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Wikimedia Foundation Annual Plan/2018-2019/Audiences

This page describes the five programs proposed in the 2018–2019 annual plan for the Audiences department in the Wikimedia Foundation. A Changelog of all non-format changes made since June 27th, 2018 sits at the bottom. If you update this page, please describe that change in the changelog.

Contents

New ContentEdit

Better content through productive contributions by retaining new contributors with more diverse interests, capabilities, languages, and geographies.

Activity type: Programmatic activities

Teams contributing to the program: Editing, Readers Web, iOS + Android, Growth, Language

Goals, Outcomes, and Outputs for New ContentEdit

Annual Plan FY18-19 topline goals: Knowledge Equity – grow new contributors and content

How does your program affect the annual plan topline goal? By lowering known technical and cultural barriers to participation, particularly those formed by geographic, lingual or economic distinctions, we enable a broader spectrum of people to contribute effectively and create greater equity in the knowledge creation process.

Program goal: Better content through productive contributions by retaining new contributors with more diverse interests, capabilities, languages, and geographies

High-level metrics:

  • Increase in new contributor retention rate on target wikis by 10%.
  • Increase rate of new article creation on target wikis by 10%.
Outcomes for New Content program

Outcome 1: Progressive OnboardingEdit

A richer suite of onboarding tools will help new contributors learn about wiki rules, tools and practices, decreasing friction and helping contributors to be less confused and more successful in their early days on the wiki.

We believe that onboarding challenges are a barrier that don’t just limit retention, but specifically and artificially limit the kinds of people who can contribute and the quality of their contributions.

This will increase retention of new contributors in the target wikis, Czech and Korean Wikipedias.

Output 1.1: Human-to-human help
Primary team: Growth

Develop a human-to-human help area on two medium-sized wikis (Czech and Korean Wikipedias), using lessons learned from similar efforts on larger wikis. The focus will be on helping new contributors to overcome early challenges.

In the early stages of this project, the team will be learning from the editors who work on existing successful help areas on the larger projects, including the Teahouse on English Wikipedia, and the Forum des nouveaux on French Wikipedia. The team will be able to offer some improvements to existing programs if needed, and then work with existing editors in two medium-sized wikis to establish new help areas.

Work on this project will also pay attention to the kind of support and feedback that experienced question-answer-ers need, to continue offering help.

Metrics:

  • Mentor retention on target wikis
  • New contributor retention on target wikis

Dependencies:

  • Research, to help with evaluations of current projects and the team’s work
  • Ambassadors on Czech and Korean WP
Output 1.2: Movement Organizers study
Primary team: Design Research

Movement organizers are fundamental implementers of the Wikimedia movement direction, allowing best practices and capacity to grow within the movement -- a core asset necessary for sustaining and growing the movement. Understanding of movement organizers allows the Community Engagement department to better align to support this group, for Community Engagement and Audiences departments to better understand how to work together on future projects that support this audience, and a shared framework for making strategic investments in support for that audience. This project will be part of a multi-year arc of work, which develops competency within the Wikimedia Foundation for addressing the needs of this vital programmatic audience.

The goal of this study is to develop a shared understanding of and investment in the needs of movement organizers at the Wikimedia Foundation and in the Wikimedia movement, to ensure that this strategic audience gets the support it needs to grow the Wikimedia communities.

The milestone for this project will be a public report on the research findings, including movement organizers personas to inform future work in community outreach and software development. The report will offer recommendations for further work to help movement organizers to succeed.

Dependencies:

  • Design Research
  • Community Engagement
Output 1.3: Measuring Contributor Diversity
Primary team: Web

Support the Research team's goal of providing baseline statistics on contributor diversity in one or more Wikimedia projects via extension of Quick Surveys feature to enable direct polling of logged in users.

Target: Baseline statistics on contributors demographics

Dependency: Close collaboration with Research Team

Outcome 2: CommunicationEdit

The ability to communicate with other editors is essential to successful on-wiki collaboration. The lack of a clear user interface for communication features is a significant barrier for new users taking part in productive discussions. Learning how to use a complicated communication feature should not be an entrance exam for contributors. We believe that making these tools more accessible to people with different levels of wiki knowledge will help experienced contributors to communicate and work productively with new contributors.

