Machine Learning

5 Reasons Machine Learning Is the Future of Marketing

Today's smarter business systems generally mean smarter, and more profitable, companies.
5 Reasons Machine Learning Is the Future of Marketing
Image credit: Erikona | Getty Images
Guest Writer
Entrepreneur, Lawyer, Author and Freelance writer
5 min read
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I do a great deal of research on business trends and online tools that can enhance business productivity. Naturally, I visit and monitor many websites and website content. And just as predictably, I encounter ads from those same companies on my Facebook timeline. More surprising is how well Facebook integrates search behavior and online activity to increase ad campaigns' integrity and specificity.

Machine learning can be defined as an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience (without explicitly being programmed to do so). Machine learning focuses on developing computer programs that can access data, analyze it and use it to learn.

Related: This Is the Year of the Machine-Learning Revolution

It’s not just futuristic-looking products such as Siri and Amazon Echo. And it's not limited to companies we typically think of as having huge research-and-development budgets -- the Googles, Facebooks and Microsofts. In reality, machine learning already is helping nearly every Fortune 500 company run more efficiently and make more money.

Here are five reasons companies on the up should start applying machine-learning marketing strategies on their respective scales.

1. It brings 'real time' to life.

The phrase “real time” has been touted among marketers for years, but it wasn’t really possible until machine learning showed up on the scene. No prior system came close to the level of responsivity that machine learning provides. Consumers see offers change by the minute based on the virtually unlimited data their behaviors create for machines to process. Facebook’s retargeting ads are just one example. Visit a website, and you don't need to wait long for an ad to surface on your timeline. 

"Machine learning and other cutting-edge technologies have opened new opportunities for investing their marketing budget smarter," says Rafa Jimenez, CEO of Adinton. The company is knee-deep in providing machine-learning solutions and more to businesses. "These new technologies allow companies analyze tons of data in real time, 24/7, getting deep insights. Managing big data and getting powerful and actionable insights are going to be the most important basis for any online business these days."

Related: 8 Companies Changing How Machine Learning Is Used

2. It eliminates business marketing's greatest enemy. 

Effective business marketing reaches its audience and creates conversions. The challenge lies in the very simple problem of marketing waste. For want of a better strategy, marketing campaigns have taken a trial-and-error approach. Whether online or offline, campaigns essentially scatter seed on the soil in the hopes some will take root. 

Imagine your marketing efforts were seen mainly by the people you want to see them -- people who've searched for what you have to offer, or whose online behavior suggests they're mostly likely to be interested in your products or services. Machine learning has the potential to reduce much of marketing's imprecise nature. Using behavioral data, marketers can target their audiences in an efficient way that greatly improves the likelihood of converting shoppers to customers. 

Related: 10 Ways to Learn About Your Target Audience

3. It opens the door to marketing prophecy.

Professionals have flirted with marketing prophecy, or demand forecasting, over the years. In many cases, this planning has been accomplished based on trends and consistent purchase patterns. Adopting AI for marketing purposes offers decision-makers something more concrete: the overwhelming possibility to give customers what they want before they know they want it. These efforts still will be mostly suggestions. But they'll be informed by data, not presented as blind suggestions to a disinterested consumer. 

Renowned developer Kevin Carroll put it this way: "Much of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations and much more."

Related: Forecasting Is Hard, But It's Harder to Run a Business Without Doing It

4. It helps structure marketing content.

Copywriters use the insights at their company's or client's disposal to craft advertisements and email marketing campaigns that speak to the target audience. To a large extent, though, these skilled persuasive writers must work with a blanket approach and plenty of educated guesses.

Machine learning narrows down the bracket. Then, it goes one better: It provides actual means of sentiment analysis so marketers know what to say and how the audience is likely to react. The effects of sentiment analysis are laid bare on Twitter, where marketers can monitor social chatter to see what’s resonating with a specific target audience. Brand specialists and copywriters then can tweak ads immediately in response to comments and trending replies. This brings the right message to the surface.  

Related: Connecting With Your Customer Is What Drives Relationship Marketing

5. It reduces costs.

Now that the world has moved almost completely online, machine learning can adapt to handle some of marketing's toughest challenges. Cost always is near the top of that list. 

Machine learning reduces marketing expense because it requires far fewer people to be involved. It also drastically cuts communication costs, as a majority of customers can be kept updated on offers via automatic emails, scheduled social-media posts and online ads or other content. 

Machine learning's precision informs production and distribution for offline materials, too. This allows marketers to pinpoint the right quantity and use the most effective channels, reducing excessive costs related to overproduction.

Related: 10 Facebook Messenger Chatbot Marketing Expert Tips

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