SEO News

Posted by KelseyLibert

[Estimated read time: 9 minutes]

In a recent Whiteboard Friday about 10x content, Rand said to expect it to take 5 to 10 attempts before you’ll create a piece of content that’s a hit.

If you’ve been at the content marketing game for a while, you probably agree with Rand. Seasoned content marketers know you’re likely to see a percentage of content flops before you achieve a big win. Then, as you gain a sense for why some content fails and other content succeeds, you integrate what you’ve learned into your process. Gradually, you start batting fewer base hits and more home runs.

At Fractl, we regularly look back at campaign performance and refine our production and promotion processes based on what the data tells us. Are publishers rejecting a certain content format? Is there a connection between Domain Authority (DA) and the industry vertical we targeted? Do certain topics attract the most social shares? These are the types of questions we ask, and then we use the related data to create better content.

We recently dug through three years of content marketing campaigns and asked: What factors increase content’s ability to earn links? In this post, I’ll show you what we found.

Methodology

We analyzed campaign data from a sample of 345 Fractl campaigns that launched between 2013 and 2016. To compare linking performance, we set benchmarks based on the industry averages for links per campaign from our content marketing agency survey: High success (more than 100 placements), moderate success (20–100 placements), and low success (fewer than 20 placements).

We looked at the relationship between the number of placements and the content’s topic, visual assets, and formatting. “Placement” refers to any time a publisher wrote about the campaign. In terms of links, a placement could mean dofollow, cocitation, nofollow, or text attribution.

Which content elements can increase link earning potential?

The chart below highlights the largest differences between our high- and low-success campaigns.

We found the following characteristics were present in content that earned the most links:

1. Highly emotional
2. Broad appeal
3. Comparison
4. Pop culture-themed

The data confirmed our assumptions about why some content is better than others at attracting links, as all four of the above characteristics were present in some of our biggest hits. As an example, our Women in Video Games campaign checked all four of those boxes.

It paired a highly emotional topic (body image issues) with a strong visual contrast. It also included a pop culture theme that appealed to a niche audience (video game fans) while also resonating with a broader audience. To date, this campaign has amassed nearly 900 placements, including links from high-authority sites such as BuzzFeed, Huffington Post, MTV, and Vice Motherboard.

Read on for more takeaways on how to increase your content’s link-earning potential.

Content that evokes a strong emotional response is extremely effective at earning links.

Emotional impact was the greatest differentiator between our most successful campaigns and all other campaigns, with those that secured over 100 placements being 3 times more likely to feature a strong emotional hook than less successful campaigns.

Example: The Truth About Hotel Hygiene

Our Truth About Hotel Hygiene earned more than 700 placements thanks to a high “ick” factor, which gave it emotional resonance paired with universal interest (most people use hotels). We’ve also found including an element of surprise helps strengthen the content’s emotional impact. This study definitely surprised readers with a shocking finding: The nicest hotels had the most germs.

Example: Perceptions of Perfection

In our Perceptions of Perfection campaign, audiences were surprised to see drastically how designers altered a woman’s photo to fit their country’s standards of beauty. The surprise factor added an additional layer of emotionality to the already emotional topic of women’s body image issues, which helped this campaign get nearly 600 placements.

Choose content topics with wide appeal to increase potential for high-quality links.

So we’ve proven emotionally provocative content can attract a lot of links, but what about high-quality links? We found a correlation between high average domain authority and content topics with mass appeal. Broad topics appeal to a greater range of publishers, thus increasing the number of relevant high-authority sites your content can be placed on.

Some verticals may have an advantage when it comes to link quality too. Campaigns for our travel, entertainment, and retail clients tend to have a high average domain authority per placement since these verticals naturally lend themselves to content ideas with mass appeal.

Some examples of campaign topics with a DA-per-placement average above 55:

• Cities That Hate Tourist
• Most Googled Brands in Each State
• Data Breaches by State and Sector
• Airline Hygiene Exposed
• Deadliest Driving States

Pro tip: A site’s influence matters more than the type of link you’ll acquire from it. Don’t fear nofollow links; for two of our best-performing campaigns of all time, the initial links were nofollows from high-authority sites. A nofollow link on a high-authority site can lead to syndication on hundreds of other sites that will give dofollow links.