Metric: Long-term retention of contributors, but we don't expect this to change this year.

Output 2.1: “Fix talk pages” consultation
Primary team: Contributors

The Foundation has been developing a Structured Discussions feature (aka Flow) since 2013. It is working well for some use cases on some large and medium-sized wikis, but some users on some of the largest wikis have been telling us for years that the strategy we’ve been pursuing will not work for their communities. To make progress on our long-term movement strategy, we need to develop an improved communication system for all of our wikis, including the largest projects.

This year, we will hold a large-scale consultation that involves both large and medium-sized wikis on the future of the on-wiki communication system. This will require starting from the beginning—identifying problems with the existing system, and building consensus for a solution, or set of solutions. This process may lead to a system similar to Structured Discussions, or it may lead in a different direction. We may find that it’s not necessary to have a single, unified system for all use cases, and the best strategy may be to develop several different communication features. We need to commit to a sincere and transparent consultation process that is not weighted towards reaching a predetermined goal. This will be a difficult, high-investment partnership with our communities, and a necessary one for us to make progress toward developing a more workable on-wiki communication system.

Dependencies:

  • Data analysis
  • Design research
  • Community Liaisons
  • Design

Outcome 3: Mobile ContributionEdit

It is easier for someone to contribute productively to Wikimedia projects on a mobile device, leading to more mobile edits and higher retention.
  • Mobile contributor retention rate on target wikis
  • Mobile edit rate on target wikis
  • Mobile edit revert rate’s increase is manageable

Tying it back to our goal: We believe that mobile device usage is crucial to retention of contributors in underrepresented languages and countries.

Output 3.1: Contribution tools on mobile web via an existing mediawiki skin
Primary team: Reading Web

Expanding contribution workflows on an existing skin will provide a quick way to increase the amount of productive mobile contributions. It will also allow the full breadth of tools in a short timespan, giving us more time to do thorough research and design for the most crucial workflows.

Existing contributors can optionally access contribution tools on mobile web. A responsive skin including desktop features should make all on-wiki contribution and curation features, as well as the most widely used administrative tools, usable (though not optimized) on mobile web.

While this work is not intended to benefit new contributors directly, it sets the stage for having an advanced experience for advanced contributors (<0.1% of users) separate from the basic/onboarding experience for readers and new contributors (>99.9% of users).

Metrics/Target:

  • Mobile web edit rate on target wikis 10% increase
  • Retention rate for opt-in advanced mobile mode amongst medium and high-volume editors (100+ edits previous month) At least 60% retention
  • Moderation actions on mobile web on target wikis 10% increase

Dependencies:

  • Community Liaisons
  • Editing team
Output 3.2: Mobile for existing contributors
Primary team: iOS

The iOS team will begin development of contribution features of the app, starting with features that already exist in incomplete form, overlap with Readers needs, or otherwise are more easily adapted from the web. We will also work with design research to define a longer term roadmap for key workflows, with the focus on Wikipedias which have high levels of iOS use, and evident interest in app related contribution (examples could include South Korean, Swedish, Catalan, etc).

Given the scales involved, and the fact that most iOS users are in high awareness markets, it is unlikely this will increase overall rates of new contributor retention or more diverse content. It is necessary preliminary work, though, and foundational to more sophisticated interventions, which could follow and be adapted to the web when practical.

This work will begin our understanding and planning for contributing in a multi-client stack. It will provide high-quality interaction and design patterns which other teams can use as they work on similar communication channels.

Metrics/Target:

  • Working new contribution feature on iOS
  • iOS contributor retention rate on target wikis 10% increase
  • iOS edit rate on target wikis 10% increase

Dependencies:

  • Community Liaisons
  • Design research
  • Reading Infrastructure
Output 3.3: Research-driven mobile contribution for new contributors
Primary team: Android

Description:

Development of contribution features in the Android app, focusing on those tasks that suit a mobile context – e.g., short translations, typos, adding media, etc. – and also on those tasks where contributors report they do not need multiple windows or a long workflow to accomplish the tasks. Essentially, wherever we can best add value as a mobile app, rather than trying to shoehorn in unsuitable workflows. This necessitates working with design research to define a longer term roadmap for key workflows, with the focus on wikis which have high levels of Android use, and evident interest in app-based contribution.

