Research:Optimizely Fundraiser Analysis
- Ryan Faulkner
- Dan Siroker
Using Optimizely software to analyze WMF Fundraiser data. Dan Siroker expressed some interest to analyze WMF fundraiser data. This could include de-deuping the data and performing A/B testing of visitors falling into different sub-groups (e.g. number of banners seen, types of banners seen etc.)
Data is to be prepared for general consumption by researchers with IP information anonymized (implementation is being discussed with Roan Kattouw). The WMF will publish this data on the data dumps server (dumps.wikimedia.org). The data will be sourced from 1) WMF squid server request logs and 2) donations from our donor database. This data is to be processed into the following three forms based on table schemas that define the anonymized data:
Banner Impressions - ip_hash, banner, article_hash, browser, country, language, request_time
Landing Page Impressions - ip_hash, banner, utm_campaign, utm_medium, landing_page, article_hash, browser, country, language, project, request_time
Donations - ip_hash, banner, utm_campaign, utm_medium, landing_page, donated amount, timestamp
This data, after careful review, will be made publicly available for use by external researchers on dumps.wikimedia.org.
Specific methods to be used by Dan Siroker have not yet been determined however, the software that may be used to analyze WMF Fundraiser data may be found at the Optimizely Homepage.
The WMF will publish this data on the data dumps server (dumps.wikimedia.org). Prior to this a review process will be setup to determine that the privacy constraints for publication are met.
Wikimedia Policies, Ethics, and Human Subjects Protection
All data published to dumps.wikimedia.org will be stripped of any fields that may be used in personally identifying any donors or readers that are the source point of the server impressions and donation records held by the WMF. This request has been reviewed by WMF departmental resources from Community, Engineering, and Legal.
Benefits for the Wikimedia community
Potential Analysis that will aid in making the WMF annual fundraiser more efficient. This could include:
- Improvement of A/B testing methods to increase efficiency of campaign testing
- Sensitivity of conversion metrics to duplicate requests for visitors
- Learning about donor and reader behaviours based on user-experience (banner views, types of articles visited etc.)
This is a volunteer project. Resources for pre-processing the data for public consumption will be provided internally by WMF staff accounted for under the 2010/2011 annual budget.
Dan Siroker - email@example.com
Ryan Faulkner - firstname.lastname@example.org