|Need||Create a paywall with seven free reads a month. Sell membership and include membership with purchase of magazine subscription.|
|Idea||Create an encrypted API on main server to communicate with store's host (BigCommerce).|
|Steps taken||The steps used to create this proprietary function are not publicly shared.|
|Result||Prime access became a very popular product and was responsible for significant revenue.|
Many publishing websites in recent years have incorporated paywalls to pay their authors and contributors. Nautilus offered the service as a membership to Prime. It could be bought as a standalone yearly subscription or included in a print subscription as an additional benefit. As a member of Prime, you have unlimited access to all content published on the site. Public views only allowed seven monthly articles. In addition to unrestricted access, there is ad-free pages and the opportunity for offline viewing by downloading issues as ePubs or PDFs. Prime is also configurable to open access for members of specific scientific groups or students visiting nautil.us from school computers.
|Need||Show a visitor how other readers are reacting to the articles.|
|Idea||Use Google Analytics API to control what is shown.|
|Steps taken||Pre-configure a specific report in the Google Analytics admin panel. Make decisions about what kind of data to report and for duration of sample (most recent 7 days). On the main server, set up a cron job to hit the Google Analytics API every 6 hours and cache the response as JSON. Request the cache every time the home page is shown and have it locate the six 'Most Read' and 'Most Shared' articles.|
|Result||Increase in traffic to popular pieces without data server impacted from large queries.|
Often when a website needs to show a "most-popular" module, it is done by tracking the clicked articles in a traffic table within the site's database. Rendering the module means using that table to determine what to show and in what order. Making periodic calls the Google Analytics API and caching the response provided more information about the users' habits then could have been done with a simple "click table." Are they sharing on social media? Are they emailing articles to each other? Is it a particular issue that's getting the most attention?