In July, I’ll be speaking at the Design & Content Conference, in Vancouver. Recently, I was interviewed by Geoffrey Daniel (@Geoffrey_Daniel), one of the MCs from the conference. We talked about how the industry has evolved over the time I’ve been doing this kind of work (two decades now!), what I’ve learned, how my job has changed, and a little bit about what I’m going to be speaking about in July.
I also learned that if you’re the kind of person who uses their hands a lot while talking, and you’re doing a video interview, you should probably just sit on your hands. 🙂
Watch the video over on the DCC site. Check out some videos from some of the other speakers, while you’re there. And then come see us in person at the conference!
My colleague and friend, Robert Stribley, recently arranged for our User Experience department to watch Rams, a new documentary by Gary Hustwit about the designer Dieter Rams.
After initially training to be an architect, Dieter Rams became a renowned industrial designer, creating many iconic, minimalist products for Braun in the latter half of the 20th century. His designs have influenced generations of designers after him. At one point in his career he stepped back and asked himself how someone could tell if their designs were good, and he articulated Ten Principles for Good Design. He was approaching this from the perspective of industrial design, but the principles have since been applied to other design disciplines as well. So, I thought I’d revisit these principles and apply them to the world of content, including content design, content strategy, and content creation.
Ten Principles for Good Content
For each of Dieter Rams’ principles, I have replaces the word “design” with the word “content.”
Good content is innovative
For Rams, this was a statement about the relationship of technology and design – he was developing technological products, and even using new materials to build them. He felt his designs should be as innovative as the products and materials.
In the world of digital content, the most innovation is happening in the ways that content is distributed, shared, discovered, and consumed. Content publishers have to make their content ready to be viewed on everything from large-screen displays to smart watches, and keep an eye on what’s coming next. They also have to be aware of how people are finding and sharing their content, so they can structure and craft their content for increased exposure.
Good content makes a product useful
This is a funny one, because sometimes the content is about a product, and sometimes the content is the product. In either case, it should be useful – and that means from the perspective of the audience. This requires a deep understanding of your audience’s needs. What are they trying to get from interacting with this content, and how do you make sure it’s crafted in a way to satisfy that need?
Good content is aesthetic
This is pretty clear. Good content should be enjoyable to read, watch or listen to. Otherwise, even if it contains useful information, you’re creating an unnecessary barrier that people have to push through in order to receive its benefits.
Good content makes a product understandable
In this case, Rams was saying that the product should be self-evident from the design. Consider an item you’ve encountered with such a clever design that you couldn’t figure out how to open it or start it. In the realm of content, this may apply most directly to the field of UX Writing, and the economy of words needed to concisely convey an idea or function.
Additionally, digital content is far reaching and as it travels to different sites and devices, you should make sure that it’s as complete and self-contained as it needs to be. Your content needs to make sense where ever and whenever a person may encounter it, or people will skip right by it.
Good content is unobtrusive
Here Rams seems to be reacting to design-for-design’s-sake. Basically, he’s saying, get our of your own way. Don’t show off your verbal skills at the expense of comprehension. Or, as Mark Twain said, “Don’t use a five-dollar word when a fifty-cent word will do.”
Good content is honest
In other words: Follow through on the promise of your content. If people followed this one, we’d see significantly less linkbait online. It’s not just about “fake news” though – it’s about making sure you’re not promising more than your content can deliver.
Good content is long-lasting
I love this one, because digital content can stick around for a long, long time and yet it’s often written or produced as if it’s going to be consumed right in that moment and then disappear forever. Future-proofing your content is not just about avoiding current slang, it means considering if it will continue to make sense to people in 6 months, or 10 years. It also means including metadata for reference (date stamp, source info, etc), and ensuring content can be separated from visual design elements so that when people encounter it later (perhaps in a completely different layout) they will still have all the textual and contextual cues they need to understand it.
Good content is thorough down to the last detail
This principle is about process. It means that you should be thoughtful, do your research, and consider the impact of every aspect of your content. For Rams, this meant “Nothing must be arbitrary or left to chance.” This creates an interesting challenge when we’re increasingly making use of algorithms to help create data-driven content and experiences. In my last post, The Algorithms are Hangry, I walked through some examples of both mundane and extraordinary bot failures. I think the best way to honor this principle, especially when working with dynamic content, is to consider way more edge cases than we would normally entertain, rather than just focusing on a handful of primary scenarios.