Use rankings and comparisons to fuel online discussion.

Contrast was a recurring theme in our high-performing campaigns, with strong contrasts achieved through visual or numerical comparisons. More than half of our highest-performing campaigns centered around a ranking or comparison, compared to just a third of our lowest-performing campaigns. Pitting two or more things against one another fuels discussion around the content, which can lead to more placements.

Example: Comparing Siri, Cortana, and Google Now

Comparing Cortana was a hands-on study for which participants gave a command to their virtual assistant and rated their satisfaction with the response. Comparing the three most widely used smartphone assistants attracted the attention of techies (especially Apple fans) as well as the broader public, since most people have one of these assistants on their smartphone.

Example: Airport Rankings

The Airport Rankings campaign looked at which airports offered the best and worst experiences, based on data including the volume of canceled flights, delays, and lost luggage. Local publishers loved this campaign; many focused on the story around how their regional airport fared in the rankings. Since most travelers have lived through at least one terrible airport experience, the content was extremely relatable too.

Pro tip: Side-by-side visualizations pack a high-contrast visual punch that helps drive linking and social shares. This type of contrasting imagery is extremely powerful visually since it’s easy to process. It helps evoke an immediate response that quickly engages viewers.

Incorporate a geographic angle to earn international or regional links.

Did you notice a majority of the broad-topic campaigns with a high domain authority listed above also had a geographic angle? In addition to broad appeal, geography-focused topics help attract interest from international and regional publishers, thus securing additional links.

Example: Most Popular Concert Drugs

The Most Popular Concert Drugs, one of our most successful campaigns to date with nearly 1,900 placements, examined the connection between music festivals and drug mentions on Instagram. Many global sites featured the story for its worldwide festivals, including publishers in the U.K., France, Italy, Australia, and Brazil. Had we limited our selection to U.S. festivals, it’s doubtful this campaign would have attracted as much attention.

Example: Most Instagrammed Locations

As with the example above, pairing a geographic angle with Instagram data proved to be a winning formula for the Most Instagrammed Locations campaign. We featured the most Instagrammed places in both the U.S. and Canada, which helped the campaign secure additional coverage from Canadian publishers.

Pro tip: To extend a campaign’s reach to the offline world, consider pitching relevant TV and radio stations with geo-themed content that offers new data; traditional news outlets seem to love these stories. We’ve had multiple geo-focused campaigns featured on national and local news stations simply because they saw the story getting covered by online media.

Include pop culture references to pique audience interest.

Our campaigns with more than 100 pickups were nearly twice as likely to incorporate a pop culture theme than our campaigns with fewer than 20 pickups. Content that ties in pop culture is primed for targeting a niche of dedicated fans who will want to share and discuss it like crazy, while it simultaneously resonates on a surface level for many people. Geek-culture themes, such as comic books and sci-fi movies, tend to attract a lot of attention thanks to rabid fan bases.

New School vs. Old School

Trending pop culture phenomena are best for making your content feel relevant to the current zeitgeist (think: a Walking Dead theme that appeals to fans of the show while also playing up the current cultural obsession with zombies).

On the other hand, old school pop culture references are effective for creating strong feelings of nostalgia (think: everything in BuzzFeed’s ’90s category). If your audience falls within a certain age bracket, consider what would be nostalgic to them. What did they grow up with, and how can you weave this into your content?

Example: Fictional Power Sources

Fictional Power Sources looked at which iconic weapons, vehicles, and superpowers featured in movies were the most powerful. Rather than focusing on one movie, we featured a handful of popular movies — including Star Wars, Back to the Future, and The Matrix — which increased it the campaign’s appeal to movie fans.

Example: Sitcom Cribs

Sitcom Cribs looked at the affordability of the living spaces on various TV shows — could the “Friends” characters really afford their trendy Manhattan digs? By featuring a lot of older TV shows, this campaign had a high nostalgia factor for audiences familiar with classic ’90s sitcoms. Including newer TV shows kept the campaign relevant to younger audiences too.

