Prosecution Insights
Prosecution Insights
Technology areas: Computing & Software • Communications • Transportation, E-Commerce & Mechanical Systems
13 pending office actions • 10 art units • 12 examiners • 0 of 13 (0%) have an AI response strategy ready • 9 patents granted in the last 365 days
Nielsen Consumer LLC currently has 10 pending office actions within the Computing & Software technology area. These actions are distributed across 4 distinct art units, showing a concentration of the company's current USPTO activity in a few specialized sections. The prosecution is handled by 10 distinct examiners, meaning that every pending action is currently assigned to a different individual.
The busiest examiner, GAVIN, KRISTIN ELIZABETH, has only 1 pending office action, which reflects the broader trend of one examiner per action across the 10 pending matters. This lack of examiner overlap suggests that Nielsen Consumer cannot leverage a single examiner's history to predict the outcomes of multiple pending cases. Each of the 10 distinct examiners will bring a unique perspective to the 10 pending office actions.
With 4 distinct art units involved, the portfolio is spread across multiple technical domains within the Computing & Software field. The fact that the busiest examiner, GAVIN, KRISTIN ELIZABETH, holds only 1 pending action emphasizes the decentralized nature of the company's current prosecution. This requires the legal team to manage 10 separate examiner relationships simultaneously to resolve the 10 pending actions.
Based on the USPTO statutory response window for each pending office action. 3 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Every pending office action with a known statutory deadline, placed on a days-until-due axis. Dots left of Today are overdue; the further right, the more runway. Cases that share a deadline window stack vertically. 3 of the docket's apps have a known mailing date.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §101 only | 1 (8%) |
| §101 + other | 8 (62%) |
| §112 only | 1 (8%) |
| Double-patenting only | 1 (8%) |
| Multi-statute (no §101) | 2 (15%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| GAVIN, KRISTIN ELIZABETH | 2 | 15.0% | +17.5% |
| WHITE, DYLAN C | 1 | 76.9% | +13.6% |
| OBEID, FAHD A | 1 | 28.3% | +48.3% |
| SHAH, UTPAL D | 1 | 87.8% | +11.4% |
| DUNPHY, DAVID F | 1 | 85.4% | +10.0% |
| KASHYAPA, ANUSHA | 1 | 100.0% | +0.0% |
| LU, HWEI-MIN | 1 | 63.2% | +40.9% |
| LEVEL, BARBARA HENRY | 1 | 72.0% | +28.1% |
| SMITH, BRIAN M | 1 | 52.5% | +36.9% |
| MESFIN, MATTHEWOS | 1 | — | — |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18967907 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO DECODE RECEIPTS BASED ON NEURAL GRAPH ARCHITECTURE | DUNPHY, DAVID F | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17977967 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO PROVIDE VISUALIZATIONS OF VOLUME SHIFT ANALYSIS | HO, THOMAS Y | 9d overdue |
| 18309325 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO REDUCE LONG-TAIL CATEGORIZATION BIAS | MENGISTU, TEWODROS E | 7d |
| 18496605 | QUALITY OF LABELED TRAINING DATA | GAVIN, KRISTIN ELIZABETH | 54d |
| 19297444 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS FOR CONFIGURABLE SEGMENTATION OF PRODUCT ASSORTMENTS | WHITE, DYLAN C | — |
| 19219759 | METHODS AND APPARATUS TO REDUCE SIGNAL-TO-NOISE RATIO (SNR) OF MONADIC SCORES | GAVIN, KRISTIN ELIZABETH | — |
| 19208300 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO MONITOR THE AVAILABILITY OF PRODUCTS FOR PURCHASE | OBEID, FAHD A | — |
| 19005736 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO CLASSIFY LABELS BASED ON IMAGES USING ARTIFICIAL INTELLIGENCE | SHAH, UTPAL D | — |
| 18932169 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO LABEL DATA | KASHYAPA, ANUSHA | — |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18496605 | QUALITY OF LABELED TRAINING DATA | GAVIN, KRISTIN ELIZABETH | 54d |