Good content is environmentally friendly
Taken literally, this principle applies to industrial design in a way that’s not particular relevant for digital endeavors. But at its core, it’s about conservation and if we consider the idea of “waste” more broadly, this one has a lot of applications.
For one, I think about the waste of content production time. In my own career, I’ve focused a lot on creating and improving tools and processes that make it easier to perform the repetitive tasks of creating and publishing content. This allows content creators to spend more of their time and energy being creative.
For another, I think about all the “contentless” content available. This content creates a lot of noise and makes it more difficult for people to find the content they really want or need. It’s content pollution, and in an attention economy, that should probably be considered a crime.
Good content is as little content as possible
For this principle, I weighed whether to leave the second instance of “design” as-is because I suspect there’s a nuance here where the first design is meant to convey “the resulting design” and the second design is meant to convey something more like “evidence of the process of doing design.” I don’t think the principle, as translated for the realm of content, is actually about having “as little content as possible” – although, that’s often going to be a side effect of keeping things simple, clear, and concise. I think this principle is really about making sure that the design process is invisible in the final product. It may take you hours to craft and edit your words, but in the end it should seem effortless, obvious, and inevitable.
I find it curious that none of Rams’ principles include a concept of design being “universal,” though maybe, for him this was inherent in the idea that design should be simple and self-evident. When relating this to content principles, I couldn’t find the best place to talk about important topics like accessibility or localization, though, in some sense, these may be considered tactics for making content useful, understandable, and thorough down to the last detail. It all depends on having empathy for a wider audience with a broader, more varied set of needs.
It’s an interesting framework, though. And even if it doesn’t comprehensively cover important content considerations, it’s clearly flexible enough to allow for the addition of new areas of practice. What I like best about it is that it came from a spirit of self-reflection. We could all stand to take a step back from time to time and ask ourselves how we know when our work is good.
Lots of articles (some with shiny infographics) will tell you about how much data we’re now creating, and how it’s increasing at a stunning rate every year. And yet, it’s still not enough data to make algorithms actually useful most of the time.
When I first started talking with people in the content industry about what was happening with semantic technology about a decade ago, occasionally people wondered with concern if things like natural language processing and artificial intelligence were going to make human content professionals obsolete.
My feeling at the time was “not any time soon.” These technologies seemed useful for assisting people, especially for managing data at scale, but they were always going to need to be guided and tweaked by people.
The basic expectation that most content professionals have is that algorithms will help us understand what people are interested in, and this information will be used to dynamically serve up more content that will be of interest. Some organizations may even use this information to guide content creation. Ideally, smart systems will even provide some level of assistance in producing that content.
But, I’m not here today to go down the rabbit hole of horrifying, pre-apocalyptic examples of AI gone wrong. I’m not even here to talk about the trashy link-bait promos that have infected most online journalism like a plague. I want to talk about how, even in their most mundane, limited functions, algorithms just aren’t hitting the mark as much as I’d have expected them to by now.
The bots are boring!
My complaint is with Google Now. My Android phone knows more about me than any technology really should. It knows what I search for, it knows where I go, it reads my email and knows (among other things) what movie tickets I bought. So, in theory, it should be able to show me some interesting things in the daily feed. I mean, specifically interesting to me, based on my actual interests.
Sometimes it works. It showed me an interview with Wim Wenders about the recently remastered “Wings of Desire” after I bought tickets to see the movie. That was a pretty cool article that I wouldn’t have even guessed was available. But generally the feed is roughly 80-90% things that are completely uninteresting to me.
To some degree, this is because I do a limited set of things on my phone, even within the larger realm of things I do online. For example, I always look up Fortnite hints and maps on my phone because my computer is too far away when I’m in the living room using the Xbox. So, my phone obviously thinks I’m a huge Fortnite fan and it now constantly shows me news updates, leaks, and articles about fan suggestions for the game.
I also wonder if there’s some kind of crossed-signal demographic effect going on (“people who like Fortnite also like XYZ”), because my feed recently included a string of stories about various football figures, even though I have never once shown any interest in football in anything I’ve done online. I had to manually mark a whole bunch of topics as “not interested.”
