Product Analytics
Product Analytics
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The Wikimedia Foundation's Product Analytics team has nurtured data-informed decision-making in the Product department since February 2018.
Our Mission & Values
[edit]We deliver quantitatively-based user insights to inform decision-making in support of Wikimedia's strategic direction toward service and equity.
We strive to provide guidance, insights, and data that are:
Ethical • Trusted • Impactful • Accessible • Inclusive • Inspired
What we do
[edit]Product Analytics contributes to the Wikimedia Movement through our work with Product teams and departments across the Foundation.
Our responsibilities include:
- Empowering others to make data-informed decisions through education and self-service analytics tools
- Helping set and track goals that are achievable and measurable
- Ensuring that Wikimedia products collect useful, high quality data without harming user privacy
- Extracting insights through ad-hoc analyses and machine learning projects
- Building dashboards and reports for tracking success and health metrics
- Designing and analyzing experiments (A/B tests)
- Developing tools and software for working with data, in collaboration with Data Engineering and Product teams.
- Addressing data-related issues in collaboration with teams like Data Engineering, Security, and Legal
Who is on the team
[edit]Listed alphabetically by first name within each section
Product Analytics is part of the Research and Decision Science group, led by Kate Zimmerman, Senior Director of Decision Science.
Team Leadership
[edit]- Mikhail Popov, Data Science Manager
Team Members
[edit]- Connie Chen, Sr. Data Scientist
- Irene Florez, Data Scientist III
- Jennifer Wang, Staff Data Scientist
- Krishna Chaitanya Velaga, Data Scientist III
- Megan Neisler, Staff Data Scientist
- Morten Warncke-Wang, Staff Data Scientist
- Shay Nowick, Sr. Data Scientist
Product team support
[edit]Analyst | FY24–25 | FY23-24 Embedded in… |
---|---|---|
Connie | De-embedded | Structured Content |
Irene | De-embedded | Campaigns-Product
Trust and Safety Product (Incident Reporting System, limited capacity) Wikipedia ChatGPT-plugin and other Future Audiences experiments |
Jennifer | Part-time embedded in Web
Supporting Temporary Accounts (formerly IP Masking) |
Trust and Safety Product (IP Masking) |
Krishna Chaitanya | Part-time embedded in Language and Product Localization (LPL) during Q1 while wrapping up support for Automoderator project.
Full-time embedded in LPL for the remainder of the fiscal year. |
Language
Community-Tech (limited capacity) |
Megan | Part-time embedded in Editing | Editing |
Morten | De-embedded
Supporting Metrics Platform |
Growth |
Shay | Full-time embedded in Wikimedia (Mobile) Apps | Wikimedia Apps |
Team references
[edit]- Team mission and values
- Team norms
- Glossary
- Data products (various deliverables such as reports, analyses, and datasets)
- Working with Product Analytics
- Chore Wheel
- Onboarding notes for new team members
- Research and Decision Science documentation and materials for new data practitioners
- Includes guidelines, best practices, documentation on tools we use
- Offboarding
- Contingency Carousel
- Fun
All sub-pages of Product Analytics
[edit]- Chore Wheel
- Comparison datasets
- Consultation Hours
- Contingency Carousel
- Dashboarding Guidelines
- Data products
- Data products/fawiki metrics summary
- Data products/ptwiki intervention impact report
- Data products/ptwiki metrics summary Jun2022
- Event Platform recommendations
- Event logging
- Fun
- Glossary
- Mission and Values
- Movement metrics
- Offboarding
- Offsites
- Offsites/2018-11-Onsite
- Onboarding
- Reporting Guidelines
- Style guide
- Superset Access
- Team norms
- Wiki comparison suggestions
- Working with Product Analytics