
Over nine months, D. Berry engineered robust experimentation and analytics infrastructure in the mozilla/metric-hub and mozilla/bigquery-etl repositories, focusing on data-driven product improvements. Berry designed and implemented TOML-configured A/B tests, telemetry enhancements, and SQL-based analytics pipelines to support onboarding, feature adoption, and cross-platform engagement measurement. Leveraging Python, SQL, and TypeScript, Berry expanded metrics coverage, improved data integrity, and enabled granular segmentation for experiments across Firefox platforms. The work included developing Glean-based telemetry, refining experiment configuration management, and authoring technical documentation, resulting in maintainable, extensible systems that empower teams to make informed decisions through reliable, actionable data and streamlined experimentation cycles.

In August 2025, mozilla/metric-hub delivered targeted analytics improvements and multi-region experiment instrumentation, strengthening data-driven decision making around tab groups and sign-in UX. The work expanded measurement scope, enabled richer segmentation, and extended data collection windows to support robust analysis of user engagement. No major bugs were documented in this period; momentum was maintained through well-scoped configurations and instrumentation across AU and IN regions, with clear artifacts for ongoing experimentation and data reuse across future cycles.
In August 2025, mozilla/metric-hub delivered targeted analytics improvements and multi-region experiment instrumentation, strengthening data-driven decision making around tab groups and sign-in UX. The work expanded measurement scope, enabled richer segmentation, and extended data collection windows to support robust analysis of user engagement. No major bugs were documented in this period; momentum was maintained through well-scoped configurations and instrumentation across AU and IN regions, with clear artifacts for ongoing experimentation and data reuse across future cycles.
July 2025 — Delivered two key feature experiments in mozilla/metric-hub that drive measurable improvements in data collection and engagement analysis. Implemented enrollment data collection for the desktop-credit-card autofill global enablement holdback experiment via a TOML-configured query, and refined the data analysis scope by adjusting the date range and event tracking. Added new user activity segments for the Whats-new notification tab groups experiment to enhance targeting and insights into engagement with tab-group features. Impact: enables more accurate measurement of autofill adoption across global users and supports data-driven rollout decisions; improves segmentation-driven analytics for product engagement. Tech stack and skills demonstrated: TOML-configured data collection, experiment instrumentation, event tracking, and segmentation analytics.
July 2025 — Delivered two key feature experiments in mozilla/metric-hub that drive measurable improvements in data collection and engagement analysis. Implemented enrollment data collection for the desktop-credit-card autofill global enablement holdback experiment via a TOML-configured query, and refined the data analysis scope by adjusting the date range and event tracking. Added new user activity segments for the Whats-new notification tab groups experiment to enhance targeting and insights into engagement with tab-group features. Impact: enables more accurate measurement of autofill adoption across global users and supports data-driven rollout decisions; improves segmentation-driven analytics for product engagement. Tech stack and skills demonstrated: TOML-configured data collection, experiment instrumentation, event tracking, and segmentation analytics.
Monthly performance summary for 2025-06 focusing on delivering telemetry enhancements for Firefox Desktop, reinforcing data governance, and enabling richer analytics through Glean.
Monthly performance summary for 2025-06 focusing on delivering telemetry enhancements for Firefox Desktop, reinforcing data governance, and enabling richer analytics through Glean.
Delivered New Toolbar iOS redesign Experiment (Iteration 1) in mozilla/metric-hub, configuring an A/B/n test named 'new-toolbar-ios-ios-redesign-iteration-1' with three weekly enrollment segments and data sources, including extraction of client IDs and enrollment dates from the event stream to quantify engagement during the experiment windows. No major bugs fixed this month. This work advances measurement-driven rollout decisions and strengthens instrumentation for iOS toolbar experiments.
Delivered New Toolbar iOS redesign Experiment (Iteration 1) in mozilla/metric-hub, configuring an A/B/n test named 'new-toolbar-ios-ios-redesign-iteration-1' with three weekly enrollment segments and data sources, including extraction of client IDs and enrollment dates from the event stream to quantify engagement during the experiment windows. No major bugs fixed this month. This work advances measurement-driven rollout decisions and strengthens instrumentation for iOS toolbar experiments.
March 2025: Feature delivery and documentation improvements across two repos, enabling advanced experiment design and dot-release targeting for desktop experiments. Key outcomes include detailed preenrollment bias and covariate adjustment docs and Fx 136.0.2 targeting support, with related GraphQL/TypeScript and Docusaurus updates.
March 2025: Feature delivery and documentation improvements across two repos, enabling advanced experiment design and dot-release targeting for desktop experiments. Key outcomes include detailed preenrollment bias and covariate adjustment docs and Fx 136.0.2 targeting support, with related GraphQL/TypeScript and Docusaurus updates.
