The cliché "content is king" is as tired as its close cousin "stories sell." Neither is any less valid than a decade ago when online marketing started taking off, but today's content marketing has a lot more tools at its disposal.
Here's a look at what makes for great digital marketing content nowadays, complete with fresh data on referrals, social media, and sponsored content.
1. Original data creates the most compelling stories
Data-based stories are at once the next big thing on the digital content marketing scene but also the most criminally disregarded format out there, according to Alexandra Samuel. She argues that a few big names like The Guardian and The New York Times are already investing and cashing in on this type of content creation, but that marketers are still overlooking the opportunity.
There is some evidence that brands are slowly wising up to the trend of creating compelling stories based on data. For example, Pinterest is teeming with infographics. However, the vast majority of those visual posts are nothing but pretty blog posts, arranged in graphic form—with nothing remotely close to insightful, fresh, and original data.
Moreover, run a Google search on "data-driven content," and you'll find very few results about creating content backed with stats, facts, and figures. Yet when strategizing content marketing campaigns based on metric, reach, share, and page insight reports, marketers are busily churning out ideas.
Why aren't more brands investing in this kind of content?
Let's look at some reasons, which are actually all fear-based misconceptions, and debunk them.
- "I don't want to reveal too much of my brand's inner workings to audiences at large." As a marketer, have you ever felt frustrated because of Google's lack of transparency in providing organic keywords or in publicizing major algorithm updates? I'm willing to wager the answer is "yes"—and it's legitimate. However, brands stand to gain a lot of trust when they show their users, audiences, and clients what they do with the data collected from them.
- "I don't know how to put the data I collect in story form." (In this case, you might need a better content creation team.) A recent post from the Nieman Lab has revealed that the handful of brands that do use data-driven content marketing are not too adept at it, but they still produce viral posts.
To make better use of data, consider working with trained statisticians or sociologists. Also, don't hesitate to look for brands that do things the right way. One great example is a data-based story from sleep-monitoring app Jawbone:
- "I'm not sure how sharing my data will benefit my brand." We've already covered the matter of establishing authority and trust. Social media sharing is almost a given in regards to creating fact-based content. If you're going to put solid data out there, you're also going to share some priceless educational resources. Posts with facts and figures are highly likely to get more links. You'll also get a glimpse into how other brands and marketers use your data (i.e., how they relate to your industry). Finally, and perhaps most importantly, when you publish data and make good use of it, it's impossible not to attract organic traffic based on the sheer quality of the content alone.
2. But all data (with no story) will fail
Though author Samuel makes a powerful case in favor of aptly using data for story-telling purposes, marketing guru Geoff Livingston states that today's digital marketers are skilled at using precision tools in creating targeted campaigns, but when eliciting emotions that compel and trigger important consumer behaviors like a sense of loyalty, affiliation, trust, and well-being, marketers fail. Livingston argues this is because marketers have forgotten how to tell stories. Though he may be empirically correct, let's also take a look at what science is saying.
The above image from Neuroscience summarizes the findings of a data analysis survey by Britain's IPA, whose databank stores information on more than 1,400 successful ad campaigns. The researchers wanted to know how purely emotion-based efforts ranked against those that combined sentiment and reason as well as those based purely on rational arguments.
Emotion-based campaigns won out by nearly double the margin of the runner-up (combined emotional-rational campaigns: 31% vs. 16%, respectively).
Those findings have been confirmed time and again, both by neuroscience as well as by marcom data analysis. Here are some further examples and arguments, aimed to sway you toward creating emotion-eliciting content:
- The brain processes emotion at one fifth the time it takes to process rational thought. This factoid comes from Emotionomics: Leveraging Emotions for Business Success, a recent book by Dan Hill.
- Emotional response happens at the pin-pointed intersection between the new and the familiar. Abigail Posner, head of Google's Agency Strategic Planning team, cites neuroscience research to argue that online content elicits emotions because it causes the synapses to fire away pure joy. That occurs when the brain connects familiar elements in surprising new ways.
Need some case studies to go with these arguments and illustrate how emotions affect user behavior? There you go:
- Generac, a standby generator producer, doubled its business by allaying its clients' fears. Generac ran a study that proved that men associate using its product to protecting their families like a superhero, and women reported a sense of deep fear without the same product akin to being on the sinking Titanic. The company re-articulated its campaigns based on these findings and grew its business by 100%, to $1.2 billion over just 2 years.
- A study shows that people who experience fear while they watch a movie also feel affiliation toward a brand present at hand. The research, published in the Journal of Consumer Research, shows that fear is a more powerful trigger for brand loyalty since it's an experience one needs to share. Sharing fear with friends reduces the pressure inflicted by the emotion, but when no human companionship is available, even an abstract brand will do.