The hypothesized long term impact is activation and retention of contributors on Android in emerging markets – people whose main source of internet access is their phone, for which contribution tools are not currently optimized. The shorter-term proposition engaging the current communities of contributors around tasks they want to perform on the go (tying into what the iOS team is doing), with the added benefit of introducing more people in existing markets to low-context forms of editing.

Metrics/Target:

  • Working new contribution feature on Android
  • Android new editor rate on target wikis 10% increase
  • Android contributor retention rate on target wikis 10% increase
  • Android edit rate on target wikis 10% increase

Dependencies:

  • Community Liaisons
  • Design research
  • Reading Infrastructure
Output 3.4: Simpler editing on mobile web + apps
Primary team: Editing

Report on current state and define acceptance criteria. Specifically define whether new contributors can use the existing version of VisualEditor on mobile web, understand the social problems around making visual-based editing the default across wikis for mobile editors, and the potential cost and feasibility of mobile native editing. The initial milestone will be an on-wiki report on the current state and potential future options for consideration and discussion by communities and Foundation leadership, with specific work to follow based on the outcomes of that report and consultation.

Metrics:

  • Number of edits per period via mobile visual editing feature(s) 10% increase
  • Number of edits per period via mobile visual editing feature(s) from newer editors (first 6 months after registration) 10% increase
  • Number of editors per period using mobile visual editing feature(s) 10% increase

Dependencies:

  • Community consultations about goals and acceptance criteria
  • Design: UX research
  • App team: performance testing & feasibility of using VE
  • Editing team: performance testing & feasibility

Outcome 4: Local Language ContentEdit

There is more coverage of topics in non-English languages, due to higher rate of non-deleted new articles in local languages.
Output 4.1: Content translation
Primary team: Language

Remove the main points of friction that new contributors encounter when translating, such as dealing with infoboxes, references, abuse filter errors and existing content in the page. This will be driven primarily via finalizing integration with VE. Stabilize, graduate out of beta to expose to more users, and add minimal support for a translation bookmarking system for active translators to keep track of articles that they plan to translate later.

Metrics:

  • Rate of new article creation on target wikis 10% increase
  • New editor success rate with content translation tool Increases
  • Surviving translated article rate Increases

Dependencies:

  • This depends on the in-progress integration of Visual Editor as the editing surface and overall completion of the rewritten version of Content Translation to be at par with the current features in use.
  • Community Liaisons
Output 4.2: Improve Translate extension & translatewiki.net process
Primary team: Language

Review and audit i18n core libraries (and tools) in/connected with MediaWiki core and extensions, with the intention to prepare a maintenance (and expansion) plan for the rest of the fiscal year. Preliminary focus on Translate extension and translatewiki.net process enhancements, using the i18n wishlist as a guide.


Metrics:

  • The number of open maintenance issues related to Translate Extension & translatewiki.net is reduced quarter on quarter
  • The number of open maintenance issues related to general i18n support is reduced quarter on quarter

Targets for New ContentEdit

Outcomes Targets Measurement methods
1 Onboarding

New contributor retention rate will increase.

10% above current rate in target wikis Standard retention metric reported here: mw:Wikimedia Audiences#Contributors
2 Communication

New contributor retention rate will increase.

10% above current rate in target wikis Standard retention metric reported here: mw:Wikimedia Audiences#Contributors
3 Mobile Contribution

It is easier for someone to contribute productively to Wikimedia projects on a mobile device, leading to more mobile edits and higher retention.

  • Mobile contributor retention rate increases 10% in target wikis
  • Number of mobile edits increases 10% in target wikis
  • Mobile edit revert rate increase is "manageable" in target wikis
Edit tables
4 Local language content

There is more coverage of topics in non-English languages.

10% higher rate of new articles in target wikis Number of articles in language as a function of time

Please see the New Content Program metrics reports page for updated metric reports showing progress towards these targets.

