When a digital product’s core functionality involves the display of content, the effectiveness of designs can’t be evaluated until such content exists. Prototyping is an effective means of validating designs, but unless prototypes include rich content, they will remain limited in their effectiveness.
I’ve begun to think of this kind of prototype as a “content prototype.” I draw a distinction between, say, a motion prototype (which may be as simple as an animation in Keynote demonstrating the movement of a few display elements) here because it allows users to search, filter, retrieve or read content. I also distinguish between product design approaches that flow content into static designs, such as those facilitated by the awesome Sketch Data Populator. While it’s important to make sure that your designs can accommodate the kinds of content they’re designed to display, doing so, at a template level, is often a case of making sure that you’ve designed elements that can accept strings of a certain length, or assets of a certain aspect ratio. Content prototypes are less about validating designs at the node level than allowing the design team to validate interactions that rely on sets of content. Does the search functionality return good results? Do those filters help to refine results effectively? Are there even enough content elements to necessitate search and filter functionality? These are the kinds of questions you can start answering when you prototype with live content.
To get started, you’ll need a set of content and a means of getting that set into your app. Both of these elements can be deceptively tricky. The set of content has to be both of good enough quality to serve as sample content in the prototype, and in the right format. (Often, web crawling can help here.) The measures for content quality can vary, of course, but in prototypes, soft attributes like voice and tone tend to matter less than the presence of usable metadata. Another element of a set of content’s suitability for prototyping is its size: if there’s not enough content items, the set won’t be able to help evaluate the effectiveness of search and filter functionality.
Creating a production ready content library is painstaking work. To apply the same level of rigor to content intended for prototyping is often untenable. However, one can assemble a set of content suitable for testing using intelligent modifications of existing content.