Pro tip: To increase the appeal, feature a range of pop culture icons as opposed to just one, such as a list of movies, musicians, or TV shows. This adds to the range of pop culture fans who will connect with the content, rather than limiting the potential audience to one fan base.

Earning high-quality links is just one benefit of creating content that incorporates high emotionality, contrast, broad appeal, or pop culture references. We’ve also found these characteristics present in our campaigns that perform well in terms of social sharing.

In particular, emotional resonance is a key ingredient, not only for earning links but also for getting your content widely shared. Our campaigns that received more than 20,000 social shares were 8 times more likely to include a strong emotional hook than campaigns that received fewer than 1,000 shares.

How can you ensure these elements are incorporated into your content, thus increasing its linking and sharing potential? In a previous post, I walk through exactly how we create campaigns like the examples I shared above. Check it out for a step-by-step guide to creating engaging, highly shareable content.

What observations have you made about your most successful content? I’d love to hear your thoughts on which content elements attract the most links and shares.

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Posted by Dr-Pete

[Estimated read time: 7 minutes]

Four years ago, just weeks before the first Penguin update, the MozCast project started collecting its first real data. Detecting and interpreting Google algorithm updates has been both a far more difficult and far more rewarding challenge than I ever expected, and I’ve learned a lot along the way, but there’s one nagging question that I’ve never been able to answer with any satisfaction. Can we use past Google data to predict future updates?

Before any analysis, I’ve always been a fan of using my eyes. What does Google algorithm “weather” look like over a long time-period? Here’s a full year of MozCast temperatures:

Most of us know by now that Google isn’t a quiet machine that hums along until the occasional named update happens a few times a year. The algorithm is changing constantly and, even if it wasn’t, the web is changing constantly around it. Finding the signal in the noise is hard enough, but what does any peak or valley in this graph tell you about when the next peak might arrive? Very little, at first glance.

It’s worse than that, though

Even before we dive into the data, there’s a fundamental problem with trying to predict future algorithm updates. To understand it, let’s look at a different problem — predicting real-world weather. Predicting the weather in the real world is incredibly difficult and takes a massive amount of data to do well, but we know that that weather follows a set of natural laws. Ultimately, no matter how complex the problem is, there is a chain of causality between today’s weather and tomorrow’s and a pattern in the chaos.

The Google algorithm is built by people, driven by human motivations and politics, and is only constrained by the rules of what’s technologically possible. Granted, Google won’t replace the entire SERP with a picture of a cheese sandwich tomorrow, but they can update the algorithm at any time, for any reason. There are no natural laws that link tomorrow’s algorithm to today’s. History can tell us about Google’s motivations and we can make reasonable predictions about the algorithm’s future, but those future algorithm updates are not necessarily bound to any pattern or schedule.

What do we actually know?

If we trust Google’s public statements, we know that there are a lot of algorithm updates. The fact that only a handful get named is part of why we built MozCast in the first place. Back in 2011, Eric Schmidt testified before Congress, and his written testimony included the following data:

To give you a sense of the scale of the changes that Google considers, in 2010 we conducted 13,311 precision evaluations to see whether proposed algorithm changes improved the quality of its search results, 8,157 side-by-side experiments where it presented two sets of search results to a panel of human testers and had the evaluators rank which set of results was better, and 2,800 click evaluations to see how a small sample of real-life Google users responded to the change. Ultimately, the process resulted in 516 changes that were determined to be useful to users based on the data and, therefore, were made to Google’s algorithm.

I’ve highlighted one phrase — “516 changes”. At a time when we believed Google made maybe a dozen updates per year, Schmidt revealed that it was closer to 10X/week. Now, we don’t know how Google defines “changes,” and many of these changes were undoubtedly small, but it’s clear that Google is constantly changing.

Google’s How Search Works page reveals that, in 2012, they made 665 “improvements” or “launches” based on an incredible 118,812 precision evaluations. In August of 2014, Amit Singhal stated on Google+ that they had made “more than 890 improvements to Google Search last year alone.” It’s unclear whether that referred to the preceding 12 months or calendar year 2013.