3. Reach that sweet spot between shares and links with powerful voices and strong facts
When BuzzSumo and Moz, two of the biggest names in online metrics reporting, teamed up for research purposes this summer, its declared goal was not to confirm the two points above (that the winning formula for great content = data + emotion). However, that's precisely what they did, inadvertently, while looking to find out what makes a post shareable and backlink-able. Here's what they found, in a nutshell:
- Most posts are plain bad but also poorly promoted. In an initial sample of 100,000 random posts, more than half had two or fewer Facebook interactions and more than 75% had no external links.
- Getting shares is easier than getting links. In a larger sample of 750,000 highly shared posts, 75% had no backlinks.
People share and link for different reasons. The correlation ratio between shares and links in the 750,000 article sample was a mere 0.021. Here's a breakdown of the stats:
The findings regarding posts that get both shares and backlinks were consistent across several sample types. In the random sample of over 750,000 well shared posts, the experts at BuzzSumo and Moz found high correlations of links and shares on domains with high-quality, well-researched articles.
However, since each of these sites came with a small sample size of articles, they undertook further research on sites with consistently high numbers of shares. They looked nearly 50K articles from the New York Times and over 45K from The Guardian. By breaking down the data into content-type subsets, they found that opinion editorials and researched articles performed best. A further analysis of over 20K articles from The Atlantic and New Republic confirmed their findings.
It's worth mentioning that site magnitude and popularity was not a factor taken into account in this study, so further research is necessary, to determine its impact. For now, let's say that good, compelling content needs to be:
- Backed by solid data
- Long and well written
4. Reverse engineer great content with Google Analytics
The Social Media Examiner ran a podcast with analytics pro Andy Crestodina, who approached the use of Google Analytics as a tool for analysis, not just for reporting. In the podcast, he explained that people need to look at user behavior, referring domains and traffic origination devices, ask questions, and set goals for improvement. Though his advice is mostly geared toward making commercial sites better, he also touched on some great points for content marketers.
Here's some of his wisdom, summed up:
- Bounce rates don't matter, but dwell time does. As Crestodina explains, if you're getting some decent "dwell time," the fact that many of your pages get single hits becomes largely irrelevant. After all, users of educational websites come in looking for an answer, get to it, and then leave. But if 95% of them are spending under 5 seconds on your site, your content is not helping them solve their problems.
- Check out your competitors' dwell time. If you feel your content needs improvement, catching up with the Jonses is a good idea. Input your targeted keywords into Google, check out the top-ranking sites, then go to Alexa.com to see how much time users are spending there. It should be around 1 to 1:30 minutes. If that number is higher (or at least higher than yours), you should definitely consider taking a few pointers from what they're doing right.
Your goal is more subscribers. Google Analytics works with targeted goals, which you can find in the Conversions Tab > Goals > Reverse Goal Path. You can work with several simultaneous goals. When you select one from the drop-down menu at the top, the left-hand bar will show all about that goal, and the list on the left will be the content that triggered people to act on that goal. This list will show all the content and pages that people were on, right before they subscribed. Be aware that those are raw numbers, not conversion rates, so make sure to calculate that with the aid of a spreadsheet.
Once you figure out what content pieces perform well, you can choose to create similar content, up your social media game by promoting them on your platforms of choice, or push the content on your home page. The basic idea here is that though Analytics can't tell you just what your users want from you, it's a powerful tool toward figuring that out on your own.
5. Consumers don't mind trustworthy branded content
Intuitively, you'd be tempted to believe that users abhor sponsored content (or native ads). However, a couple of recent studies prove that users are not too aware of the type of content they're consuming in terms of who's paid for it. Does this mean they enjoy it? Probably not. More likely, it just means they don't pay enough attention to disclaimers or "sponsored" labels. Does it mean brands should keep pushing for native ads?
That's a tricky question. The poll results should be interpreted as a lack of interest in the underpinnings of the publication at hand for most users. If it looks like an article, reads like an article, and satisfies users' thirst for answer like one, then most users will approach it accordingly. That opens up an interesting opportunity for content marketers, which I would advise you to take with a grain of salt... If you can produce data-driven content that is useful and compelling, selling it as native advertising might be worth it. If, however, you can't justify its presence in a serious publication, you'd better not run the risk.
What's the risk, you ask? Check out the comments on this Marketing Land post. The post itself cites a poll from Contently, which revealed that respondents confuse native ads in The New York Times, BuzzFeed, and The Wall Street Journal with actual ads (see percentage breakdowns below).
As the comment section goes to show, many users surmise that sponsored content will see a sharp drop in credibility (alongside with the publishers that indulge in it) once proper disclosures become mandatory.