Talk:Analytics/Data Lake/Traffic/UserRetention

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Potential Collaboration between Fundraising, Reading, and Analytics

It seems to me User Retention doesn't make sense to us in the traditional sense that it would at e-commerce companies. But it still seems important to Fundraising, maybe with an alternate custom definition that we can come up with. So Fundraising could be a good, concrete stakeholder. Reading could guide that into requirements that make sense for them as well, and Analytics could provide technical help with the data pipeline and metrics reporting. I just wanted to point out this potential collaboration, seems like it could work well. --milimetric (talk) 17:30, 23 August 2016 (UTC)

Agree. And adding to that: In e-commerce, for example, pageviews are tied to purchases because pageviews are mere previews of the product clients will buy, they are part of the consumption funnel; more pageviews statistically mean more purchases. However, in Wikipedia, pageviews correspond to the user browsing and consuming the final product. Pageviews do not precede donations in a consumption funnel. So, +1 alternate custom definition. Mforns (talk) 14:38, 25 August 2016 (UTC)

Our own metric instead of industry standard

I think the retention metric is designed/intended for sites that offer products to their clients (in exchange for money). And those products have a consumption cycle, like: shoes, news, TVs, books, etc. When those products wear out or are fully consumed, you can expect the client to return.

In Wikipedia's case, knowledge does not wear out. A user that reads page A will probably not read it again any soon. And if a user has the wish to read 100 pages, they may very well read them in 1 day, because it's free (money is not a tempo factor). Also, Wikipedia's contents are not periodically refreshed, like a rotating stock that follows fashion trends, wiki contents grow/change in a different way. So, I wonder if Wikipedia users follow a cycle that can be measured.

I'm not saying that we can not learn things from retention concept, but instead of going for the industry definition of retention I would go for our own metric: think what we want to know and why, and then choose a metric. Mforns (talk) 14:29, 25 August 2016 (UTC)