However, the deeper source of failure really seems to be that there isn’t the volume of unique, high-quality content out there to meet the need that Google is trying to fill with this tailored feed. When I first started using Google Now, I noted that there were a lot of cases where I would read an article and then it would show me “similar” articles which were really just summaries that other sites had written of the original article.
Lately I’ve noticed a different trend, which I’m sure is also influenced by these algorithms and metrics. While Google has previously gone to great efforts to cut down on content farms, it has also created an appetite for nutritionless content. And there are plenty of sources ready to jump in and fill that hungry void.
For example, let’s take Avengers: Infinity War. I was very interested in seeing this movie, but I didn’t particularly read a lot about it. I probably looked up the release date at some point before it came out, watched the trailer when it was released, and then bought tickets to see it in a theater. After seeing it, I looked up the expected release date for the sequel. It’s possible (even likely) that I did all of these things on my phone.
Since the movie came out, last April, my phone has shown me content about it every single day. At first it was explanations of the ending, and analysis of the poster showing how it secretly contained spoilers for what happened in the movie. But it very quickly became a stream of non-stop speculation, fan theories, hints, spoilers, and occasionally legitimate news about the sequel (which is coming out this coming April).
I cannot tell you how uninterested I am in almost all of this. I definitely didn’t want to read about Avengers for an entire year between movies. I have zero interest in fan theories that explain some speculative aspect of the sequel. Sure, it ended with a dramatic cliff-hanger, but I just want to quietly go about my business for a year and then go see part 2 when it’s ready and I can enjoy the culmination of 10+ years of Marvel Cinematic Universe storytelling. Sure, I could mark this topic as “not interested” but that’s not the case. I am interested in it. Just not to that degree, and not wild speculation and rumors.
Maybe if Google Now knew more about my other interests, the feed would be more balanced. But my guess is that this topic, being broadly popular, has a more steady stream of source material than the obscure “long tail” topics I’m interested in.
So, is the failing with the algorithms, or is the failing with the sources of content? Or is it some kind of dysfunctional way that they learn from and influence each other? In all of the examples described above, from spectacularly disturbing to humdrum disappointing, the problem seems to call for the capability to course correct, to monitor the algorithms and tune them to be more discerning. That gets into some very subjective areas that our AIs are not quite read for. More likely, we will just keep feeding them whatever they demand and hope for the best.
The idea of going into your parents’ line of work seems kind of archaic these days. Unless maybe you’re the villain in a superhero movie. Which is why I was a little shocked to realize, while talking with a family friend several years ago, that I had gone into a field that is essentially a blend of the work my mother and father did.
I was trying to explain Content Strategy to Bruce, a man who had known my parents since they were all in college together, and I described it as “some parts like an editor and some parts like a database programmer.” He responded, “Well, then it sounds like the job you were born to do.” I was probably just trying to put it in terms that I knew he would understand, but it didn’t even occur to me that I was describing my work in terms of my father and mother’s life-long careers.
When I was in grade school, my mother, Ceil Silver, was a Systems Administrator for Sperry Univac. She trained and supported clients like NBC and SUNY Stony Brook on how to use giant mainframes. I had no idea what this meant, at the time, but I was playing with punchcards at a time when most kids had never heard of computers. Plus, I was watching my mom work in a male-dominated field and succeeding at it.
Later, we were one of the first families I knew of to have a personal computer in their home, and my mom became a database developer. She built custom applications in FoxPro for clients who used them for billing, course registration, and running other important aspects of their businesses. She went to user group meetings and conferences, became a Microsoft MVP, and wrote articles on FoxPro Tips. She didn’t talk about her work that much, but she was undeniably an expert in her field.
My dad, Jay Lovinger, was working as a journalist when he discovered his true calling as an editor. He landed a job at a new magazine called Inside Sports, eventually becoming the second in command before the magazine folded. He worked at People magazine. He started a Sunday magazine for the Washington Post. He was the editor of Life Magazine for about a year. He’s worked at Sports Illustrated and ESPN. He’s won Emmy awards for online video stories that were ostensibly about sports, but really about people, challenge and triumph. If you’re a fan of sports journalism, he’s probably worked with your favorite writers, and he has a reputation for being one of the best long-form editors in the business.
