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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 21 May 2026 has been entered.
Status of Claims
This is a non-final office action in response to the request for continued examination filed 21 May 2026. Claims 1, 12, and 19 have been amended. Claims 9 and 20 have been canceled, and claim 22 is newly added. Claims 1-8, 10-19, and 21-22 remain pending and have been examined.
Response to Amendment
Applicant’s amendment to claims 1, 12, and 19, and addition of new claim 22 has been entered.
Applicant’s amendment is insufficient to overcome the pending 35 U.S.C. 101 rejection. The rejection remains pending and is updated below, as necessitated by amendment.
Applicant’s amendment is sufficient to overcome the pending 35 U.S.C. 103 rejection. The rejection is respectfully withdrawn.
Response to Arguments
Applicant’s arguments regarding the 35 U.S.C. 101 rejection have been fully considered, but are not persuasive. Applicant asserts that the claims are not directed to an abstract idea and the limitations do not fall within the certain methods of organizing human activity grouping. Examiner respectfully disagrees. Per paragraph [0076] of the Specification the analytics module analyzes “collected data, such as, for example, customer data, agent data, and interaction data. The models may include behavior models of customers or agents. The behavior models may be used to predict behaviors of, for example, customers or agents, in a variety of situations, thereby allowing embodiments of the technologies described herein to tailor interactions based on such predictions or to allocate resources in preparation for predicted characteristics of future interactions, thereby improving overall contact center performance and the customer experience.” Therefore, the recited limitations are related to performance metrics based on customer service interactions, which falls within the definition of certain methods of organizing human activities. Further, analyzing collected data to determine performance metrics and for decision making for “improving overall contact center performance and the customer experience” could be performed mentally or through use of pen and paper and therefore fall within the mental processes grouping of abstract concepts.
Applicant asserts that the claims include specific recitations that place meaningful limits on any alleged judicial exception because the claims have been amended to include additional details for complaining agent performance over a plurality of agents and visualizing the comparison, “in which the selected agent profile groups multiple agents by a characteristic of a work schedule that is shared by the multiple agents.” Examiner respectfully disagrees. The steps for filtering of analyzed data into agent groups for visualization of a data comparison is not a meaningful limitation to the recited abstract idea. These steps are merely a process of gathering and analyzing information of a specified content, and then displaying the results, and not as any particular inventive technology for performing those functions. Analyzing a data set (customer feedback and performance data) to generate a new set of data (performance metrics) for further analysis and comparison by a generic computer acting as a tool to perform the abstract idea of evaluating agent performance, does not transform or reduce the analyzed data into a different state or thing. It is merely further manipulation of data by applying mathematical concepts (comparisons and algorithms) to manipulate existing information to generate performance indicators. Therefore, the abstract idea is not integrated into a practical application.
Applicant also asserts that under Step 2B, each of the amended claims recite significantly more than the abstract idea, regardless of the characterization of the claims as an abstract idea. Applicant submits that the amended features of the claims recite “ ‘additional features’ that are not taught by the prior art of record when each claim is interpretated as a whole… that at least those features not taught, when read in view of the claim as a whole, constitute significantly more that the alleged abstract idea.” Examiner respectfully disagrees. The analysis of claims under 35 U.S.C. 101 and 35 U.S.C 103 are separate and distinct determinations. Claims that overcome a prior art rejection do not by default overcome 35 U.S.C. 101. The claim limitations do not have an inventive concept because the claim limitations merely recite various computer-based elements along with no more than mere instructions to implement the identified abstract idea using the computer-based elements. The claimed limitations viewed “both individually and as an ordered combination,” do not recite significantly more than the judicial exception to transform the claim into patent-eligible subject matter.
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 1-8, 10-18, and 21-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claim 1 recites a device, independent claim 12 recites a process, and independent claim 19 recites a product for evaluating agent performance. Independent claims 1 and 19 recite substantially similar limitations.
Taking claim 1 as representative for claim 9, claim 1 recites the following limitations:
obtain metric data for one or more agents including a plurality of raw performance indicators each corresponding to a particular agent performance metric of a plurality of agent performance metrics;
convert, based on the metric data, each of the plurality of raw performance indicators into a points score for the particular agent performance metric to provide a plurality of points scores for the plurality of agent performance metrics;
calculate, based on the points score, a goal percentage for each particular agent performance metric to provide a plurality of goal percentages for the plurality of agent performance metrics; and
compare, based on the plurality of goal percentages, agent performance over the plurality of agent performance metrics including to display, for each agent in an agent profile selected by a user, the plurality of goal percentages for the plurality of agent performance metrics assigned to the particular agent to facilitate visualized comparison of agent performance across the selected agent profile, in which the selected agent profile groups multiple agents by a characteristic of a work schedule, that is shared by multiple agents,
wherein to convert each of the plurality of raw performance indicators into a points score comprises to normalize the points score for the particular agent performance metric across a plurality of variables to evaluate agent performance according to a common standard.
