7 Ways to Use Machine Learning in Marketing

Irfan Ahmad

Machine learning can automate, streamline, and enhance many processes in digital marketing, such as email marketing, social media, messaging, and influencer outreach.

Machine learning has become a buzzword — and rightly so. The capacity to analyze big data in-house is at the cusp of transforming many industries today. Digital marketing is no exception. 

Whether you want to generate more traffic to your website, engage your customers on social media, boost conversions on e-commerce sites, or delight existing customers by delivering a personalized experience, machine learning can help with all that and more.

In order to succeed in today’s rapidly evolving digital marketing world, you have to rely on:

  • Personalization
  • Automation
  • Optimization
  • Analytics

Machine learning can help you with all four of these things and let you achieve your marketing goals.

In this article, you will learn about seven ways in which machine learning can enhance the effectiveness of your digital marketing efforts.

7 Marketing Processes Enhanced by Machine Learning 

  • Personalize Your Communication
  • Create the Right Content
  • Automate Your Marketing
  • Make Your Advertising Smarter
  • Automate Your Email Marketing Campaigns
  • Streamline Social Media Marketing
  • Boost Influencer Marketing

1. Personalize Your Communication

With so many brands vying for customer attention, your brand voice can easily drown in the sea of noise. One way you can make your brand stand out is by offering personalized customer experiences. Machine learning can help you with that.

One of the best examples in this regard is Netflix. Netflix has a global audience, so they don’t rely on ratings when showing results. Instead, they use machine learning to show personalized rankings, image selection, search, and even messaging depending on where the user is accessing the platform. 

Moreover, Netflix uses machine learning to offer content recommendations that users are most likely to love. E-commerce businesses also use this technology to earn money online by offering relevant product recommendations.

2. Create the Right Content

Not only does machine learning help with finding and curating content, but it can also help content marketers in creating the right content. With AI at your disposal, your content team will be able to select the right topics and scale your content creation efforts. 

That way, you can take advantage of the latest content marketing trends without risking your underlying ROI. You can also test content, images, and other related elements on your website and optimize them for the best results.

All in all, additional data supplied by machine learning can help you in creating a more customer-oriented content strategy.

3. Automate Your Marketing

Automated marketing tools have become more popular as they deliver more leads and conversions. Nearly 4 out of 5 marketing automation users has increased their leads, and 77% of users have lifted their conversions. 

While B2B marketers prefer to use marketing automation to grow high-quality leads and revenue, many are looking for side benefits as well, such as:

  • Automating retention and onboarding programs (14% of marketers list this as a third priority).
  • Measuring the impact of marketing campaigns against the company’s bottom line (20% list this as a third priority).
  • Aligning sales and marketing efforts to ensure mutual success (20% list this as a second priority).
  • Better understanding how customers behave in the digital world (14% list this as a second priority)
digital marketing statistics from statista

Marketing automation tools leverages machine learning to identify patterns and offer useful and actionable insights on customer segmentations, content targeting, and much more. With this data, a marketing department’s decision-making process becomes much easier, and your insights continue to get better through continuous learning.

4. Make Your Advertising Smarter

With declining organic reach, many businesses have no choice but to rely on paid advertising to get their message heard. There are several factors that you should consider before running ads, including:

  • Advertisement channels
  • Timing
  • Advertisement space
  • Duration of ad and ad campaign

Google Ads uses machine learning for its smart bidding to automate bids and arrange them for higher conversions. This not only saves your time but also increases your return on investment (ROI). You can also use machine learning to show the right ads to the right people.

5.  Automate Your Email Marketing Campaigns

Email marketing is still an effective way to target your customers. When you combine email marketing automation tools with machine learning, it becomes a potent weapon in your digital marketing arsenal. These tactics will increase your click through rate, open rates, and engagement.

With machine learning, you can learn useful data about user preferences. This data can let you target even your passive customer personas and segments more effectively through email marketing campaigns. You can also automate the whole process by setting the time, recipient, and other details. 

AI can even help you write more compelling emails. Which subject lines engage your user base? Does an extra image gain you more clicks? What color should your call-to-action be? Does your copy really connect with your customers? Machine learning can take your A/B testing to the next level, unlocking the right emails that your target audience cannot resist.

6.  Streamline Social Media Marketing

Just like in email marketing, machine learning can also help you make a more efficient social media strategy for your business.

Machine learning lets you schedule posts and create user segments based on data so that you go live at the best times and are visible to your target audience. Its ability to analyze and identify patterns from huge data sets makes machine learning a great social listening tool as well. 

Marketers in the B2C and B2B pipeline already target different platforms to reach their customers. B2C marketers are more likely to use Facebook, Instagram, and Pinterest to reach their audience while their B2B counterparts flock to LinkedIn.

How Marketers Use Social Media % of B2B marketers that use Facebook, Twitter, YouTube, LinkedIn, and other platforms.

Machine learning can give you even more insights about where to find your customers and what type of content your target audience want to consume.

This will help you create social media content that resonates with your target audience and help you get more social shares, likes, comments, and engagement.

7. Boost Influencer Marketing

Influencer marketing is one of the hottest trends in digital marketing these days, and already machine learning is transforming it in several ways. Brands can use machine learning to:

  • Predict incentives
  • Evaluate influencer performance
  • Determine influence

More importantly, it also enables you to identify and eliminate fake engagement and spam bots. Brands can also flag posts that don’t follow their disclosure guidelines. This way, you can easily avoid influencers with fake following and choose real influencers with real followers.

Influencers, on the other hand, can use machine learning tools to identify which content type strikes a chord with your audience. That way, they can publish and promote the right type of content to your audience.

Machine Learning and Marketing Can Go Hand in Hand

If you want your digital marketing efforts to make a bigger splash, you will have to adopt machine learning. It can help you generate more traffic, leads, customers, and revenue.

Whether it is social media marketing, email marketing, or influencer marketing, you can optimize your digital campaigns so you can achieve your marketing goals and go beyond.


Irfan Ahmad

Digital Marketing Strategist, Branex
Irfan Ahmed is a digital marketing strategist at Branex, a web design and SEO company in Toronto, Canada. He has 11+ years of experience in the IT industry, and he is a guest blogger on various websites.
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