When Data Just Isn't Enough: The Hidden Context that's Key to Content Loyalty

Posted by ronell-smith

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When the client asked to "go mute" during our monthly client call, there was no reason to sound the alarm. After all, being able to talk through what they've heard as a team, in private, was normal. But when the always-skeptical global marketing director said the COO (who has been in the room for the 10 minutes of analytics discussion) wants to take the discussion offline for a bit, but wants you to hold on, I knew things had likely gone off the rails.

"Thanks for holding, you guys," says the head of marketing upon taking the phone off mute after what seemed like an eternity. "Tim was just in here, and he had some questions about the data. He expressed concern that it appears [the team] is simply regurgitating a bunch of numbers."

After it was explained that the numbers actually exceeded everyone's expectations for how the site would perform after the redesign, the link detox and having new content in place, she made things crystal clear.

"Let me cut to the chase," she said. "The numbers are great. We're happy with the numbers. But this the same thing our last agency provided us: great data. What we're looking for is someone to share what the data is telling us about what to do in the future, so we can focus only on those areas that are likely to benefit the brand. We'd like to know what will help us attain success in the future, not what [your team] thinks will lead to success in the future."

What this client needed was the Oracle of Delphi, not someone to analyze their data.

But she was right. They were looking for all-important insight, insight that could not be gleaned from data alone. However, this agency and all the others she'd worked with had led her to believe the data is gospel. Follow it to the Promised Land.

She knew better.

Data alone is never enough.

Though many in online marketing prefer to see data as the be-all and end-all, at best data alone tells us what's likely to be effective in the future. It does not provide the "if this, then that" clarity we crave.

The more we share "according-to-the-data" insight, the more we walk a tightrope that never ends. Data tells us what happened, can yield great insight into what's likely to happen, and is at its best when used to discern what is happening.

However, in the real world, things change constantly and often without warning, a fact that cannot be accounted for via data alone.

"[Data] is an abstract description of reality," writes Jim Harris on his blog, Obsessive-Compulsive Data Quality. ''...The inconvenient truth is that the real world is not the same thing as these abstract descriptions of it—not even when we believe that data perfection is possible (or have managed to convince ourselves that our data is perfect)."

To be sure, data is integral to attaining success in the information-rich online marketing arena. Everything from our websites to our campaigns to conversions depends on it. In fact, data is a large part of what sets online marketing apart from traditional marketing, which can, at times, feel like so much guesswork.

But over the course of the last two years, through interviews with more than 300 folks in the content marketing/inbound marketing space, I've come to realize that many wonder if data (insofar as how it's used to make decisions) isn't as much a curse as it is a blessing.

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In conversation after conversation, I've heard CEOs, SEOs, CMOs, PPC nerds, and content folks say the same things, which is summed up nicely by these comments from a director-level SEO at one of the most successful agencies in the US: "Even in those cases where we deliver to clients data that far exceeds their expectations, they often fire us. Heck, especially when we deliver those amazing results, they fire us."

I think this occurs for one of two reasons:

1. They realize data doesn't yield the solution they'd hoped for, or
2. They falsely believe data highlights the end-game, meaning they can now thrive on autopilot.

As any of us working in online marketing can attest, nothing could be further from the truth.

Data is an important part of a large picture, one that is as nuanced and as varied as it is ever-changing.

Because of that, we need context.

"Data doesn't come with context," says Tim Gillman, an analytics nerd at Portent Interactive in Seattle. "For example: measuring content. If your data says people spend ~15 mins reading your post, there's always the chance that they simply left their computer for awhile. You don't know for certain they were loving your content."

I struggled with this reality for months, wondering what, if anything, could be done to bridge this gap, which would allow us to (a) be given the time to do quality work for our clients and (b) have clients realize the efficacy of our efforts.

I read big data and data science books, started following the words and works of big data nerds active on social media, in addition to listening to podcasts, watching YouTube videos, and talking to as many people as I could to discern how we, as online marketers, can be successful.

