Strategies from Successful Companies on How to Use Machine Learning

Strategies from Successful Companies on How to Use Machine Learning

Machine learning is a huge trend. After overcoming the $1 billion mark in 2016, the machine learning technology is expected to hit Around $40 billion by 2025.

Machine learning was created by computer scientist Arthur Samuel in 1959, however, only recently has the business community come to discover its value. In the next few months, the technology will be adopted by everyone, from startups and small businesses to large and successful corporations.

The first challenge is determining a use case. You are not sure what to do and where to start?

To make the most of machine learning, consider how top companies are using it:

#1

Embrace Experiences As A Whole (Apple)

Anyone with an Apple product knows how well the devices are connected and synced. The tech leader is using machine learning technology to create an even more seamless experience for the customers. Apple filed a patent that implies that is focusing on cross-device personalization. For example, in the near future, a user’s iPhone might suggest an iTunes playlist to match his fitness goal in another app.

Any company or organization that works with smart devices can take advantage of this technology, for example, an Internet of Things company. Connecting various models with the same set of data improves the value and quality of information delivered, as well as, the customer’s experience. Devices connected cooperate like a pitcher and catcher in baseball. They are working from the same set of data meaning they can decide how to approach a specific task from opposite sides.

#2

Deliver Personalized Media (Spotify)

After the acquisition of two machine learning companies in 2017, Spotify is testing out new features for its music recommendation service.

For example, a Mashable writer, last December, noticed “like” and “don’t like” buttons in the Discover Weekly feed. Even though Spotify has been private about its plans in acquiring video recommendation business MightyTV and music personalization company Niland, it did so to refine the AI (Artificial Intelligence) stack and outperform other competitive music services.

The bet on Discover Weekly speaks to the music consumers place on music personalization, made possible thanks to machine learning innovation. Spotify is positively surprised by Discover Weekly and its huge success which was not part of the music company’s offerings when it was launched back in 2007. After Discover Weekly’s debut in 2015, services like Apple’s New Music Mix cropped up.

#3

Create the Ideal Preview (Twitter)

When someone posts an image to Twitter, he wants people to see it. However, if the thumbnail is 90% wall, nobody is going to click on the photo.

Luckily, Twitter has solved this issue by using neural networks. In a cost-effective and scalable way, the social media giant is using machine learning to crop photos into low-resolution and compelling preview photos. The result is fewer thumbnails and more funny signs above them.

For your next marketing campaign, you can give Twitter’s optimization a try. Upload user-generated and brand-aligned photos and let Twitter decide which elements of each photo boost engagement. Use the top-performing image crops for your next campaign. Let’s face it – who doesn’t love market research free of charge?

#4

Customize Customer Journeys (Alibaba)

Did you know that more than 500 million people shop with Alibaba – the Chinese retail giant? That is more than the entire population in the US. Each of these customers goes through a distinct journey, from start to end, from searching to shopping. So, how does Alibaba track and tailor each of these 500 million customer journeys? With machine learning.

Alibaba’s AI (Artificial Intelligence) should make every seller and e-tailor jealous. The virtual storefronts are completely customized for each customer. That is pretty impressive, right? The search results turn up perfect products.

The conversational bot – Ali Xiaomi handles most written and spoken customer service questions and inquiries. Every part of the business feels like it was created for the shopper engagement with it, and every move the shopper makes teaches the machine more about shopper’s preferences.

#5

Learn From Today to Invest Better in the Future (Target)

Target – the retail giant discovered that machine learning technology can be used to predict purchase behavior. But that is not all. It can also predict pregnancy.

Target’s model is so precise that it can guess which month or trimester a pregnant woman is in based on what she has purchased. After a father discovered that his 16-year-old daughter was pregnant (thanks to Target’s promotions), Target had to dial its actions by adding less specific ads.

Most promotions presented by companies are driven by the holidays or the seasons. For example, sunscreen goes on sale in June, show shovels in July, etc. Consumers go through seasons all the time. The worst time to sell someone a new car is right after he bought one. But it is the best time market car insurance to this person. Machine learning can help you with those rhythms, helping businesses recommend the products to customers when the time is right.

Machines can’t learn everything about a certain business company or its shoppers. However, companies like Alibaba, Shopify, and Apple are pushing the boundaries back further. With machine learning making innovation easier, it is up to leaders and business owners to show the brands how it is done. Here you can see more articles about 5 B2B Content Marketing Strategies Click 

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FUTURE MARKETING is a platform where you can find not only useful professional tips and reviews on digital marketing, but also useful tips from our research in areas such as Artifical Intelligence, Machine Learning.

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