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.
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.
“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.”
2. It eliminates business marketing’s greatest enemy.
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.
3. It opens the door to marketing prophecy.
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.”
4. It helps structure marketing content.
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.
5. It reduces costs.
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.