How Is Artificial Intelligence & Machine Learning Used in Marketing?
There's no mistake that the topic of artificial intelligence has been showing up more and more in your newsfeed. It isn't just the people you are following, this technology is the hot topic everywhere and it doesn't seem to be cooling off.
WHAT IS Artificial intelligence AND MACHINE LEARNING?
Artificial intelligence (AI) is essentially intelligence displayed by machines. It is the study of agents (computer programs or hardware with a sensor and actuators) that perceive the world around them, form plans, and make decisions to achieve their goals.
Machine learning is a subset of AI and generally entails teaching a machine how to do a particular thing by feeding it large amounts of data and then directing it to make predictions on new data. Its goal is to enable computers to learn on their own by identifying patterns in observed data, building models that explain the world, and predicting things without having explicit pre-programmed rules and models. The big deal about machine learning now is that it's getting easier to invent software that can learn over time and get smarter as it accumulates more and more data.
"But definitely don’t think of this as futuristic. Don’t be put off by the science fiction movies whether, you know, the Terminator or other AI shows. That’s not what’s going on. It’s a bunch of very specific practical applications that are completely feasible."
-Erik Brynjolfsson, MIT Sloan School professor
Despite making great strides in recent years, the AI field got its start in the 1950s when John McCarthy, a math professor at Dartmouth College, issued a 2-month research project. The study was to "proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it."
Over the next few years AI research labs popped up at the Massachusetts Institute of Technology (MIT) and Stanford University, mainly focusing on developing algorithms for computer chess, robotics and natural-language communication. During the mid-1980s, interest was waning and only a few startups and venture capitalists were backing further research. It wasn't until the twenty-first century that computer technology and hardware became powerful enough that the extremely large data sets and complex AI computations could be calculated in reasonable time, causing interest to surge again.
In 2012 Google made headlines after they "trained" a neural network with 16,000 central processing unit (CPU) chips on 10 million images from YouTube videos and taught it to recognize cats. That same year, image recognition made a huge leap after a company called DNNresearch created an eight-layer neural network on two graphics processing units (GPUs) to accurately classify images based on their content.
Since then, AI activity has only accelerated, with the world's top technology companies leading the way.
“Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the web. It would understand exactly what you wanted, and it would give you the right thing.”
-Larry Page, CEO of Alphabet, former CEO of Google
I'll never forget that first time I waited for my Facebook photo feed to load when I saw this small type in the corner of the picture: "Image may contain two smiling people and a dog". Then the picture loads and there are 2 smiling people with a dog in their arms. What?! How did Facebook know? Enter AI to social media and pictures.
According to the Head of Growth of HubSpot Labs, Sam Mallikarjunan says visual content will have an increasing influence on SEO, as he noted, “search engines are getting good at knowing what a video, audio clip, or image is actually about.” Visual content creators and marketers need to up their SEO game to make sure keyword targeting, descriptions, tags, and other items are in place and optimized.
Google’s AI, RankBrain, uses AI to attempt to understand the context of content on websites. As Google gets better at analyzing searcher intent, it’s more important than ever to get our keyword research right, and then tie those keywords back into our content.
AI is also used in marketing automation to engage customers, analyzing their behavior and delivering tailored content to move them through the sales cycle. This is done by recommending content, engaging with them through social media or using tailored email campaigns.
MACHINE LEARNING WITHOUT THE MACHINES
While tech giants like Google, Microsoft and Facebook have made rapid progress implementing machine learning, you don't have to be a big business to jump into the AI realm. By keeping track of frequently asked questions in chatrooms, or in emails your company receives, you can see patterns of what is on your audience's mind. Pair that with monitoring how your sales team responds to those FAQs and which of their responses led to more sales or a positive encounters and you have a bare-bones way of pulling in data to find which patterns of phrases and answers were the most successful.
And, being able to put all that data into a machine learning algorithm which gives you those patterns is even easier.
“By far, the greatest danger of Artificial Intelligence is that people conclude too early that they understand it.”
—Eliezer Yudkowsky, AI researcher
But just having the data or the AI technology doesn't improve business on its own. Humans using these new systems must adapt to work with or eliminate the patterns that are uncovered. Take the time to find which of your targeted ads are actually targeting the right people, invest more thought into keywords and how your website is centered around a main topic, develop a link building plan. Or consider using a marketing automation platform or find an agency that specializes in this.
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