We don’t have a public number for the past couple of years, but it is incredibly unlikely that the rate of change has slowed. Google is making changes to search on the order of 2X/day.

Of course, anyone who has experience in software development realizes that Google didn’t evenly divide 890 improvements over the year and release one every 9 hours and 51 minutes. That would be impractical for many reasons. It’s very likely that releases are rolled out in chunks and are tied to some kind of internal process or schedule. That process or schedule may be irregular, but humans at Google have to approve, release, and audit every change.

In March of 2012, Google released a video of their weekly Search Quality meeting, which, at the time, they said occurred “almost every Thursday”. This video and other statements since reveal a systematic process within Google by which updates are reviewed and approved. It doesn’t take very advanced math to see that there are many more updates per year than there are weekly meetings.

Is there a weekly pattern?

Maybe we can’t predict the exact date of the next update, but is there any regularity to the pattern at all? Admittedly, it’s a bit hard to tell from the graph at the beginning of this post. Analyzing an irregular time series (where both the period between spikes and intensity of those spikes changes) takes some very hairy math, so I decided to start a little simpler.

I started by assuming that a regular pattern was present and looking for a way to remove some of the noise based on that assumption. The simplest analysis that yielded results involved taking a 3-day moving average and calculating the Mean Standard Error (MSE). In other words, for every temperature (each temperature is a single day), take the mean of that day and the day on either side of it (a 3-day window) and square the difference between that day’s temperature and the 3-day mean. This exaggerates stand-alone peaks, and smooths some of the noisier sequences, resulting in the following graph:

This post was inspired in part by February 2016, which showed an unusually high signal-to-noise ratio. So, let’s zoom in on just the last 90 days of the graph:

See peaks 2–6 (starting on January 21)? The space between them, respectively, is 6 days, 7 days, 7 days, and 8 days. Then, there’s a 2-week gap to the next, smaller spike (March 3) and another 8 days to the one after that. While this is hardly proof of a clear regular pattern, it’s hard to believe the weekly pacing is entirely a coincidence, given what we know about the algorithm update approval process.

This pattern is less clear in other months, and I’m not suggesting that a weekly update cycle is the whole picture. We know Google also does large data refreshes (including Penguin) and sometimes rolls updates out over multiple days (or even weeks). There’s a similar, although noisier, pattern in April 2015 (the first part of the 12-month MSE graph). It’s also interesting to note the activity levels around Christmas 2015:

Despite all of our conspiracy theories, there really did seem to be a 2015 Christmas lull in Google activity, lasting approximately 4 weeks, followed by a fairly large spike that may reflect some catch-up updates. Engineers go on vacation, too. Notice that that first January spike is followed by a roughly 2-week gap and then two 1-week gaps.

The most frequent day of the week for these spikes seems to be Wednesday, which is odd, if we believe there’s some connection to Google’s Thursday meetings. It’s possible that these approximately weekly cycles are related to naturally occurring mid-week search patterns, although we’d generally expect less pronounced peaks if change were related to something like mid-week traffic spikes or news volume.

Did we win Google yet?

I’ve written at length about why I think algorithm updates still matter, but, tactically speaking, I don’t believe we should try to plan our efforts around weekly updates. Many updates are very small and even some that are large on average may not effect our employer or clients.

I view the Google weather as a bit like the unemployment rate. It’s interesting to know whether that rate is, say, 5% or 7%, but ultimately what matters to you is whether or not you have a job. Low or high unemployment is a useful economic indicator and may help you decide whether to risk finding a new job, but it doesn’t determine your fate. Likewise, measuring the temperature of the algorithm can teach us something about the system as a whole, but the temperature on any given day doesn’t decide your success or failure.

Ultimately, instead of trying to predict when an algorithm update will happen, we should focus on the motivations behind those updates and what they signal about Google’s intent. We don’t know exactly when the hammer will fall, but we can get out of the way in plenty of time if we’re paying attention.

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!