Content marketing automation: the age of artificial intelligence
We’ve had robots building cars on assembly lines way before they could drive them. Likewise, marketers have so far been able to automate basic repeatable tasks but the creative or strategic parts of marketing – which include content – have benefited only minimally from advancements in automation. It’s only now that they can finally start to turn to artificial intelligence (AI) systems to help them not just work faster but also work smarter.
A brief history of automation and marketing
Twenty plus years ago, I created a machine-learning neural network that was designed to predict which stocks were most likely to rise in the next 12 months. The bot – though we didn’t call it that at the time – crunched thousands of data points on stock performance, company financials and economy trends to learn correlations that no human beings could establish. At least in theory. In reality, I’m not sure what the system really understood but I did. I realized that it would take a few more decades before AI could do the job of a stock market portfolio manager.
Three years later, I worked on a different kind of automation as an industrial engineer manufacturing mobile phones. We used automation to build electronic boards, assemble mobile devices and even test them for quality assurance purposes. Even in the 90’s, this wasn’t experimental science. It was simply the only way we could afford to produce mobile phones in Western Europe (and even that proved not to be enough a few years down the road).
Five years ago, I started to look at marketing as a tech entrepreneur on the hunt for problems to solve. I quickly recognized the same patterns of how automation and technology had been applied:
The assembly line robot equivalent, capable of processing simple repeatable tasks faster and with greater precision than humans, already existed. It was – and still is – called marketing automation . Companies like Marketo or HubSpot have made marketing automation widely available. And like the younger me desperately trying to compete with Chinese mobile phone manufacturers, every experienced marketer now leverages this kind of automation to grasp as much attention they can from their volatile target audience.
The intelligent and self-learning piece was non-existent or experimental at best. I couldn’t find marketers who told me they were using machine learning or even simpler form of AI like expert systems in their daily marketing operations.
Why automation alone is not enough when it comes to content
Image by Fred & Lori Snyder
With time, the first kind of automation extended to social media. Beyond systems to send a multitude of emails through various workflows, software like HootSuite enabled marketers to schedule tweets or Facebook posts in advance and across multiple channels. Whether it’s email or social, the core feature in these systems is pretty much the same:
IF (Conditions) THEN (Send / Publish)
Example conditions would be data from an individual contact meeting certain criteria or visiting a certain page. In this situation, a specific email would be sent to that contact. Another example would be the condition “when a certain time is reached”, whereby a certain social post or DM would be sent. You can elaborate on the conditions and publishing channels, and even get conditions somewhere to publish somewhere else thanks to services like IFTT or Zapier, but it’s still the same linear conditional trigger.
For content marketers, automation is necessary but it’s not sufficient . Sure, content needs to be distributed and automation helps distribute it across various channels at multiple times. But the content marketing cycle is more complex than “create, publish, repeat”. In particular:
This basic type of automation doesn’t help with content creation. You can not “if-then-that” a blog post.