None of this was consciously part of my decision to go into the field of digital content strategy, a field that didn’t even exist when I started my professional life. But I have always loved words, content and communication, and I have always been comfortable with computers and intrigued by the role they play in the way we create, share and find information.
I guess it’s just a good thing my parents weren’t underwater pirates, or I could have ended up like Black Manta.
Let’s talk about what I’m doing with this blog. When I started writing here, in 2007, I had two blogs. I had this blog for writing about content strategy and the semantic web, and I had a personal blog, where I mostly wrote about movies, sometimes about other pop culture things, and sporadically about weird things I experienced or overheard while living in NYC or traveling.
I updated both blogs most actively from 2007 through 2009. After that, I shifted most of my professional writing to a now-defunct content strategy blog we started at Razorfish, called scatter/gather, updating this blog only on rare occasions, and I switched to posting about weird experiences and pop culture on Facebook. I took notes about movies I saw at film festivals in notebooks, but didn’t bother to post them online anywhere.
Both blogs languished.
Since that time, the lines between professional personas and personal personas have increasingly blurred. Part of it is because of Twitter, Facebook, and other online forums which were ostensibly designed for “connecting” but turned into mostly “broadcasting.” Part of it was due to a movement in professional conference and writing circles to start telling more personal stories about empathy, vulnerability, roadblocks, and failure. I feel cynical about it when I hear people talk about their “brand,” but the reality is that empathy works a lot better when we interact as real, multi-faceted people, and not as business robots. I’ve seen many in my cohort do a pretty nice job of writing about the successes and challenges they encounter in both their work and their personal lives, together, in the same places.
So, as I bring this blog back up to speed, I’m still going to be writing about trends and ideas in the realm of digital content, but I’m also going to be weaving in some posts about non-work experiences and observations (like my last post, about movies I’ve seen recently at the Alamo draft house). But, I’ll probably still turn to Facebook to talk about those random celebrity encounters, or weird overheard conversations in an NYC bodega.
I realized recently that I haven’t updated the Resources page in three years. Obviously, there are a lot more recent, more interesting resources out there now. So many, in fact, that I should probably entirely replace what was there. But I do want to retain that info, so here it is in a post. Refreshed Resources page, coming soon.
[As of 10/7/09]
I gathered the following resources to be a handout to go along with my “Content Gone Wild!” talk at the MIMA Summit 2009. These articles and sites support the Content Strategy practices discussed in the examples from the presentation. These are not the only resources, and they’re not necessarily the final word on these topics, but they should provide some good information and get you started with practical techniques and tips.
TopBraid Composer™ – a commercial tool for building ontologies and semantic web applications. TopBraid Ensemble™ adds a layer that makes it more user-friendly for content providers, and may also be useful in prototyping.
Apparently, it’s time for my semi-annual blog update!
I’ve been focusing a bit more on work-work this year, and dialing it back on some of the writing and speaking. Not entirely, just gathering up my thoughts so that I can continue working on things that are interesting and relevant.
Writing: I’ve continued to post Scatter/Gather, Razorfish’s Content Strategy blog. And I also published some articles elsewhere this year.
Speaking: This year I got more serious about scaling back on the public speaking. The My Presentations page has been updated with info and links to recordings (when available). Here’s also a list of just the new ones:
Metadata Workshop – Content Strategy Applied, London, UK, March 1-2, 2012 (on slideshare)
Content Strategy: Why Now? – Sisältöstrategiaseminaari 2012 (Content Strategy Seminar 2012), Helsinki, Finland, February 8, 2012 (on slideshare)
Coming soon – I’ll be co-presenting a workshop and giving a talk at Content Strategy Forum 2012, Cape Town, South Africa, October 24-26, 2012
Attending: Even though I’m doing less speaking, I still love the inspiration of going to conferences. I also went to Confab, and soon I’ll be going to dconstruct and XOXO.
Other: One other thing I’ve been up to – I’m serving as Producer on a documentary that Jason Scott is shooting about DEFCON. Here’s a teaser trailer. There’s some other clips, teasers, and test footage on Jason’s YouTube channel.