Prosecution Insights
Last updated: April 19, 2026
Application No. 18/323,806

EMPLOYEE NET PROMOTER SCORE GENERATOR

Non-Final OA §101
Filed
May 25, 2023
Examiner
LOFTIS, JOHNNA RONEE
Art Unit
3625
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Degree Inc.
OA Round
3 (Non-Final)
43%
Grant Probability
Moderate
3-4
OA Rounds
4y 4m
To Grant
48%
With Interview

Examiner Intelligence

Grants 43% of resolved cases
43%
Career Allow Rate
216 granted / 499 resolved
-8.7% vs TC avg
Minimal +4% lift
Without
With
+4.2%
Interview Lift
resolved cases with interview
Typical timeline
4y 4m
Avg Prosecution
34 currently pending
Career history
533
Total Applications
across all art units

Statute-Specific Performance

§101
39.7%
-0.3% vs TC avg
§103
30.2%
-9.8% vs TC avg
§102
16.8%
-23.2% vs TC avg
§112
9.1%
-30.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 499 resolved cases

Office Action

§101
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 December 29, 2025, has been entered. Response to Arguments Applicant's arguments filed with respect to Examples 39 and 47 and the Desjardins memo have been fully considered but they are not persuasive. In response to Applicant’s comments about Example 39, Examiner notes the analysis revealed there was no judicial exception present therefore the analysis under Prong 2 is not applicable. The current pending claims recite an abstract idea thus the fact patterns do not align. The analysis of the pending claim determined a judicial exception is recited, therefore the analysis proceeds to Prong 2. With respect to Example 47, the analysis showed an abstract idea that is integrated into a practical application because there is an improvement in the technical field of network intrusion detection. The pending claims do not recite an analogous technical improvement. While Applicant asserts the claims “detect anomalies and automatically take remedial action”, the anomalies and actions of the Example claim 3 reflect a technical improvement whereas the “anomalies and actions” of the pending claims relate to suggesting actions to improve an employee Net Promoter Score which is an abstract idea. The specification describes the improvement offered by the pending claims relates to understanding user sentiments in a way such that the entity can adapt its practices or policies to improve its levels of success with respect to various metrics, such as employee satisfaction, efficiency, and/or retention, that are deemed important by stakeholders of the entity [Background] which is an abstract process and not a technical improvement. With respect to Applicant comments regarding the Desjardins memo, Examiner notes that recommending actions in response to employee sentiment data is not a technical solution to a technical problem. Further, the specification does not describe an analogous improvement to the machine learning as in Desjardins. Here, it is not the artificial intelligence learning model that is improved. In this case, the machine learning is being used as a tool to implement the judicial exception and does not improve a technology or technical field. Applicant's arguments filed with respect to rejections under 35 USC 101 have been fully considered but they are not persuasive. Applicant first argues the amended limitation relating to machine-learned models cannot reasonably be performed in the human mind. Examiner points out that the machine learning models is not found to be an abstract idea, but an additional element considered under Prong 2. The use of machine learning amounts to using a computer as a tool to implement a learning model. As described above, there is no improvement to any computer technology or technical field. The rejection has been updated in response to the amendments. Next, Applicant reiterates the comments regarding the comparison to Example 47. Examiner notes the pending claims do not include a technical improvement as identified in the Example. Using first data from the machine learning model as second input to retrain the model, does not improve the learning model or the technology involved. This amounts to using a computer to implement a machine learning model. On page 12, Applicant reiterates the comments regarding Desjardins. As stated above, the specification does not describe an analogous improvement to the technology. The specification does not describe the machine learning with any specificity such that it amounts to using a computer as a tool to apply the machine learning. The claim does not reflect any alleged improvement. As claimed, suggested actions are generated, the actions including “machine-learned actions that previously improved the eNPS score” and proceeds to describe how the machine-learned actions were generated. The specification describes the suggested actions as a list of actions that can be included as an action in the plan [0871, 0872, 0908] and machine-learning models are trained an applied to create the curated list. This does not describe any technical improvement. The machine learning models amount to using a computer as a tool to implement a learning model and do not offer a technical improvement. Applicant argues the claims integrate the judicial exception into a practical application because they reflect an improvement in employee engagement technology by addressing the problem of stale data and delayed actionable insights through models that are trained iteratively and updated continuously. Examiner disagrees. The use of machine learning amounts to using a computer as a tool to implement a learning model. With respect to Step 2B, Examiner notes the analysis stopped at Step 2A. Applicant continues that the ordered combination of claim limitations describes a complete technical system for privacy-preserving, AI driven employee engagement analysis that addresses the problem of stale data through continuous updated machine learning. However, as claimed, the judicial exception is not integrated into a practical application because the use of machine learning amounts to using the words “apply it” with the learning model wherein the machine learning amounts to using a computer to implement the learning algorithm. There is no improvement to any technology or technical field. