Content Feed Best practices

An explanation of how Content Feeds add value and how best to utilise their functionality

What are Content Feeds?

Content feeds are an unstructured way of delivering relevant content to end-users using tags (think of it like social media or news applications). Content items are grouped inside a Content feed and content can be in the form of video (Youtube, Vimeo) or web articles which are displayed on the end-users app home screen. Content feed offers a powerful way to reach users with continuous content and here are some of our best practices and tips to help you get the most out of content feeds.

  • Content feeds should have high-quality images and videos that stand out and instantly attract your audience as content is the key to building meaningful relationships with your end users. Content Feeds help to capture users’ attention, maintain their engagement, inspire them, provide important updates and take them on learning journeys essential to your service. 
  • Check the settings for Vimeo videos to ensure that they are correct. The settings should be changed from "Unlisted" to "Hidden from Video" for all Vimeo videos to play properly inside a content feed.
  • Showcase new content regularly to keep the app fresh and engaging.
  • The delivery and order of content items in a content feed are determined by the ML (Machine Learning) & tags and end-users can save content items to a library to access at any time. End-users can reach out to an expert or app admin directly from a content item.
  • End-users can save and rate content items as well as reach out to experts directly from the content item.
  • Everything on the platform is governed by tags. Tags are associated with users implicitly and explicitly through surveys and their interaction with content and parts of the system. All content items are also tagged in the same way and the engine works hard to match users with content items they might be interested in. This process means that the more we learn about a user the closer we can match content to their interests. Content is then fed to the user according to a predefined schedule. Users' engagement or disengagement with that content further informs the matching engine. Additionally, we can see the degree of content saturation (or lack thereof) and advise where there is a mismatch between the content available and the interests of the users.