Better Use of DataEdit

A more reliable, efficient and accessible means of collecting, interpreting and sharing data

Program page

Activity type: Programmatic activities

Teams contributing to the program: All Audiences teams, with particular focus by product managers and product analysts, and in partnership with Analytics Engineering.

Goals, Outcomes, and Outputs for Better Use of DataEdit

Annual Plan FY18-19 topline goals: Knowledge as a Service/Foundational Strength – evolve our systems and structures

How does your program affect the annual plan topline goal? There is widespread desire among both the teams and their stakeholders to have more data, and to make better use of quantitative data in decision making and communication. This program will make improvements to our systems and structures for the effective collection, storage, analysis and sharing of data a top level goal across the Audiences department.

Program Goal: This program’s goal is to make the use of quantitative data for decision making and communication a more effective and integral part of our department’s systems and processes. Completing this program will result in more evidence based decision making at a feature team level, a better check on key indicators at the system level and much more cost effective analysis and sharing of data.

Outcome 1: Assess and communicate needsEdit

The Technology team, and particularly Analytics Engineering will have a clear understanding of the data collection, storage, analysis and communication needs of the Audiences department, and the two departments will have improved mutual understanding of which teams will work on these areas in the future.
Output 1.1: Data consumer gap analysis
Identify the set of challenges that impede the Audiences department from data-driven decision making. List the specific needs of the Audiences team for data collection and deliverable creation, written as requirements for technology changes and additions. Include needs around instrumentation, controlled experiments, data access, and visualization capabilities. In addition to technology changes, also identify any needed process improvements.
Output 1.2: Reporting technology evaluation
Assemble a document with a deep dive into the visualization capabilities needed by Audiences product managers and product analysts, evaluating different technology options and their pros and cons.

Outcome 2: Define responsibilitiesEdit

The human processes that are critical to data-driven decision making will have clearly defined owners and participants, helping ensure that all measurement priorities are accomplished efficiently and without confusion. This includes clear roles and responsibilities for the reporting of program metrics, as well as the cross-team stewardship of data policies.
Output 2.1: Measurement expectations
Audiences management will work with each product team to agree on the specific metrics that they should be reporting on, so that all high-level health metrics and granular project metrics are tracked and surfaced to stakeholders. To support this, Audiences will develop and deploy a training curriculum on data best practices, and management will set expectations of how Audiences teams should use data for reporting and decision making.
Output 2.2: Data stewardship
Responsibility for data-related policies and decisions is currently distributed and unclear, causing delays and conflict in measurement processes. Using a DACI model, Audiences will identify roles and/or create working groups to own responsibility for the following data policies and decision areas:
  • Definitions: ensuring consistency around the specific definitions of our most important metrics.
  • Usage: ensuring that data is documented, labeled, described, and stored such that it can be used by those that need it.
  • Quality: ensuring that our most widely used datasets are of consistent quality for their multiple uses.
  • Governance: ensuring that data elements are accessible by the appropriate people.
  • Privacy: ensuring that data is collected and used in ways that are compliant with our policies.

Outcome 3: Data collectionEdit

Reduced cost of collecting data on program metrics and on the feature usage that supports those metrics. New features and products will have proper instrumentation from their initiation, and the data we use will be more trustworthy and have fewer caveats when analyzed and communicated.
Output 3.1: Instrumentation
Initiate and proceed with a cross-departmental working group that makes concerted improvements to our EventLogging instrumentation workflow. This group will address challenges around front-end instrumentation, data storage, quality control processes, and ease of use. Teams will be able to measure new features more quickly, independently, and reliably.
Output 3.2: Controlled experiment (A/B test) capabilities
Initiate and proceed with a cross-departmental working group that makes concerted improvements to our ability to make scientific product decisions through controlled experiments. The group will iteratively standardize the technology tools, scientific methods, and guidelines by which we can run experiments, leading to experiments becoming increasingly more common in our decision making.

This group may evolve from or overlap deliberately with the instrumentation group, because controlled experiments rely on instrumentation capabilities.