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claim(s) 1-4, 6, 8-11, 13, 15-18, 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. Claim(s) 1-4, 6, 8-11, 13, 15-18, 20 is/are directed to a method, system, and computer program product. Thus, all the claims are within the four potentially eligible categories of invention (a process, a machine and an article of manufacture, respectively), satisfying Step 1 of the Subject Matter Eligibility (SME) test. As per Prong One of Step 2A of the §101 eligibility analysis set forth in MPEP 2106, the Examiner notes that the claims recite mental processes and certain methods of organizing human activity. More specifically, in independent claim 8, [a] method comprising: collecting anonymous answers to the eNPS survey question from a plurality of employees of an entity; calculating an eNPS score for the entity, the calculating of the eNPS score including subtracting a percentage of detractors from a percentage of promoters; based on the eNPS score, generating one or more suggested actions for improving the eNPS score for the entity, the one or more suggested actions including one or more receiving an anonymity threshold value surfacing the eNPS score for the entity is Certain Methods of Organizing Human Activity since the claims recite managing relationships or interactions between people and also mental process since the claim recites observation/evaluation steps which can practically be performed in the mind or with pen and paper. Independent claims 1, 8 and 15 recite the same abstract idea. The additional computer limitations are addressed below. The recitation of generic computer components in a claim does not necessarily preclude that claim from reciting an abstract idea. Regarding Prong Two of Step 2A, a claim reciting an abstract idea must be analyzed to determine whether any additional elements in the claim integrate the judicial exception into a practical application. Limitations that are indicative of integration into a practical application include: Improvements to the functioning of a computer, or to any other technology or technical field, as discussed in MPEP 2106.05(a); Applying or using a judicial exception to effect a particular treatment or prophylaxis for disease or medical condition – see Vanda Memo; Applying the judicial exception with, or by use of, a particular machine, as discussed in MPEP 2106.05(b); Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP 2106.05(c); and 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, as discussed in MPEP 2106.05(e) and the Vanda Memo issued in June 2018. In this case, the independent claims do not include additional limitations that meet the criteria listed above, thus the abstract idea is not integrated into a practical application. Independent claim 1 recites a system comprising one or more computer processors; one or more computer memories; a set of instructions incorporated into the one or more memories, the set of instructions configuring the one or more computer processors to perform the abstract idea. The machine-learned actions generated by one or more machine-learned models, the one or more machine-learned models trained iteratively and updated continuously using a plurality of input data amount to using a computer to implement an algorithm and display the results. Claim 1 also recites a user interface. Independent claim 8 recites a user interface and the machine-learned actions generated by one or more machine-learned models, the one or more machine-learned models trained iteratively and updated continuously using a plurality of input data amount to using a computer to implement an algorithm and display the results. Independent claim 15 recites a non-transitory computer-readable storage medium storing instructions thereon, which when executed by one of more processors, cause one or more processors to perform the abstract idea. The machine-learned actions generated by one or more machine-learned models, the one or more machine-learned models trained iteratively and updated continuously using a plurality of input data amount to using a computer to implement an algorithm and display the results These additional limitations amount to using a computer as a tool to perform the abstract idea and do not integrate the abstract idea into a practical application. The dependent claims further limit the abstract idea and some recite additional elements that do not integrate the abstract idea into a practical application. Claims 2-4, 9-11 and 16-18 recite specific details of calculating the eNPS score based on percentages and thresholds. These recitations are mental process and can be practically performed in the human mind or with pen and paper. The claimed system amounts to using a computer as a tool to perform the abstract idea and does not integrate the abstract idea into a practical application. Claim 6, 13 and 20 recite the one or more surveys include one or more pulse surveys. This recitation adds additional detail to the abstract concept identified in claim 1 and the claimed system amounts to using a computer as a tool to perform the abstract idea and does not integrate the abstract idea into a practical application. The claims do not include limitations beyond generally linking the use of the abstract idea to a particular technological environment. When considered individually, the system and software claim elements only contribute generic recitations of technical elements to the claims. It is readily apparent, for example, that the claim is not directed to any specific improvements of these elements. The invention is not directed to a technical improvement. When the claims are considered individually and as a whole, the additional elements noted above appear to merely apply the abstract concept to a technical environment in a very general sense. Lastly and in accordance with 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 integration of the abstract idea into a practical application, the additional elements amount to no more than mere instruction to apply the exception using generic computer component. Mere instruction to apply an exception using generic computer components cannot provide an inventive concept. Allowable Subject Matter As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a). The following is a statement of reasons for the indication of allowable subject matter: The cited prior art taken alone or in combination fails to explicitly teach the claim limitations in combination with the anonymity threshold as claimed. The closest prior art Russ et al discloses an anonymity threshold, but in the context of the claims and the previously cited prior art does not teach surfacing the eNPS score for the entity in the administrative user interface based on the anonymity threshold value being transgressed. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHNNA LOFTIS whose telephone number is (571)272-6736. The examiner can normally be reached M-F 7:00am-3:30pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Brian Epstein can be reached at 571-270-5389. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. JOHNNA LOFTIS Primary Examiner Art Unit 3625 /JOHNNA R LOFTIS/Primary Examiner, Art Unit 3625
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Prosecution Timeline

May 25, 2023
Application Filed
Mar 13, 2025
Non-Final Rejection — §101
Aug 19, 2025
Response Filed
Oct 24, 2025
Final Rejection — §101
Dec 29, 2025
Response after Non-Final Action
Jan 27, 2026
Request for Continued Examination
Feb 17, 2026
Response after Non-Final Action
Feb 21, 2026
Non-Final Rejection — §101 (current)

Precedent Cases

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
43%
Grant Probability
48%
With Interview (+4.2%)
4y 4m
Median Time to Grant
High
PTA Risk
Based on 499 resolved cases by this examiner. Grant probability derived from career allow rate.

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