Claim 12 recites the following limitations:
obtaining, by a computing system, metric data for one or more agents including a plurality of raw performance indicators each corresponding to a particular agent performance metric of a plurality of agent performance metrics;
converting, by a computing system and based on the metric data, each of the plurality of raw performance indicators into a points score for the particular agent performance metric to provide a plurality of points scores for the plurality of agent performance metrics;
calculating, by the computing system and based on the points score, a goal percentage for each particular agent performance metric to provide a plurality of goal percentages for the plurality of agent performance metrics; and
comparing, by the computing system and based on the plurality of goal percentages, agent performance over the plurality of agent performance metrics,
wherein converting each of the plurality of raw performance indicators into a points score comprises normalizing the points score for the particular agent performance metric across a plurality of variables to evaluate agent performance according to a common standard, and
wherein comparing agent performance over the plurality of agent performance metrics comprises comparing, for each agent in an agent profile selected by a user in which the selected agent profile groups multiple agents by a characteristic of a work schedule that is shared by the multiple agents, agent performance for the particular agent over a first predefined time interval to agent performance for the particular agent over a second predefined time interval.
Under Step 1, independent claims 1, 12, and 19 recite at least one step or act, including obtaining metric data. Thus, the claims fall within one of the statutory categories of invention.
Under Step 2A Prong One, the limitations recited in claims ,. 12, and 19 for obtaining metric data for one or more agents, converting each of the plurality of raw performance indicators into a points score for the particular agent performance metric, calculating a goal percentage for each particular agent performance metric, comparing agent performance over the plurality of agent performance metrics, normalizing the points score for the particular agent performance across a plurality of variables, and comparing agent performance for the particular agent over a predefined time interval, under its broadest reasonable interpretation falls within the "Certain Methods of Organizing Human Activity" grouping of abstract ideas, because the inventive concept involves managing the behavior of call/contact center agents by gathering job performance metrics to determine whether business goals are being met for providing various types of services to customers and improving overall contact center performance and the customer experience. See at least Spec. at [0056, 0076]. Each of the claimed steps could also be performed mentally or through use of a pen and paper and as a result, reasonably fall under the mental processes grouping of abstract ideas. Additionally, the steps for converting raw performance indicators into a points score, calculating a goal percentage, and normalizing the points score, and comparing agent groups according to certain characteristics, fall within the mathematical concepts grouping of abstract ideas because the scoring, normalizing, and converting steps involve mathematical relationships and calculations. Accordingly, the claims recite an abstract idea.
Under Step 2A Prong Two, the judicial exception of claims 1, 12, and 19 is not integrated into a practical application. In particular, the claims only recite a processor and storage device for performing the recited steps. These additional elements are recited at a high level of generality (i.e., as a generic processor performing a generic computer function) and amount to no more than mere instructions to apply the exception using generic computer components. See MPEP 2106.05(f). For example, Applicant’s specification at paragraph [0051] states: “The computing device 100 may be any workstation, desktop computer, laptop or notebook computer, server machine, … or any other type of computing, telecommunications or media device, without limitation, capable of performing the operations and functionality described herein.” The Specification does not provide additional details about the computer system r that would distinguish it from any generic processing devices that communicate with one another in a network environment. Adding generic computer components to perform generic functions, such as data gathering, performing calculations, and outputting a result would not transform the claim into eligible subject matter. See MPEP 2106.05(h).
The steps for filtering of analyzed data into agent groups for visualization of a data comparison is not a meaningful limitation to the recited abstract idea. These steps are merely a process of gathering and analyzing information of a specified content, and then displaying the results, and not as any particular inventive technology for performing those functions. Analyzing a data set (customer feedback and performance data) to generate a new set of data (performance metrics) for further analysis and comparison by a generic computer acting as a tool to perform the abstract idea of evaluating agent performance, does not transform or reduce the analyzed data into a different state or thing. It is merely further manipulation of data by applying mathematical concepts (comparisons and algorithms) to manipulate existing information to generate performance indicators. Therefore, the abstract idea is not integrated into a practical application.
The claim fails to recite actual interface functionality. As claimed herein the limitations for displaying the results of the data processing steps processed data amounts to insignificant extra-solution activity, not to specific interaction with an object selected from a graphical user interface (GUI) with claim limitations related to how the interface performs in response to the specific action in a particular interface interaction in a technical manner that provides a technical improvement to interface technology. The claims fails to recite a significant amount of interaction with a particular interface element that uses the information in a particular way such that the claims integrate the judicial exception into a practical application by modifying or improving the functions of the GUI. Specifying the abstract idea of gathering and analyzing agent performance metrics to evaluate agent performance being executed in a computer environment merely indicates a field of use, i.e. to execution on a generic computer. Accordingly, the 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.
Under Step 2B the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements of a processor and storage device amount to no more than mere instructions to apply the exception using a generic computer component which cannot provide an inventive concept. See MPEP 2106.05.