Outcome 4: Deliverable creationEdit

Program metrics will be more easily generated, maintained, and communicated out to stakeholders through both changes in technology and process. Product decision makers will be able to independently explore data about their products. Stakeholders will have confidence that reports reflect the information they need to know.
Output 4.1: Report stewardship
Designate a steward or working group to organize legacy reports, create and enforce guidelines for organization of future reports, and create and maintain a reporting portal where decision-makers know they can find the reports relevant to program metrics.
Output 4.2: Reporting technology
Implement reporting technology recommendations from “Outcome 1: Assess and communicate needs”, such that different Audiences roles have the appropriate technology for their skill levels in order to generate reports, reports can be updated regularly, and can be collected into accessible portals for consumption by the broader organization.
Output 4.3: Wiki segmentation
Instead of implementing programs that attempt to affect all wikis at the same time, it is common for a given Audiences program to focus just on groups of wikis, such as mid-size wikis, or large wikis. Given that we focus our work on groups of wikis, we should be able to report out using those groupings. The output here are evolving sets of segmentations that classify different wikis into groupings relevant for the Audience department's work. These will be used to align strategic planning, program focus, and reporting on Audiences department impact -- making it possible to report out using the same groupings as we use in our daily work.

Targets for Better Use of DataEdit

Outcomes Targets Measurement methods
1 The Technology team, and particularly Analytics Engineering will have a clear understanding of the data collection, storage, analysis and communication needs of the Audiences department, and the two departments will have improved mutual understanding of which teams will work on these areas in the future. Written gap analysis and specifications during Q1 Written document on wiki
2 The human processes that are critical to data-driven decision making will have clearly defined owners and participants, helping ensure that all measurement priorities are accomplished efficiently and without confusion. This includes clear roles and responsibilities for the reporting of program metrics, as well as the cross-team stewardship of data policies. All product teams are producing and sharing their program metrics during Q1. Curriculum for measurement training completed by all product managers, tech leads, and designers. DACIs exist for all data stewardship areas. Reports and DACIs are posted on wiki.
3 Reduced cost of collecting data on program metrics and on the feature usage that supports those metrics. New features and products will have proper instrumentation from their initiation, and the data we use will be more trustworthy and have fewer caveats when analyzed and communicated. All non-trivial interventions on are reported on with quantitative impact by Q4. Documentation for correct use of instrumentation and controlled experiment technology and processes. Reports on important interventions are published in quarterly reports along with the program metrics to which they relate.
4 Program metrics will be more easily generated, maintained, and communicated out to stakeholders through both changes in technology and process. Product decision makers will be able to independently explore data about their products. Stakeholders will have confidence that reports reflect the information they need to know. Report portal is populated with program metric reports and is in use by stakeholders. Wiki segments included in reporting. Report portal usage metrics


Dependencies (optional)

Please describe any dependencies that this program has on other teams/departments, external partners, etc. This will help leaders of relevant teams understand and plan for the dependency.

  • This program will require significant engineering and consultative support from the analytics engineering team.
  • This program will require consultative support from research.
  • This program will potentially involve consultative support from the Legal and Security teams.

Community WishlistEdit

Meet the needs of active Wikimedia contributors for improved, expert-focused curation and moderation tools.

Activity type: Programmatic activities

Teams contributing to the program: Community Tech

Goals, Outcomes, and Outputs for Community WishlistEdit

Annual Plan FY18-19 topline goals: Knowledge as a Service/Foundational Strength – evolve our systems and structures

How does your program affect the annual plan topline goal? This program benefits the core contributors in our volunteer communities, making their work on the projects easier and more productive. This supports increased production, curation and moderation of Wikimedia projects as sources of knowledge.

Program Goal: Core contributors are more productive.

Very active contributors will be more productive and more satisfied with their on-wiki activities.

Outcome 1: Productivity and satisfactionEdit

Output 1
In 2018, the team is responsible for investigating and addressing the top 10 wishes from the 2017 survey, including: Infobox wizard, development on the Programs and Events dashboard, Article Alerts in more languages, auto-save for VisualEditor, and others.

