How Brands are Leveraging Machine Learning to Get more ROI

How Brands are Leveraging Machine Learning to Get more ROI

There is no doubt about it that machine learning is all the rage. For entrepreneurs who are running marketing agencies, design companies and branding agencies, to enable a large number of real world machine learning projects, it is clear that machine learning is already empowering massive changes in the way agencies operate.

It is not simply about hi-tech products such as Siri and Amazon Echo, and it is not about just being used by major brands with huge research and development budgets such as Microsoft and Google. If truth be told, in near future, almost every Fortune 500 company will be running more effectively and making more sales, just because of machine learning.

Here are a few important aspects of machine learning that are making our lives easier and better every day.

User-generated Content

Believe it or not, user-generated content (UGC) is pathetic. It is actually worse than you think. It is filled with spelling mistakes, slang, wrong information, and vulgarity. But by determining the good and bad UGC, machine learning systems can sort out the worst and come up with the best without needing a real person to correct each piece of content.

And when it comes to dealing with spam emails, machine learning helps identify spam, basically get rid of it. This is why, these days, it is quite uncommon to view your spam folder in your mailbox every morning. Same thing will be going to happen with user generated content in near future.

Let’s take a few examples here:  Pinterest uses machine learning to show more interesting pins. NextDoor uses machine learning to sift content on their message boards. Yelp uses machine learning to scrutinize photos uploaded by users and Disqus, getting the most of machine learning to discard spam content.

Finding the Desired Product/Service Quickly

It’s no wonder that as search engine, Google is always at the forefront of hiring machine learning geeks. Google recently hired an artificial intelligence expert in charge of search. The phenomenon to index such a massive database and fetch results that match the keyword has been there since 1970. But what makes Google extra special is that it knows how to show up the most relevant results that match the exact keywords. They way that it knows this secret is through machine learning.

But it is not only Google that needs machine learning to show smart search results. Web design agencies, marketing firms and branding companies also need it to improve their operations. Apple needs machine learning to show the most relevant apps in the Apple Store. Intuit needs it badly to surface a good help page when a user types in a certain tax form. Similarly, Home Depot uses it to show which bathtubs in its huge inventory will fit best in a customer’s bizarre shaped bathroom.

In addition, ecommerce businesses, including Trunk Archive and Lyst employ machine learning to show high quality content to their customers. Some other ecommerce businesses, like Edgecase and Rich Relevance, also use machine learning strategies to give their ecommerce customers the most accurate results when they are browsing for products.

More Customer Engagement

Have you noticed contact us and sign up forms are getting leaner day by day? That is another room where machine learning has helped modernize business operations. Rather than having users to fill out never ending form fields, machine learning can only search the substance of a request and direct it to the right place.

Nowadays, more and more major brands are investing in machine learning, because it helps them generate more sales and ROI. That seems like a not big deal, but having a sales inquiry resulting in a qualified lead, or a complaint end up immediately in the customer support department’s queue can save a lot of time, money and resources. Just because machine learning make sure things get prioritized and answered as fast as possible.

User Behavior and Feedback

Machine learning also excels at behavior analysis. And while customers’ feedback can often seem worthless to non-marketing folks, it can actually have the real power to drive more sales and leads.

For example, a production house puts out an official trailer of a movie for a holiday blockbuster. They can analyze social media engagement to check out what is resonate with their fans. Then makes changes in the promo immediately to surface what people are actually responding to. This marketing strategy puts audience in theaters.

Another example: a game studio announces a new title in popular video game line without a game type that their target audience were expecting. When gamers give their feedback on social media, the studio could analyze and understand the feedback/complaints. This way, the company can change their release schedule in order to add that particular feature, turning critics into fans.

Do you know how did they turn complaints into millions of shares, likes and tweets? They use the power of machine learning. And in the past few years, user engagement and customer feedback through machine learning has become standard operating system.

What to Expect

Now machine learning is everywhere. Data has now become more accessible and prevalent than ever before. Managing machine learning algorithms is somehow a bit tricky. Machine learning algorithms  most probably operate like humans. As users, we want some trickier queries to be answered. Some more advanced algorithms are expectable, let’s see how they work in near future.

Famous brands are investing in machine learning not because they are outdated or because they want to stay ahead of the competition. They invest because they know they will get more ROI. And that is the reason innovation will be continued.

Posted in Marketing
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Written by Mariya Sabeen

Mariya Sabeen Irshad @MariyaSIrshad is a Creative Writer by passion and a Content Marketing Strategist by profession – a tech-savvy who is currently associated with Branex, a digital marketing agency. With an MBA in Marketing, she holds relevant industry experience and writes about digital marketing, mobile applications, web designing, career counseling, game development and trending technology news.