Scaling Developer Content Production at Snyk ![rw-book-cover](https://mletojawq8w4.i.optimole.com/cb:TRmb.b7c6/w:auto/h:auto/q:90/f:avif/https://developerrelations.com/wp-content/uploads/2022/12/snyk-case-study.png) [[3. Resources/Readwise/Full Document Contents/Articles/Scaling Developer Content Production at Snyk|Full Document Contents]] ## Document Notes Abstract: This document presents a strategy for scaling developer content production at Snyk, a platform for open-source security. It begins by identifying three content types – deeper technical pieces, introductory technical content and news/event reaction – and making a model to measure their impact. This is followed by creating a production timeline for each content type with the goal of increasing effectiveness. Finally, the document outlines a plan to forecast the average impact of a content piece for a given goal. By implementing this plan, Snyk aims to increase their content production's overall effectiveness. Bullet List: - Identified three content types: - Deeper technical pieces - Introductory technical content - News and event reaction - Model content’s impact - Create a reliable production timeline - Forecast average impact of content pieces - Increase effectiveness of content production Paraphrasing: Original: To model content’s impact, the Snyk DevRel team identified three content types: Deeper technical pieces that generate around a thousand sessions in the month after publicationIntroductory technical content that generate around half the sessions but takes less work to produceNews and event reaction, such as a post on the Log4Shell vulnerability, that could generate as many as 30,000 sessions but happen only once or twice a year. Paraphrased: To measure the effectiveness of content, the Snyk DevRel team categorized it into three types: Deeper technical pieces that bring in about a thousand viewers in a month after publishing, introductory technical content that acquire half the number of viewers but are easier to create, and news/event reactions like a post on the Log4Shell vulnerability that can gain up to 30,000 viewers yearly but only occur a couple of times a year. > [!note]+ Document Notes > Abstract: > > This document presents a strategy for scaling developer content production at Snyk, a platform for open-source security. It begins by identifying three content types – deeper technical pieces, introductory technical content and news/event reaction – and making a model to measure their impact. This is followed by creating a production timeline for each content type with the goal of increasing effectiveness. Finally, the document outlines a plan to forecast the average impact of a content piece for a given goal. By implementing this plan, Snyk aims to increase their content production's overall effectiveness. > > Bullet List: > > - Identified three content types: > - Deeper technical pieces > - Introductory technical content > - News and event reaction > - Model content’s impact > - Create a reliable production timeline > - Forecast average impact of content pieces > - Increase effectiveness of content production > > Paraphrasing: > > Original: To model content’s impact, the Snyk DevRel team identified three content types: Deeper technical pieces that generate around a thousand sessions in the month after publicationIntroductory technical content that generate around half the sessions but takes less work to produceNews and event reaction, such as a post on the Log4Shell vulnerability, that could generate as many as 30,000 sessions but happen only once or twice a year. > > Paraphrased: To measure the effectiveness of content, the Snyk DevRel team categorized it into three types: Deeper technical pieces that bring in about a thousand viewers in a month after publishing, introductory technical content that acquire half the number of viewers but are easier to create, and news/event reactions like a post on the Log4Shell vulnerability that can gain up to 30,000 viewers yearly but only occur a couple of times a year. ## Highlights - • create a reliable production timeline for each type of content and how it affects an individual’s ability to deliver on other types of work • forecast the average impact that a content piece should have on their goal of inc ([View Highlight](https://read.readwise.io/read/01gvx0pq7xmy01rw831r8qmcap)) - To model content’s impact, the Snyk DevRel team identified three content types: • Deeper technical pieces that generate around a thousand sessions in the month after publication • Introductory technical content that generate around half the sessions but takes less work to produce • News and event reaction, such as a post on the [Log4Shell vulnerability](https://en.wikipedia.org/wiki/Log4Shell), that could generate as many as 30,000 sessions but happen only once or twice a year. ([View Highlight](https://read.readwise.io/read/01gvx0pxwbqj8613a8qxa38ppm))