Product Analytics
The Wikimedia Foundation's Product Analytics team has nurtured data-informed decision-making in the Product department since February 2018.
Product Analytics
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Our Mission & Values
editWe 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
editProduct 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
editListed 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
editAnalyst | 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