a summary of payments collected 482. In the embodiment shown in FIG. 29, the payments
collected feature 482 indicates that a payment of $221.49 was made by money order number 1234. A
summary of the customer's account may also be obtained by activating the ledger feature 490 of the
system. The ledger feature 490, as best shown in FIG. 30, provides an account history for a specified
contract. In a preferred embodiment of the invention, the ledger feature 490 includes a listing of all
charges 491, payments 492, reversed charges 494 and fee waivers 495. The ledger feature 490 also
indicates the charges which have been paid in full 496 and provides the balance due 497 on the account.
It would have been obvious to one of ordinary skill in the art at the time of the invention to
include the above limitations as taught by Shoen et al in the systems of Lieberman et al, since the
claimed invention is merely a combination of old elements, and in the combination each element merely
would have performed the same function as it did separately, and one of ordinary skill in the art would
have recognized that the results of the combination were predictable.
As per claim 11, please see the rejection of claim 4.
As per claim 18, please see the rejection of claim 4.
Claim(s) 5, 6, 12, 13, 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lieberman
et al (US 20210103872 A1), and further in view of Walker et al (US 20030101087 A1).
As per claim 5, Lieberman et al does not disclose the following, however, Walker et al discloses:
determining to increase or decrease a current price for a storage unit type based on the
generated updated price, (Walker et al (US 20030101087 A1): [0150] The demand elasticity estimator (DEE) 700 estimates demand elasticity, step 1170 in FIG. 11. The operation of DEE 700 is summarized in FIG. 7. The magnitude of change in demand in response to the change in rent depends on the demand elasticity. Demand elasticity is typically defined as the percentage change in demand versus the percentage change in price. The DEE 700 assumes an inverse relationship between price and demand; that is, DEE 700 defines elasticity to be the percentage decrease (increase) in demand versus the percentage increase (decrease) in price. As a result, elasticity is always negative).
It would have been obvious to one of ordinary skill in the art at the time of the invention to
include the above limitations as taught by Walker et al in the systems of Lieberman et al, since the
claimed invention is merely a combination of old elements, and in the combination each element merely
would have performed the same function as it did separately, and one of ordinary skill in the art would
have recognized that the results of the combination were predictable.
As per claim 6, Lieberman et al discloses:
wherein the current operational metrics include available storage unit types, The method
(100) involves determining a pricing tier of a plurality of pricing tiers for each of the available storage
units based on a total number of available storage units within each of the pricing groups and the rank
order of the available storage units by the server.
Lieberman et al does not disclose the following, however, Walker et al discloses:
occupancy percentage, and net rentals during a threshold of time, (Walker et al (US 20030101087 A1)
[0097] Another variable maintained by the update module 300 is QOB. QOB results indicate that the
number of guest cards depends on the occupancy level. Since during high rates of occupancy, demand
requests are turned down for lack of availability, there is a significant correlation between occupancy
and number of guest cards. The update module 300 first compute occupancy as 24 Occupancy = OnRent
PhysicalCapacity - NonRevenue (21 ); [0126] For optimization, the LRO 100 computes Optimizable Rent
at WK, UC, LTC, LNR, MS level based on client's historical rents and competitor rents. This is computed
as Reference Rent minus Property preparation and Vacancy Costs for each WK, UC, LTC, LNR, and MS
level. This is one of the main inputs to the optimization model and represents net expected
contribution).
It would have been obvious to one of ordinary skill in the art at the time of the invention to
include the above limitations as taught by Walker et al in the systems of Lieberman et al, since the
claimed invention is merely a combination of old elements, and in the combination each element merely
would have performed the same function as it did separately, and one of ordinary skill in the art would
have recognized that the results of the combination were predictable.
As per claim 12, please see the rejection of claim 5.
As per claim 13, please see the rejection of claim 6.
As per claim 19, please see the rejection of claim 6.
Response to Arguments
Applicant's arguments filed 3/31/26 have been fully considered but they are not persuasive.
With regard to the 101 rejection, Applicant argues that the claims have been amended in a manner that renders the rejections moot. However, the claims as amended are still rejected under 101. Applicant’s arguments have been fully considered but are moot in view of the claim amendments. The claims have been amended in a manner that does not overcome the previously applied rejection under 35 USC 101 because the amended claims continue to recite an abstract idea relating to pricing management and rule-based evaluation of operational metrics implemented using generic computer components, an abstract idea. Accordingly, the 101 rejection is maintained.