Dependent claims 2-8, 11, 13-18, and 21-22 include the abstract ideas of the independent claims. The limitations of the dependent claims merely narrow the method of organizing human activity abstract idea by describing how the gathered performance metrics are manipulated, analyzed, and presented to users. The limitations of the dependent claims are not integrated into a practical application because none of the additional elements set forth any limitations that meaningfully limit the abstract idea implementation. There are no additional elements that transform the claim into a patent eligible idea by amounting to significantly more. The analysis above applies to all statutory categories of invention. Accordingly independent claims 1 and 19 and the claims that depend therefrom are rejected as ineligible for patenting under 35 U.S.C. 101 based upon the same analysis applied to claim 12 above. Therefore, claims 1-8, 10-19, and 21-22 are ineligible under 35 U.S.C. 101.
Allowable Subject Matter
Claims 1-8, 10-19, and 21-22 are rejected under 35 U.S.C. 101, but the claims would be allowable if the aforementioned rejections are overcome.
The 35 U.S.C. 103 rejection is withdrawn in light of Applicant’s Amendments and Remarks herein, which are deemed persuasive. Examiner analyzed amended claims 1, 12, and 19 in view of the prior art of record and an updated prior art search and finds not all claim limitations are explicitly taught nor would one of ordinary skill in the art find it obvious to combine these references with a reasonable expectation of success. Particularly, the prior art of record does not teach, suggest, or otherwise disclose a system that displays, for each agent in an agent profile that groups multiple agents that share a characteristic of a work schedule, a plurality of goal percentages for the plurality of agent performance metrics assigned to each agent to facilitate visualized comparison of agent performance across the selected agent profile (e.g., across the multiple agents grouped by that selected agent profile), as required by amended independent claim 1. Therefore, claims 1-8, 10-19, and 21-22 are eligible over the prior art.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Beaver et al. (US 2025/0315769) - One aspect provides a method for providing automated agent performance ranking includes obtaining, for each agent of a plurality of agents, a performance score for each feature associated with a plurality of customer-agent interactions, wherein each feature is associated with a key performance indicator (KPI) metric and is under control of the agent; determining a task label for each of the plurality of customer-agent interactions; grouping the plurality of customer-agent interactions into one or more task groups based on the task label for each of the plurality of customer-agent interactions; determining, for each agent of the plurality of agents, a task-feature performance value, wherein the task-feature performance value is a combination of the performance score for each feature associated with the one or more task groups; and generating, for each feature, a report comprising a ranking for each agent of the plurality of agents based on the task-feature performance value.
Burke et al. (US 2015/0134694) - a database of reference metrics data determined from testing of members of a reference population; means for selecting target group metrics data, the metrics data determined from testing of the members of the target group and associated with metadata relating to the target group; means for selecting at least one item of metadata; means for selecting a reference group from the reference population in dependence on the selected metadata, the reference group being associated with reference group metrics data determined from testing of the members of the reference group and associated with metadata relating to the reference group; means for selecting a comparison aspect, the comparison aspect being associated with a subset of metrics data; means for generating comparison data relating to the comparison of the distribution of metrics data values for the target group with that of the reference group in accordance with the selected comparison aspect; and means for outputting the resulting comparison data.
Deodhar et al. (US 2017/0116552) - automated measurement, analysis and improvement of exact effort spent on business related activities and objectives, without requiring manual intervention or configuration.
Gundappa et al. (US 2018/0330292) - providing a common user interface for different functional users. The common user interface is configured to display multiple visualizations and reports associated with the transactions. The method also includes obtaining, according to a user input at the common user interface, one or more metrics and one or more analytics from the data store. The one or more metrics and the one or more analytics are associated with the obtained information. The method also includes configuring the common user interface to display, according to the user input, at least one visualization or report involving the one or more metrics and the one or more analytics.
Lightbown (US 2024/0005252) - method for measuring service performance of a company. The company may be a human services company. A performance technology system is provided for facilitating the method. The performance technology system, operating on a services performance server, enables human service providers to measure every change of every client in service to accurately reflect service performance and changes in the rate of service impact from period to period.
Silvera et al. (US 2007/0276722) - methods of aligning an agent's compensation with an organization's goals, incentivizing an agent to improve their performance, and managing an agent. In one embodiment, the present invention includes defining a performance metric that relates to a goal of an organization. Performance levels are then defined for the performance metric. The performance levels are associated with performance values that an agent must meet to have their performance classified within a performance level. The method also includes providing a compensation rule that defines which of the performance levels an agent must achieve to change their current compensation. The performance of an agent with respect to the performance metric is then monitored to generate an agent performance, which is compared to the previously established achievement values to determine an agent's performance level.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LETORIA G KNIGHT whose telephone number is (571)270-0485. The examiner can normally be reached M-F 9am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rutao WU can be reached at 571-272-6045. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/L.G.K/Examiner, Art Unit 3623 /RUTAO WU/Supervisory Patent Examiner, Art Unit 3623
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