Growth/Personalized first day/Newcomer tasks/en

This page describes the Growth team's work on the "newcomer tasks" project, which is a specific project under the larger "Personalized first day" initiative. This page contains major assets, designs, and decisions. Most incremental updates on progress will be posted on the general Growth team updates page, with some large or detailed updates posted here.

The design and planning for this project began on 2019-07-24.

Current status

 * 2019-07-24: first team meeting to discuss newcomer tasks
 * 2019-08-27: team meeting to go over design concepts.
 * Next: team meeting to discuss technical approaches

Summary
We think that newcomers should have every opportunity to succeed when they first arrive at the wiki. But frequently, newcomers attempt a task that is too difficult for them, can't find a task they want to do, or can't find ideas for how to remain involved after their first edit. This leads to many of them leaving and not coming back. There have been successful attempts in the past at recommending tasks to editors, and so we believe that the newcomer homepage is a potential place to recommend relevant tasks for newcomers.

We'll need to keep in mind a few things:
 * Many newcomers arrive with something specific in mind they're trying to accomplish, like add a specific photo to a certain article. We don't want to get in the way of them accomplishing their goal.
 * Newcomers build up their skills over time by progressing from easier edits to hard ones.
 * When newcomers are successful early on, they are more motivated to continue editing.

Taking those things into account, we want to recommend tasks to newcomers that... A valuable tool we have for helping tasks be relevant to newcomers is the welcome survey, which was originally built specifically for this purpose: personalizing the newcomer's experience. We'll plan to use the optional information newcomers give about their goals and interests to recommend appropriate tasks for them.
 * ...arrive at the right time and place for a newcomer's journey.
 * ...teach relevant conceptual and technical skills.
 * ...gradually guide users to build up their editing abilities.
 * ...be personalized to their interests.
 * ...show them the value and impact of editing.
 * ...motivate them to participate continually.

One of the largest challenges is going to be figuring out how to gather tasks that are appropriate for newcomers to do. There are many existing sources, such as templates that call for work on articles, recommendations in the Content Translation tool, or suggestions from tools like Citation Hunt. The question will be which of those options help newcomers accomplish their goals.

At first, we'll focus on using the newcomer homepage as the place to recommend tasks, but in the longer term, we can imagine building features that extend into the editing experience to recommend and help newcomers accomplish recommended tasks.

Also in the longer term, we'll be thinking about ways to tie task recommendations into other parts of the newcomer experience, such as the impact module on the homepage, or into the help panel.

Why this idea is prioritized
We know from research and experience that many newcomers fail early in their editing journey for one of these reasons:
 * They arrive with a very challenging edit in mind, such as writing a new article or adding an image. Those tasks are difficult enough that they likely fail and don't return.
 * They arrive without knowing what to edit, and can't find any edits to make.

We also know that on the newcomer homepage, the most frequently clicked-on module is the "user page" module -- the only thing on the page that encourages users to start editing. This makes us think that many users are looking for a clear way to get started with editing.

And from past Wikimedia endeavors, we've seen that task recommendations can be valuable. SuggestBot is a project that sends personalized recommendations to experienced users, and is a well-received service. The Content Translation tool also serves personalized recommendations based on past translations, and has been shown to increase the volume of editing.

For all these reasons, we think that recommending specific editing tasks for newcomers will give them a clear way to get started. For those newcomers that have an edit in mind that we want to do, we'll encourage them to try some easy edits first to build up their skills. For those newcomers who do not have a specific preference on what to edit, they'll hopefully find some good edits from this feature.

Glossary
''There are many terms that sound similar and can be confusing. This section defines each of them.''


 * "Task recommendations" or "Task suggestions"
 * Lists of articles that need editing work, suggested automatically to users.


 * "Personalized"
 * Software that adapts automatically to each user to fit their needs.


 * "Customized"
 * Software that the user adapts to fit their needs.


 * "Topic"
 * A content subject, such as "Art", "Music", or "Economics".


 * "Maintenance template"
 * Templates that are put on articles indicating that work needs to be done on them.

Comparative review
Our team's designer reviewed the way that other platforms (e.g. TripAdvisor, Foursquare, Amazon Mechanical Turk, Google Crowdsource, Reddit) offer task recommendations to newcomers. We also reviewed Wikimedia projects that incorporate task recommendations, such as the Wikipedia Android app and SuggestBot. We think there are best practices we can learn from other software, especially when we see the same patterns across many different types of software. Even as we incorporate ideas from other software, we will still make sure to preserve Wikipedia's unique values of openness, clarity, and transparency. The main takeaways are below, and the full set of takeaways is on this page:


 * Task types – bucket into 4 types: Rating content, Creating content, Moderating/Verifying content, Translating content
 * Incentives – Most products offered intangible incentives mainly bucketed into the form of: Awards and ranking (badges), Personal pride and gratification (stats), or Unlocking features (access rights)
 * Reward incentives – promote badges or attainments of specific milestones (e.g., a badge for adding 50 citations)
 * Personalization/Customization – Most have at least one facet of personalization/customization. Most common customization is user input on surveys upon account creation or before a task, most common system-based personalization type is geolocalization
 * Visual design & layout – incentivizing features (stats, leaderboards, etc) and onboarding is visually rich compared to pared back, simple forms to complete short edits.
 * Guidance – Almost all products reviewed had at least basic guidance prior to task completion, most commonly introductory ‘tours’. In-context help was also provided in the form of instructional copy, tooltips, step-by-step flows,  as well as offering feedback mechanisms (ask questions, submit feedback)

User testing
To be written

Measurement and results
To be written