Milestones:

  • 100% of Top 10 Wishes from 2017 Wishlist are completed or addressed on-wiki by EOY 2018.
  • The 2019 Wishlist Survey is completed by EOY 2018
  • 100% of Top 10 Wishes from 2019 Wishlist are investigated by April 1, 2019
Output 2
Build features to benefit groups of users that work with WMF Community Engagement, including admins, stewards and grantees, as well as internal tools as prioritized by Community Engagement
Resources

Targets for Community WishlistEdit

Outcome Target Measurement method
Improved productivity and satisfaction for very active contributors Over 50% of Wishlist participants report being satisfied with the outputs of the previous years’ Wishlist. We will run an optional, unintrusive one- or two-question survey as part of the 2018 Wishlist process. We will disregard responses from users who identify as being unfamiliar with the 2017 Wishlist.

WikidataEdit

Mutual development with WMDE on open-sourced code to be used to improve the functioning of Wikimedia sites.

Activity type: Programmatic activities

Goals, Outcomes, and Outputs for WikidataEdit

Teams contributing to the program: VP of Audiences

Annual Plan FY18-19 topline goals: Knowledge as a Service/Foundational Strength – evolve our systems and structures

How does your program affect the annual plan topline goal? Mutual development with WMDE on open-sourced code to be used to improve the functioning of Wikimedia sites.

Program Goal: WMF will provide non-exclusive funding to WMDE to be used by WMDE to lead an engineering team to develop the Wikidata Software. Although users will continue to contribute to Wikidata.org freely, the funding will allow WMDE to commit to the structured development of Wikidata Software in accordance with the project plan.

Through this funding, the WMDE will use reasonable efforts to close the Wikidata Software’s identified key gaps:
  • API and Storage: apps required query & write access, secondary storage system
  • Curation: Success depends on the communities' ability to manage growth
  • Data Partnerships: Open data community is waiting for us to talk to them in earnest

Outcome 1: Improve Wikidata softwareEdit

Output 1.1: WMF will approve WMDE funding on a yearly basis to support WMDE in development and supporting the Wikidata software in accordance with funding plan
Output 1.2: WMF will install the wikidata software on WMF server to incorporate it into Wikidata.org site
Output 1.3: WMDE will create and deliver code for the Wikidata Software in accordance with Schedule B: Project Plan.
Output 1.3: WMDE will follow the Wikidata software development roadmap outlined in Schedule C: Goals, Reporting & Deadlines

Management of Personal DataEdit

Working with Legal and other departments to protect users' privacy and ensure their control over their personal data.

Activity type: General and Administrative activities

Teams contributing to the program: To be determined

Goals, Outcomes, and Outputs for Management of Personal DataEdit

Annual Plan FY18-19 topline goals: Knowledge as a Service/Foundational Strength – evolve our systems and structures

How does your program affect the annual plan topline goal? By working to improve the privacy tools we provide registered users and considering the best way to manage unregistered users information, we will continue to be a leader in internet privacy, and respect our users' needs and concerns.

Program Goal: To protect users' privacy and ensure their control over their personal data.

Outcome 1: Data PortabilityEdit

To be determined
Output 1.1: Wiki account data download
Primary team: Community Tech

Provide a way for users to download their wiki account data. The data will be exported in a structured, machine-readable format.

Output 1.2: Supplemental data download
Primary team: To be determined

The team will investigate and address the portability of other forms of user data, including but not limited to: code contributed by volunteer developers, contributions to Phabricator, grant proposals and authorizations, and travel and event registration data.

If making a particular form of data portable is impractical or damaging to the projects, the team will provide a written explanation.

Outcome 2: Data Deletion RequestsEdit

To be determined
Output 2.1: Data audit and implementation of best practices
Primary team: To be determined

The team will audit the current data deletion practices, and ensure that we're following best practices. This includes but is not limited to: IP and device information, event-logging, surveys and research studies.

Output 2.2: User masking
Primary team: To be determined

The team will consider the community-led Courtesy vanishing process, and determine if we need to make similar functionality available on request in order to better ensure user privacy.

