Product Analytics

About UsEdit

 
Monthly report on key Product metrics

Nurturing data-informed decision-making in Product since 2018-02-01.

Our Mission & ValuesEdit

We deliver quantitatively-based user insights to inform decision-making within the Foundation and the Wikimedia Movement in order to support Wikimedia’s strategic direction toward service and equity.

We strive to provide guidance, insights, and data that are:

Ethical The data we use are ethically sourced & applied.
Trusted Our analysis is reliable & valid. We clarify our level of certainty, flag issues if they arise, and provide caveats as needed.
Impactful We focus on providing insights that impact product development and organizational decisions.
Accessible Our colleagues can access the data they need and understand how to use it. Our guidance and insights are clear and digestible.
Inclusive Inclusivity and equity are fundamental moral imperatives.

In our daily work, we seek out diverse perspectives and abilities to strengthen the quality of our analysis.

Inspired We spark creativity through deep thought, collaboration, and fun!

Product Analytics primarily supports teams within Product, but we also support teams across the Foundation as well as community members in the Wikimedia Movement.

Our WorkEdit

  • Empowering others to make data-informed decisions through education and self-service analytics tools
  • Helping others set and track goals that are achievable and measurable
  • Helping set up Wikimedia products to collect useful data without harming user privacy
  • Ensuring that data collected is high-quality
  • Extracting insights from the Foundation's data repositories
  • Building dashboards and reports for tracking success and health metrics
  • Designing and analyzing experiments (A/B tests)
  • Doing ad-hoc analyses and machine learning projects
  • Developing tools and software for working with data, in collaboration with Analytics Engineering and Product Analytics Infrastructure.
  • Helping others work with teams like Analytics Engineering, Security, and Legal to address data-related issues

Product Team SupportEdit

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.

Analyst Point person for...
Connie Self-Service Reporting & High-Level Metrics
Jennifer Anti-Harassment Tools & Community Tech
Maya Data Quality & Reporting
Megan Web & Editing
Mikhail Product Analytics Infrastructure
Morten Growth & Multimedia
Neil Language & Inuka
Shay Android & iOS

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.

The team's manager is Kate Zimmerman, Head of Product Analytics, who is responsible for developing an overall strategy for product analytics, prioritizing requests, managing capacity, and professionally developing members of the team.

Who's on the team?Edit

 
Kate
 
Maya
 
Megan
 
Mikhail
 
Morten
 
Neil

Listed alphabetically by first name within each section

LeadershipEdit

  • Kate Zimmerman, Head of Product Analytics
    • Leading Better Use of Data program
    • Ask me about: Collaborating with Product Analytics, using data to inform product and business decisions, experiment design, decision science, applied stats

Team MembersEdit

  • Connie Chen, Data Analyst
    • Ask me about:
  • Jennifer Wang, Data Analyst
    • Ask me about: AHT/Comm tech metrics
  • Maya Kampurath, Data Quality Analyst (Contractor)
    • Ask me about:
  • Megan Neisler, Analyst
    • Ask me about: R, data visualization, reader metrics, technical writing
  • Mikhail Popov, Data Analyst
    • Ask me about: R, data visualization, search logs, traffic logs, Hive/SQL, Bayesian statistics, machine/deep learning, Bayesian networks & influence diagrams, time series analysis, Google Search Console
  • Morten Warncke-Wang, Data Analyst
    • Ask me about: R, machine learning, spatial (geographic) models, article quality, editor/editing/newcomer metrics, prior research on Wikipedia, and perhaps also time-series modeling (forecasting)
  • Neil Shah-Quinn, Product Analyst
    • Ask me about: Python for data analysis, SWAP, editor metrics, new editor research
  • Shay Nowick, Data Analyst
    • Ask me about: Mobile metrics, Pydata and Jupyter Notebooks, cohort analysis

Honorary MembersEdit

  • Irene Florez, Data Analyst (Contractor)
    • Ask me about
  • Jason Linehan, Software Engineer
    • Ask me about: programming languages other than R, analytics infrastructure, randomness
  • Lani Goto, Technical Program Manager
    • Ask me about: team process, meetings, coordinating cross-team projects

How can I get help with data or analysis?Edit

Submitting RequestsEdit

Please submit a ticket through Phabricator; our Product Analytics board has details and a template for submitting requests.

For Foundation members who are not familiar with Phabricator, please submit a request using our Google form for Analytics Requests: https://forms.gle/v4CFYHKUdH7J4Vn47.

Office HoursEdit

Analysts host weekly office hours (details). Click here to view the calendar or schedule an appointment.

Data FAQsEdit

See meta:Research:FAQ

How to contact usEdit

  • Contact information for team members are available on their user pages (linked above).
  • Group mailing list: product-analytics wikimedia.org

Data references, best practices, and reportsEdit

Documentation for tools we useEdit

  • Phabricator (managing requests and tracking work)
  • Superset (WMF internal dashboards and reports)
  • Turnilo (WMF internal tool for pivoting and exploring data)
  • Event Platform (Various event stream distribution and processing systems we employ at WMF)
  • Piwik/Matomo (JavaScript tracking client used for wikimediafoundation.org and other smaller-scale sites)

Team referencesEdit