3 Ways Machine Learning Makes Your Content More Effective
Recently, an AI from Deep Mind called Alpha Go beat the 5th ranked Go player in the world, a feat that most thought was about a decade off. That’s the way things are going these days in the world of machine learning and artificial intelligence.
Deep Mind is a cutting edge AI company recently bought by Google and now owned by Alphabet, the holding company created by Google shortly after this purchase. It’s one of many companies these days at the forefront of trying to teach computers how to think like humans.
The learning that goes into teaching a computer how to win at Go isn’t directly translatable into practical, day-to-day tasks like writing blog posts, but that doesn’t mean that smart startups aren’t learning from the big guys how to apply machine learning to solve many of the problems we face in our working lives…
1. Machines Write the Rote Stories We Need in Quantity
Like writing blog posts. Not that writing blog posts is ever a problem, per se, but with the sheer amount of content being produced set to increase by 500% by 2020, there is a bit of a problem in the demand side of things.
Enter machine learning. You may or may not have noticed that at least some of the content you consume each day has been written by a machine. Currently, many of the major news sites are using machines to write data-rich stories from sports reporting to business articles.
2. Machines Can Help You Target Your Audience
The fact that machines can help us out by writing the easy-to-write data-rich stories we need in quantity does not mean that we don’t need writers. Humans crave story, and though a machine can take what humans have written and learn a model to create similar stories, a machine isn’t going to understand the nuances in the human mind well enough to write compelling content.
That’s for us to do. Luckily, the dedicated folks at Atomic Reach have a suite of tools that greatly enhance your content by helping you define your audience in such a granular way that you can begin to know exactly how (and when!) to write for them.
You no longer have to either guess or spend hours mining the data yourself to figure out exactly what your audience likes to read from you. That information is pure gold, and can make the difference between content marketing and effective content marketing.
3. Machines Can Help You with Content Ignition
Mark Shaffer coined the term “content ignition” to mean that area of content marketing where people actually see and read your stuff. No longer can you simply write great stuff, make sure you’ve got a few keywords in there, and expect it to reach millions. Writing great content is the start to an effective marketing campaign, but it is just the start.
You need to make sure people are going to see what you wrote — and read it and share it, too. That comes down to an effective content promotion strategy. And this, more and more, can be made more effective through machine learning.
You are probably aware of Outbrain, Taboola, Adblade and others like it? Well, enter the likes of Keywee. Keywee reads your content, understands it, matches it with the best audience for that content and, voila, you’ve got your ideal content distributed to a wide audience.
Why Should You Care?
Well, I’d say you should care because, if you are a content creator, your life is going to get a lot better in the future. The advent of the machine learning age is here, and for many industries from healthcare to finance, innovations are already beginning to change the way things are done.
Content creation is just one of many industries benefitting from machine learning. In the next few years, we’re going to see our jobs made more creative and interesting — and much more effective — through the use of machines who have learned from the massive data sets we can feed them. Welcome to the future.
About the Author:
Wendy Kelly is a content strategist living and skiing in a small mountain town in British Columbia who enjoys storytelling and strategy. Imagine that. You can follow her at @WendyKKelly.