| 19297444 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS FOR CONFIGURABLE SEGMENTATION OF PRODUCT ASSORTMENTS | WHITE, DYLAN C | — |
| 19219759 | METHODS AND APPARATUS TO REDUCE SIGNAL-TO-NOISE RATIO (SNR) OF MONADIC SCORES | GAVIN, KRISTIN ELIZABETH | — |
| 19208300 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO MONITOR THE AVAILABILITY OF PRODUCTS FOR PURCHASE | OBEID, FAHD A | — |
| 19005736 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO CLASSIFY LABELS BASED ON IMAGES USING ARTIFICIAL INTELLIGENCE | SHAH, UTPAL D | — |
| 18967907 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO DECODE RECEIPTS BASED ON NEURAL GRAPH ARCHITECTURE | DUNPHY, DAVID F | — |
| 18658664 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO TRAIN MACHINE LEARNING MODELS USING SEMI-SUPERVISED SIGNALS | LU, HWEI-MIN | — |
| 18643794 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS FOR OBJECT-TO-OBJECT RECOMMENDATION USING LABEL PROTOTYPES AND SELF-ATTENTION | LEVEL, BARBARA HENRY | — |
| Art Unit | Apps |
|---|---|
| 3624 | 3 |
| 2142 | 2 |
| 3625 | 1 |
| 3627 | 1 |
| 2668 | 1 |
| 2673 | 1 |
| 2669 | 1 |
| 2122 | 1 |
| 2145 | 1 |
| 2127 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19297444 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS FOR CONFIGURABLE SEGMENTATION OF PRODUCT ASSORTMENTS | WHITE, DYLAN C | 3625 | §101DP | Non-Final OA | — | Pending | Aug 12, 2025 |
| 19219759 | METHODS AND APPARATUS TO REDUCE SIGNAL-TO-NOISE RATIO (SNR) OF MONADIC SCORES | GAVIN, KRISTIN ELIZABETH | 3624 | §101§103 | Non-Final OA | — | Pending | May 27, 2025 |
| 19208300 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO MONITOR THE AVAILABILITY OF PRODUCTS FOR PURCHASE | OBEID, FAHD A | 3627 | §101§102 | Non-Final OA | — | Pending | May 14, 2025 |
| 19005736 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO CLASSIFY LABELS BASED ON IMAGES USING ARTIFICIAL INTELLIGENCE | SHAH, UTPAL D | 2668 | §102§103§112Other | Non-Final OA | — | Pending | Dec 30, 2024 |
| 18967907 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO DECODE RECEIPTS BASED ON NEURAL GRAPH ARCHITECTURE | DUNPHY, DAVID F | 2673 | DP | Non-Final OA | — | Pending | Dec 04, 2024 |
| 18932169 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO LABEL DATA | KASHYAPA, ANUSHA | 2669 | §103§112 | Non-Final OA | — | Pending | Oct 30, 2024 |
| 18658664 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO TRAIN MACHINE LEARNING MODELS USING SEMI-SUPERVISED SIGNALS | LU, HWEI-MIN | 2142 | §112 | Non-Final OA | — | Pending | May 08, 2024 |
| 18643794 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS FOR OBJECT-TO-OBJECT RECOMMENDATION USING LABEL PROTOTYPES AND SELF-ATTENTION | LEVEL, BARBARA HENRY | 2142 | §101§112 | Non-Final OA | — | Pending | Apr 23, 2024 |
| 18399044 | METHODS AND APPARATUS TO PROFILE GEOGRAPHIC AREAS OF INTEREST | SMITH, BRIAN M | 2122 | §101§103DP | Non-Final OA | — | Pending | Dec 28, 2023 |
| 18496605 | QUALITY OF LABELED TRAINING DATA | GAVIN, KRISTIN ELIZABETH | 3624 | §101§103 | Final Rejection | 54d | Pending | Oct 27, 2023 |
| 18319891 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO IMPROVE ISOTONIC REGRESSION | MESFIN, MATTHEWOS | 2145 | §101§103 | Non-Final OA | — | Pending | May 18, 2023 |
| 18309325 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO REDUCE LONG-TAIL CATEGORIZATION BIAS | MENGISTU, TEWODROS E | 2127 | §101 | Final Rejection | 7d | Pending | Apr 28, 2023 |
| 17977967 | METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO PROVIDE VISUALIZATIONS OF VOLUME SHIFT ANALYSIS | HO, THOMAS Y | 3624 | §101§103 | Final Rejection | 9d overdue | Pending | Oct 31, 2022 |
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Start Free TrialNielsen Consumer LLC has 13 pending office actions as of October 2026, spread across 10 art units and 12 examiners.
Kristin Elizabeth Gavin has the most, with 2 of Nielsen Consumer LLC's pending office actions.
Mostly Transportation, E-Commerce & Mechanical Systems (USPTO Tech Center 3600), based on where its pending office actions are examined.