Training ourselves to think about data differently

In the end, it was the sage words from Harvard Business School professor Clayton Christensen that helped me gain some clarity.

Data, at best, can only tell us about the past, he writes. It cannot help us see into the future.

For that, he adds, we need a theory for helping to explain what's likely to happen. Taken together, both data and theory, serve to provide us with the building blocks of what can become the framework for success we crave.

To make this work, he says, we must go "dumpster diving" — hanging out in the real world, observing and noticing how things occur in real life — which will lead us to more effectively posit the hows (things really work) and whys (they work as they do).

Then, once we have the data, we use it to empirically assess the observed behavior, devoid of emotion.

The framework looks a lot like this:

• Observe – Dumpster-diving in the real world
• Theorize – Posit the how and the why
• Test – Assess and compile data
• Construct – Develop a framework for future efforts

With this model, we're training ourselves to think about data in a different, but no less valuable, way. In the above scenario, data is an important part of the equation; it is not treated as the equation in its entirety.

This, to my mind, gets us closer to seeing data in the proper context. That is a part of the solution. But changing how we think about data won't allow us to keep clients any better, won't immediately make us better marketers and cannot, by itself, lead to better overall decisions being made.

For that to occur, we have to change two things: the data we act upon, and how we choose to act upon it.

A framework for finding your data goalposts

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Without knowing it, Matthew Brown at MozCon 2015 provided us with the veritable playbook for how to use data to improve our content marketing efforts. During his talk, which was one of the best of the entire event, he highlighted the key to content marketing success: content loyalty.

The more loyal our audiences, the better able we are to sustain our content marketing efforts. (A loyal audience comprises the folks who most frequently visit your site.)

The key, Brown said during the talk, is to find the goalpost that helps you determine content loyalty for your brand, then optimize for that metric. So, instead of chasing Likes, shares, or links to your content, you're focused on creating loyal visitors to your site.

This is important because one of the reasons content marketers end up getting lost down the data rabbit hole is we too often chase the wrong metrics (e.g., they highlight activity but don't lead to conversions) or we attempt to track too many metrics, most of which don't lead to the goal we, or our clients, are hoping for.

Here's how such an effort could work for your brand, using the OTTC framework borrowed from Christensen's work:

• Observe
  Determine what comprises "loyal visitors" for your brand. It could be visits per day, per week, or per month. This is the crucial first step. Get this wrong and nothing else matters. What you're looking for is the metric that correlates with visitors becoming loyal to your site. Put simply, you're looking for the gotcha that says "These folks are now loyal visitors."
• Theorize
  Gather the team and spend some time thinking through what it is about your site and/or content that likely leads to these audience members becoming loyal fans and followers. Is it the length of the content? The number of images? The author? The amount of content above the fold? The number of ads?
• Test
  Use the information gleaned from that meeting with the team to begin testing the various on-page elements until you have a good idea of what it is that leads folks to become loyal. This is the fun part. To make it even more rewarding, you can rest assured that many of your competitors won't be following suit, as many of them are content to guess at what works, then throw more of the same at the wall.
• Construct
  Develop a process by which you continue to optimize for content loyalty, in large part by creating the types and formats of content that you've uncovered as leading to content loyalty. Keep in mind, however, that this process is not static, as your audience's needs are likely to change with time. But by analyzing the data, dumpster diving by interacting with the audience via emails, polls, Q&A, and sundry other methods of staying connected, your brand will be in great shape to continue putting the ball through the uprights.

Summation

This is a post I thought long and hard about writing. During this quest to better understand data and shine a light on how to make it work for us and not against us, I've developed a deep, sincere fascination for big data and the role it can play in answering some of our biggest questions.

I'm in no way anti-data. Hardly. What I'm against is the "data-tells-us-all-we-need-to-know" mindset I so often encounter.

I'm hopeful that, in the future, more and more of us are willing to be honest with ourselves and our clients, acknowledging what we know to be true: the data alone won't save us.

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