Podcast: Include It All, Filter It Afterwards -- Interview with Mark Baker
In this podcast, I talk with Mark Baker from Every Page Is Page One about the ideas he discussed in his Lavacon presentation: Include It All, Filter It Afterwards. This is a line from David Weinberger's book Too Big To Know, which explores the way that knowledge is taking the shape of a network rather than the traditional book.
The podcast is about 45 minutes long. Similar to other podcasts, the format works best if you listen while driving, exercising, or walking (or if you can manage it, sitting in a hot tub). If you're not a podcast listener and prefer the text version, see the summary below.
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On the web, people find and navigate your help content in non-linear ways, so you have to treat every page as if it's the first page ("page one") for the reader. This means you provide more context, add more links to other content, and overall give the reader enough information to achieve their goal.
Bursting a traditional book into small chunks online results only in a confusing, scattered experience for the reader. Think about how Wikipedia organizes its information, and you have a model for the Every Page Is Page One style.
When you consider this Wikipedia-like style, length becomes a dilemma. Best practices for online reading suggest short content, because users skip and skim and don't tend to stick around on any single page too long. However, shortening the content makes it difficult for users to get all the information they need. In fact, users may bounce around online precisely because they're not finding the information they need on the current page.
Mark says that structure can help solve the dilemma of length. To think about structure, consider how recipes and other genres have defined patterns that help users predict and navigate the content. That kind of structure can help users navigate longer content to find what they're looking for.
Mark isn't necessarily promoting the DITA structure of "task, concept, and reference" (what he refers to as the terrible troika). Many people incorrectly interpret these building blocks as separate topics, which leads to disconnects between tasks and concepts in ways that leave readers with incomplete information. Chunking information into these topic types may be a good idea, but DITA doesn't provide any guidance on information assembly and design. In other words, it provides the bricks, but not the blueprints for the house.
In addition to the Every Page Is Page One style, Mark also agrees with Weinberger about including more abundant information. Rather than following the book's paradigm of filtering and weeding out content, we should actually include it all, even the unlikely scenarios.
The constraints of a book require us to cut non-mainstream material because we have a finite set of pages to work with. We leave out edge cases, the less popular content, the exceptions and footnotes, etc., because a book can only be a certain length. Any reports or data we refer to, we usually summarize the information. We filter the information because a book has limits of what we can include.
But the web doesn't function with the constraints of a book. And excluding content doesn't lead to a successful online strategy. Sites that succeed often do so by winning the Long Tail game. Large stores like Amazon or Wal-Mart, where you can find and buy everything in one place, win out over specialty shops. People are searching for a great many types of information, and if they don't find it on your site, they'll go elsewhere. As a result, you're better off including everything and letting users apply their own filters, often from Google's search, to sort and organize the content.
For more information about Mark Baker, see Everypageispageone.com. For more information on some of the ideas in this podcast, see my related post, What Does “Every Page Is Page One” and “Include It All, Filter It Afterward” Mean?
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About Tom Johnson
I'm a technical writer based in the California San Francisco Bay area. In this blog, I write about topics related to technical communication — Swagger, agile, trends, learning, plain language, quick reference guides, tech comm careers, academics, and more. I'm interested in simplifying complexity, API documentation, visual communication, information architecture and findability, and more. If you're a technical writer of any kind (progressional, transitioning, student), be sure to subscribe to email updates using the form above. You can learn more about me here. You can also contact me with questions.