– Artificial intelligence or AI has started to change many aspects of life, and marketing is definitely no exception. In fact, thanks to AI, today it’s possible to reach and engage with many more customers than ever before, cutting down on marketing costs as well as boosting sales exponentially. So, if you’re looking to take advantage of this technology in your own business, here are some great ways to do so.

So, What Exactly IS Machine Learning?
– Machine learning is defined as: “a form of artificial intelligence (AI) that allows computers to learn without being explicitly programmed”. In practice, it doesn’t sound very impressive. As most people will tell you, their computer can already learn anything — because it remembers them and all their web history after all. But in reality, machine learning goes far beyond what your laptop or computer can do. While AI was previously limited to specific tasks that were hard-coded into a program by an expert programmer, machine learning can now enable systems to solve problems based on patterns in data that have previously been recorded. The importance of programming is fading as computers learn how to solve complex issues on their own based on information they are given access to, kind of like SkyNet (hmmm..?).

Now, What Are The Benefits and Advantages of Machine Learning?
– Well, a machine learning algorithm can detect patterns in data that a human wouldn’t usually notice. For example, marketers might want an algorithm to look for clues about what sorts of emails resonate with their customers or target audiences. Rather than having a marketer read through all their existing customer emails, which could take weeks (or even years!), they could simply have an AI scan those emails and make suggestions within seconds. Similarly, an AI program might be able to recognise patterns in your website traffic such as which pages attract more readers or where on a page people are more likely to click and then you change them accordingly so you get better results — simple… right?.

A few drawbacks (and how to overcome them):
– The major drawback is that computers still don’t have common sense. They understand statistical correlations between large sets of data but struggle to apply those insights outside of a specific context. This means that a lot of work needs to go into setting up algorithms if they’re going to work WELL. That being said, recent advances have improved training time significantly by making systems smarter. Here’s an example of why we need machines now more than ever before, robots can find planets in millions of years while it takes us BILLIONS of years to do it! Today’s artificial intelligence allows us to compress our earth’s history into just three decades — which is pretty impressive. So that bodes the question, who knows what AI will allow us to do in the next 10–20 years? I am really hoping it continues to be a positive impact!

BUT There are Pitfalls in Machine Learning
– The more data a system processes, the better it gets. But if all you have is a little data, there’s no way for your machine learning algorithms to make useful predictions; there just isn’t enough information available for it to comb through and create structures for. If you train a neural network on just 10,000 examples — which might be 100 times more data than your company has on hand — it’ll take quite some time before it can accurately predict outcomes. But at least that data exists; in many industries and situations, there simply isn’t much data to work with. This leads to another problem with machine learning: BIAS. Because AI algorithms use massive amounts of training data to develop predictive models, they often inherit cultural prejudices built into that training set prior to them compiling their research. For example, because existing video games reflect our society’s long-standing biases against people who aren’t white men, artificial intelligence is then trained on existing video games which will probably never create an avatar who looks like me or anyone else who doesn’t fit society’s image of what normal should look like. So being specific and having a wide range of data for your AI to pull from is essential when creating personalised experiences in our ever-evolving world. Representation is important, but AI doesn’t know any better.

Here Are Some Approaches To Machine Learning For Marketers
– First, you need to understand which level of marketer you are — are you a product manager looking for advanced ways to find data-driven insights about your audience? Or maybe you’re a social media manager who wants to build a smart chatbot that engages customers in real-time? Maybe you’re an email marketer who wants more personalised emails? Whatever your role is, there’s an artificial intelligence solution that can help. Here are some interesting AI platforms for marketers:
1. SurveySparrow
2. Google Analytics
3. TubeMogul
4. HubSpot
5. MailChimp

And remember, even if you aren’t comfortable with programming languages or neural networks right now, there’s software out there to get you started you just need to know where to look!

So Now, How Can Marketers UTILISE Machine Learning?
– Try learning algorithms with your company’s marketing data. These strategies use artificial intelligence techniques to analyze large amounts of data and make predictions about how certain variables affect, for example, whether a customer will return or when an individual will buy something. You can then use these models to help predict outcomes as well as guide business decisions. In addition, you can even create a classifier model that provides suggestions based on previous behaviour in similar situations. This might sound high-tech, but it really doesn’t require knowledge of AI specifically; instead, it only takes time and a bit of creativity. With some basic coding skills, you could be well on your way to using machine learning!
– According to Predictive Analytics World, after taking into account market size and other factors such as cost-effectiveness and ease of adoption, machine learning is one of four top technologies marketers should start utilizing now.

So it seems to me, that now is as good a time as any for most marketers! What a time to be alive!

By Prissly Mena