Outcome 3: Data MinimizationEdit

To be determined
Output 3.1: IP Address Display Masking
Primary team: To be determined

The team will investigate the feasibility and impact of masking the displayed IP address for logged-out contributors. For circumstances and workflows where masking the IP address would be damaging to the projects, the team will provide a written explanation.

Search Engine Optimization (SEO)Edit

Help people find the Wikimedia projects by investing in search engine optimization (SEO).

Activity type: Programmatic activities

Teams contributing to the program: Reading web, Performance, Parsing, Product analytics

Goals, Outcomes, and Outputs for Search Engine OptimizationEdit

Annual Plan FY18-19 top-line goals: Increase our reach

How does your program affect the annual plan topline goal?

The number of users and visits to Wikipedia are directly related to our global impact, pool of potential editors, and fundraising. The majority of Wikipedia users and visits come to us through Google search results - determined by a constantly changing algorithm and presentation scheme.

Yet over the years, we have spent very little time monitoring and optimizing this important channel. Taking our historical prominence in Google search rankings for granted, we have neglected to examine where improvements can be made or taken steps to secure this important channel. At the same time, there are signs that there are opportunities for and threats to our model here.

Program Goal: To increase usage of Wikipedia, by making sure Wikipedia's appearance in search engine results are optimized

Outcome 1: Identify opportunitiesEdit

Prioritized initial, experimental interventions for search engine optimization are established
Output 1.1: Storing google webmaster console data
Primary team: Product analytics

Begin storing google webmaster console data, for easier monitoring and analysis and to establish long-term trends (currently limited to a 16 month window)

Output 1.2: Identify opportunities
Primary team: Product management

Generate a report highlighting opportunities for search engine optimization.

Outcome 2: Improvements and analysisEdit

Efforts to improve search engine rank and appearance are made, and the results are measured. We can better gauge the relative impact of making further changes
Output 2.1: Interventions implemented
Primary team: Reading web

We will make at least 2 improvements to our site html and the markup and crawler settings we provide for Google bots and measure the impact of these changes in order to prioritize further work

Outcome 3: Ongoing improvements//monitoringEdit

By the end of the year we will have an improved system in place for ongoing monitoring of our referral traffic and, possibly, have a set of further improvements to be made in the future.
Output 3.1: Maintenance plan and future work scope
Primary team: Product analytics

The team will end the year with dashboards or monitoring tools to look at longterm referral trends, specific assignment of who is responsible for monitoring and, depending on outcomes, a list of future work.

Targets for Search Engine Optimization (SEO)Edit

Outcomes Targets Measurement methods
1 Begin storing Google webmaster console data, for easier monitoring and analysis and to establish long-term trends (currently limited to a 16 month window). A prioritized list of SEO related improvements. Plan in place by end of Q1 written document on wiki
2 We will make at least two improvements to our site html and the data we provide to Google and measure the impact of these changes in order to prioritize further work. The idea will be to focus first on impact on large wikis where we might see a bigger impact in fundraising, before taking steps in the latter half of the year that should benefit smaller wikis more, particularly in countries where we have lower reach. 1 - 10% increase in search engine referrals to impacted wikis pagerequest logs, Google referral data
3 The team will end the year with dashboards or monitoring tools to look at longterm referral trends, specific assignment of who is responsible for monitoring and, depending on outcomes, a list of future work. dashboard up, metrics included in quarterly-cadence metric meetings pagerequest logs, Google referral data

ChangelogEdit

A Changelog of all non-format changes made since June 27th, 2018 sits at the bottom. If you update this page, please describe that change in the changelog. One might think page "history" would be sufficient, but it turns out its not optimal for keeping stakeholders informed.

Name Description Reason Date(s) added by
SEO Added draft section to describe our SEO efforts. These efforts are in the overall annual plan, and we want to reflect the work we're doing in audiences 2018-09-17 Jkatz (WMF) (talk) 16:37, 17 September 2018 (UTC)
SEO Revised traffic increase metric for SEO. The 5% traffic metric previously listed was inconsistent with the 1 - 10% increase specified in the overall annual plan. 2019-03-22 KZimmerman (WMF) (talk) 23:31, 22 March 2019 (UTC)