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Optimization On The Content Battleground: Human + Machine Learning
When it comes to search engine optimization, only one website can win the battle for top spot. Columnist Jim Yu argues that winning this battle means relying on machine learning to analyze and interpret data.
Search engine optimization represents a battle for content visibility — one brand’s loss is another’s gain.
Among the obstacles that stand in the way of claiming a larger share of search visibility, I would argue that the main ones have to do with the quality of data marketers are relying on right now.
Machine Learning Can Revolutionize Content Optimization
Data needs a revolution. There’s just too much data for humans to sift through and make sense of, so we need technology to tell us when something is happening and why it’s happening.
Even though the human brain can hold the equivalent of a million gigabytes of memory, it’s not our brain’s job to solve digital marketing problems 24 hours a day — especially when we’re up against the 40 trillion gigabytes that will be a part of the digital universe come 2020, according to IDC.
So, even if you have a team of data analysts on staff, the way we are processing all this data is, by and large, creating more work rather than making things simpler.
That’s where machine learning comes in. In a nutshell, machine learning is the act of a machine producing insights without being told (programmed) what to do.
Machine learning in the marketing world is like “smart” analytics, where insights are derived and presented based on the machine’s understanding of the data over time. Recommended products on an e-commerce site is one example of machine learning in action.
Beyond First-Party Data
Scott Brinker over at Chief Marketing Technologist shared an infographic that showed the saturation of analytics and marketing technology providers. This infographic highlighted more than 1,800 companies — and it wasn’t even a full list of what’s out there.
Of those providers, many of them are simply providing insights on first-party data and offering analytics solely driven by human interaction. And this is one of the problems with the data we rely on.
Marketers shouldn’t have to rely solely on first-party data to make crucial marketing decisions. (For the purposes of this discussion, “first-party data” refers to website analytics data.)
Your website analytics can tell you how well your website is doing and how many of your marketing channels interacted with one another for a conversion on the site. What this data doesn’t tell you, however, is what else is happening on the larger battleground for search engine results page real estate.
In other words, your website analytics may be telling you everything is running smoothly, yet you still can’t account for that drop in sales. Could it be something your competition is up to? If so, how would you know?
Targeting The Competition And Audience Demand
In the battle that is content optimization, we want to create the most relevant content targeted to demand. While we know we’re in it for the long haul when it comes to content visibility, we can make our strikes more precise by:
- Better understanding the demand
- Better understanding the competition’s strategy
First, marketers need to be able to understand exactly what content topics are driving the right search demand for their brand. We need to target those topics in our content production efforts, and optimize for those in search.
Second, we need to understand who the true competition is. Who your competition is offline is not necessarily who your competition is online, and your competition will change based on the products or topics you’re targeting.
Marketers need the insights that can assess what their true competition is up to online and present those recommendations swiftly in order for brands to win the content battle in search.
Then comes refining our efforts based on what we’ve learned. In a recent thought leadership paper on content performance, Jung Suh, VP of digital channels at SAP stated:
We are constantly creating and refining our content. With the right tools and processes, this is more exciting than daunting. We can see where our content is falling short, identify gaps and zero in on emerging opportunities. Content performance measurement is absolutely key. Otherwise, how would we know if our money is well spent?
Marketers + Machines
Most of the data we’re relying on today as marketers has a fundamental flaw that’s distracting us from the big picture: what is happening out there on the content battleground.
Machine learning helps marketers understand all the content across the Web and can provide actionable insights automatically. This is key because we simply can’t conceive all of it solely based on human programming and analysis.
Digital marketing today is very labor intensive, often requiring marketers to dig through data that may not even be giving us the big picture. Right now, all businesses could use those extra hours per month spent analyzing data to spend on creating the content that is going to move the needle.
In the content battleground, the right strategy is the foundation, and data-based tactical implementation is what wins the war.
Some opinions expressed in this article may be those of a guest author and not necessarily Search Engine Land. Staff authors are listed here.