Nurturing data-informed decision-making in Product since 2018-02-01.
Our Mission & Values
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
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
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.
- Mikhail Popov, Data Science Manager
- Connie Chen, Sr. Data Scientist
- Irene Florez, Data Scientist III
- Jennifer Wang, Staff Data Scientist
- Krishna Chaitanya Velaga, Data Scientist III
- Megan Neisler, Sr. Data Scientist
- Morten Warncke-Wang, Staff Data Scientist
- Shay Nowick, Sr. Data Scientist
Product Team Support
Each analyst is a point person for a team, project, or program. Our goals are to maintain context and domain knowledge while also allowing for flexibility in analyst work assignments. For more information about how we work with Product teams, see Working with Product Analytics.
|Analyst||FY23-24 Point person for…|
Trust and Safety Product (Incident Reporting System, limited capacity)
|Jennifer||Trust and Safety Product (IP Masking)|
Community-Tech (limited capacity)
|Maya||(Moved to Movement Insights team)|
|Neil||(Moved to Movement Insights team)|
Teams that do not currently have an assigned point person are encouraged to submit requests through Phabricator. Depending on the team's capacity and organizational needs, we may also accept requests from others in the Wikimedia Foundation. The team reserves "10 percent time" to work on professional development.
How to get help with data or analysis
If you'd like to request data, analysis, or advice, create a task in Phabricator or send an email to email@example.com.
Requests are reviewed by Product Analytics and inform the direction and priorities of data projects. A team member will follow up about whether we’ll be able to work on your request.
Some questions may be suited to consultation hours; see Product Analytics Consultation Hours for more information and a link to book appointments.
Provide the following information to help us prioritize and respond to your request appropriately:
- Name for main point of contact and contact preference
- We use Phabricator to track our work and provide progress updates. Please let us know if you would like us to follow up by other methods (e.g. email).
- What teams or departments is this for?
- This helps us understand who will be using the analysis.
- What are your goals? How will you use this data or analysis?
- This helps us understand the context and priority. What decisions do you need data to inform? Will you take different actions depending on the direction of the data? Do you want to share data publicly? Do you want to include data in a narrative or message (e.g. for PR, audience engagement, or fundraising)?
- What are the details of your request? Include relevant timelines or deadlines
- Is there a date after which the analysis will no longer be useful? Please provide any timeline/relevant deadlines, requested formats, examples, links to documentation, or other information that would help us understand your request.
- Is this request urgent or time sensitive?
- We try to reply to “Urgent” requests immediately and “Time sensitive” requests by the end of the workday. All other requests will be prioritized during our weekly triage.
Note: We use Phabricator to track our work, and by default tickets are publicly visible. If any part of your request is sensitive and should be kept confidential, let us know.
How to contact us
- Contact information for team members are available on their user pages (linked above).
- Group mailing list: product-analyticswikimedia.org
Data references and reports
- Comparison datasets
- Data Dictionary (documents data sources, such as those available in Superset and Turnilo)
- Data Glossary (definitions for core and other essential metrics)
- Data Products (various deliverables such as reports, analyses, and datasets)
- Movement metrics
- ETL jobs
Guidelines and best practices
Documentation for tools we use
- Phabricator (managing requests and tracking work)
- Superset (WMF internal dashboards and reports)
- Obtaining access to Superset/Turnilo, with explanation of LDAP/Developer Account terminology
- Turnilo (WMF internal tool for pivoting and exploring data)
- Event Platform (Various event stream distribution and processing systems we employ at WMF)
- Wikimedia Infrastructure
- Google Search Console access