Product Analytics

The Wikimedia Foundation's Product Analytics team mainly supports teams within Audiences department, but also supports teams in other parts of the Foundation. The team helps product managers, engineers, and executives make data-informed decisions through:


 * Extracting insights and datasets from the Foundation's data repositories
 * Crafting key performance indicators (KPIs) and other metrics
 * Building dashboards for tracking success and health metrics
 * Design and analysis of experiments (A/B tests)
 * Ad-hoc analyses and machine learning projects
 * Developing tools and software for working with data

The team makes recommendations based on results of analyses, advocates for ethical data practices, and educates on topics around data and statistics.

Structure
Each analyst in embedded into one team, which means they participate in the team's day-to-day activities and discussions so that they can provide proactive analysis support. Each analysts are also assigned to additional teams and functional areas, which means they're the primary point of contact for requests from those teams, but generally don't join the team's day-to-day activities.

Depending on the team's capacity, it may also accept requests from others in the Wikimedia Foundation.

The team also reserves "10 percent time" to work on professional development. The team's manager is Kate Zimmerman, Head of Product Analytics, whose role involves prioritizing requests, managing capacity, and professionally developing members of the team.

Task management
We track our work in the Product-Analytics project on Phabricator. For our definitions of the task priority levels, see the project description.

Values
The Product Analytics team believes that in addition to professional expertise and personal experience, decisions should be supported by data and scientific rigor.

Who's on the team?



 * 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
 * Tilman Bayer, Senior Analyst
 * Ask me about: Experiment design, Hive/SQL, Wikimedia research literature, core reader metrics, Python for data analysis, SWAP, web analytics, traffic logs, EventLogging
 * Neil Patel Quinn, Product Analyst
 * Ask me about: Python for data analysis, SWAP, editor metrics, new editor research
 * Chelsy Xie, Data Analyst
 * Ask me about: R, search logs, traffic logs, eventlogging, Hive/SQL/Spark, experiment, machine/deep learning
 * 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)

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

See also meta:Research:FAQ

How to contact us

 * If there's someone specific you want to contact, refer to their individual user page.
 * Otherwise, use the mailing list: product-analytics@undefinedwikimedia.org