With regard to the 103 rejection, Applicant argues that although Applicant disagrees with the rejections, the independent claims have been amended to advance prosecution. Applicant specifically argues that Lieberman does not identify multiple rate rules assigned to a group, where each of the rate rules includes at least “a group-level operational rate”, “a logical operator”, “a comparison direction”, “a target or threshold value”, and “an outcome specifying how to update a pricing parameter for units in the group”. However, Examiner respectfully disagrees. With regard to identifying multiple rate rules assigned to a group, Lieberman discloses this limitation by showing [0004] “the storage facility may automatically set a price increase for all storage units on the weekends...” and also in [0004] “the storage facility may automatically set the move-in price of a pricing group to increase once the percentage of units that are occupied in the pricing group has reached a certain level” which are different pricing rules applied to the same pricing group. In addition, Lieberman discloses assigning storage units to pricing options, dynamically updating pricing, (See abstract), changing prices based on varying operational conditions and reassigning pricing tiers as availability changes (See Table 5). Therefore the “multiple rate rules” are disclosed in Lieberman as the multiple pricing adjustment conditions such as the weekend rule, occupancy rule, availability rule and desireability rule).
With regard to “assigned to a group”, Lieberman discloses rules/pricing logic applied to storage units in a group (see Table 5), also see [0031] “where each storage unit, in a storage unit inventory for all storage units existing at the storage facility, is assigned to a pricing group”.
With regard to where each of the rate rules includes at least “a group-level operational rate”, Lieberman discloses occupancy levels, availability levels, rental activity and pricing-group metrics for storage units (see [0018], each currently available storage unit is assigned to one of a plurality of pricing tiers within the pricing group based on the rank order of the storage units. Within a pricing group, units assigned to the same pricing tier have the same rental rate. The pricing tier to which a unit is assigned will vary depending on which other units in the pricing group are available.).
With regard to “a logical operator”, Table 5 shows the implementation of “level Condition Storage unit 0, 1, 2, 3 0 = “OK”, 1 = minor issue, 2 = more Condition major issue, 3 = unrentable DR_IN Input Desirability 1” in order to perform calculations.
With regard to “a comparison direction”, Lieberman discloses conditions such as occupancy reaching or exceeding a threshold, for example when the price changes when occupancy has reached a certain level, (See [0004], “the storage facility may automatically set the move-in price of a pricing group to increase once the percentage of units that are occupied in the pricing group has reached a certain level”).
With regard to “a target or threshold value”, Lieberman shows this through disclosing occupancy thresholds and pricing triggers, (See Table 5).
With regard to “an outcome specifying how to update a pricing parameter for units in the group”, Lieberman shows this through disclosing changing prices for a pricing group, (See [0002] “The present invention relates generally to a computer implemented method and system for periodically updating a pricing structure and, more specifically, to dynamically pricing self-storage storage units based on availability and desirability” and Table 5).
Applicant also argues that Lieberman fails to disclose evaluating current operational metrics for the group against all the assigned rates rules to determine whether “the current operational metrics satisfy all conditions of any of the rate rules associated with the group”. However, Examiner respectfully disagrees. As already disclosed in the above arguments and Office Action, Lieberman discloses increasing prices when occupancy reaches a threshold, applying pricing logic to pricing groups, dynamically updating pricing based on operational conditions, and automatically adjusting pricing wen conditions are satisfied, which is analogous to “evaluating current operational metrics for the group against assigned rate rules” since Leiberman shows comparing occupancy and availability metrics against pricing criteria. Furthermore, Lieberman’s disclosure also is analogous to “determine whether the current operational metrics satisfy all conditions of any of the rate rules associated with the group” since in Lieberman, the pricing actions occur only when the specific triggering conditions are met. Examiner therefore maintains the Lieberman reference.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Akiba Robinson whose telephone number is 571-272-6734 and email is Akiba.Robinsonboyce@USPTO.gov. The examiner can normally be reached on Monday-Thursday 6:30am-4:30pm.
If attempts to reach the Examiner by telephone are unsuccessful, the Examiner's supervisor, Nathan Uber can be reached on 571-270-3923. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Any inquiry of a general nature or relating to the status of this application or proceeding should be directed to the receptionist whose telephone number is (703) 305-3900.
May 27, 2026
/AKIBA K ROBINSON/Primary Examiner, Art Unit 3626
Prosecution Insights