February 2025 monthly summary for mozilla/bigquery-etl focused on ToS rollout analytics across Firefox platforms. Delivered new SQL views and metadata to monitor Terms of Service rollout enrollments across Fenix, Desktop, and iOS. Implemented derived tables to extract client_id, submission_timestamp, experiment_slug, and branch from event streams to enable tracking and analysis of ToS rollout experiments. This work was implemented as a single commit.
February 2025 monthly summary for mozilla/bigquery-etl focused on ToS rollout analytics across Firefox platforms. Delivered new SQL views and metadata to monitor Terms of Service rollout enrollments across Fenix, Desktop, and iOS. Implemented derived tables to extract client_id, submission_timestamp, experiment_slug, and branch from event streams to enable tracking and analysis of ToS rollout experiments. This work was implemented as a single commit.
January 2025 monthly summary for mozilla/metric-hub. This period focused on expanding telemetry coverage and experimentation capabilities through TOML-configured instrumentation, with emphasis on cross-device usage, onboarding cohorts, and promotional campaigns. Key outcomes include cross-device sign-in metrics on Windows, desktop-to-mobile adoption tracking, Jetstream multi-action CTA pin-tracking, extended onboarding observation windows, and onboarding add-ons promotions.
January 2025 monthly summary for mozilla/metric-hub. This period focused on expanding telemetry coverage and experimentation capabilities through TOML-configured instrumentation, with emphasis on cross-device usage, onboarding cohorts, and promotional campaigns. Key outcomes include cross-device sign-in metrics on Windows, desktop-to-mobile adoption tracking, Jetstream multi-action CTA pin-tracking, extended onboarding observation windows, and onboarding add-ons promotions.
December 2024 (Month: 2024-12) — Focused on data quality, experiment enablement, and telemetry robustness in mozilla/metric-hub. Delivered a data integrity fix for enrollment tracking and launched TOML-configured experiments to support controlled onboarding optimization, private-browsing VPN usage analysis, and account spotlight telemetry. These efforts increase metric accuracy, accelerate experimentation cycles, and provide actionable insights for product decisions.
December 2024 (Month: 2024-12) — Focused on data quality, experiment enablement, and telemetry robustness in mozilla/metric-hub. Delivered a data integrity fix for enrollment tracking and launched TOML-configured experiments to support controlled onboarding optimization, private-browsing VPN usage analysis, and account spotlight telemetry. These efforts increase metric accuracy, accelerate experimentation cycles, and provide actionable insights for product decisions.
Month 2024-11 — Mozilla Metric Hub delivered 7 cross-platform experiment configurations and telemetry enhancements to accelerate data-driven improvements in onboarding, recommendations, import behavior, and the sync/backup value proposition. Key outcomes include expanded telemetry metrics (addon counts/installations, staff picks metrics using clients_daily data, import rates, pinned tabs events including pinning, concurrent pins, reloads), reorganization of experiment configurations for maintainability (moving configs out of outcomes folder and updating pinning metrics), and targeted onboarding experiments for iOS, Android, and Windows. These changes enable faster experimentation cycles, clearer data signals, and stronger business value around user activation, feature adoption, and data-informed product decisions. Notable commits include 57afab786fb16e9b02e0f408e7b67a94601d50d4, ed372dcd86f7f760e6634eb69292353ecff86726, 0d1cb76b2d46137210c538f8c4b5de1cee9d29be, 1439bd18307b8715703aeda92318c3ab1e81973f, 5727588576470ea8feabf301a0a9ed34bf579d35, 5cb62a8fb9b26936484187b0a39cd3440d29211a, 8abcf8a3b48e5d06578374e6002b96f0d494dd7b, 2f6d0e7dff836ec7e9c20f695de6054332810e4d
Month 2024-11 — Mozilla Metric Hub delivered 7 cross-platform experiment configurations and telemetry enhancements to accelerate data-driven improvements in onboarding, recommendations, import behavior, and the sync/backup value proposition. Key outcomes include expanded telemetry metrics (addon counts/installations, staff picks metrics using clients_daily data, import rates, pinned tabs events including pinning, concurrent pins, reloads), reorganization of experiment configurations for maintainability (moving configs out of outcomes folder and updating pinning metrics), and targeted onboarding experiments for iOS, Android, and Windows. These changes enable faster experimentation cycles, clearer data signals, and stronger business value around user activation, feature adoption, and data-informed product decisions. Notable commits include 57afab786fb16e9b02e0f408e7b67a94601d50d4, ed372dcd86f7f760e6634eb69292353ecff86726, 0d1cb76b2d46137210c538f8c4b5de1cee9d29be, 1439bd18307b8715703aeda92318c3ab1e81973f, 5727588576470ea8feabf301a0a9ed34bf579d35, 5cb62a8fb9b26936484187b0a39cd3440d29211a, 8abcf8a3b48e5d06578374e6002b96f0d494dd7b, 2f6d0e7dff836ec7e9c20f695de6054332810e4d
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