Content translation/Product Definition/analytics

In order to understand the impact of Content Translation, a set of metrics are defined.

Content available in more languages
The main goal of Content Translation is to increase the content available in different languages. New articles created with the tool will be the main element to observe. Several metrics are defined to measure the success in achieving this goal:
 * Quantity of content:
 * Number of articles created in language X. This is a key metric for success since it reflects the increase in language support for articles (the number of languages in which an article becomes available). Analysing this on a per language basis allows also to identify the languages that have expanded more their number of articles thanks to the tool.
 * Length of articles. This gives an idea of the kind of articles produced. It can be useful to compare to the length of the original article (e.g., "users translate only 30% of the original article on average").
 * Impact and quality:
 * Number of readers on the original article. Does the availability of an article in other languages reduces the readers of the original one?
 * Number of readers for new articles. How many people is accessing the new content.
 * Amount of automatic translation.
 * '''Translations vs. regular edits per user"'. How many users are only contributing as translators. are prolific editors adopting translations or just users with fewer regular edits?
 * Evolution in time:
 * Edits on new articles. Is the content growing after the initial translation for new articles.
 * Deletion rate. How many articles produced by the tool are deleted by the community. It will be useful to correlate the deleted articles with other metrics (article length, amount of automatic translation, editing expertise of the user).

Other metrics
Other metrics may be considered to get an in-detail view of specific features.

Tagging articles
To support the measuring of the metrics above, the articles created by Content Translation will be tagged. Tags will allow to (directly or indirectly) identify the following context information:
 * The article was created by Content Translation.
 * The language of the translation.
 * The source article used for the translation.
 * Amount of automatic translation used in the translation. This a percentage or a discrete value (none, low, medium, high, all).
 * The number of edits of the user that creates translations. This indicates the editing expertise and may help to understand other metrics.