Published By - Brian Curtis

Best Ways to Use Machine Learning for Digital Marketing

Best Ways to Use Machine Learning for Digital Marketing

Progressions in technology are uniformly changing the world. As a marketer, one needs to understand better this technology that goes far beyond the latest smartphone release.

Machine learning is on the edge of changing the marketing sector. To some extent, it’s already started.

Companies utilize machine learning to get ahead of competitors by tackling some of marketing’s toughest challenges, such as personalization, instant customer support, and big data.

Multiple marketing tools and tactics have been practicing by marketers in this field. One such tool is Machine Learning (ML), a part of Artificial Intelligence (AI). Therefore, machine learning is revising the rules of marketing success from digital advertising to email marketing, from social media marketing to content creation.

Hence, machine learning isn’t just for computer scientists. Therefore, marketers should sit up and take notice.

Best Ways to Use Machine Learning for Digital Marketing

What is Machine Learning?

Machine learning means a machine that can learn. Hence, it means making a machine to learn, understand, and do something more. Machine learning (ML) is also an artificial intelligence (AI) application that provides devices, computers, and gadgets to learn and improve from experience automatically. It also modifies its program when data is received. Moreover, Machine learning (ML) is helping humans solve problems in a more efficient way.

What are the best artificial intelligence and machine learning tools for digital marketing?

Some of the best AI & ML content marketing tools are:

Grammarly

Grammarly is a tool that checks for grammar and spelling in real-time and offers helpful suggestions instantly. Thus, it is like a traditional spell checker on steroids as it works in various browsers and tools.

Atomic Reach

Atomic Reach eliminates the guesswork and rewrites the content. It allows to:

  • rewrite content using transparent and concise language,
  • optimize content performance by clicking a button,
  • segment content with unlimited profiles,
  • uncover insights into why the content is performing, and
  • integrate seamlessly into the workflow.

Textmetrics

Textmetrics is an expanded data-driven language analysis writing platform. It helps to write compelling, accurate, and high-quality content. Hence, during the writing process, Textmetrics reads along, analyses the text, and offers real-time enhancement suggestions.

MarketMuse

MarketMuse is content intelligence and strategy platform. Thus, it builds better and faster content and predicts content’s success. The tool specifies what one needs to target to compete on which topics.

Scoop.it

Scoop.it allows professionals and businesses to study and publish content through its content tool. Hence, it offers professionals to share valuable ideas with the right audiences to build and maintain a significant content presence.

Clearscope

Clearscope is an incredibly easy-to-use interface that helps understand what to write about and how to write it. It uses data that enables a content marketer to write an article based on a particular keyword. It also helps to understand how frequently they should practice that word in their text.

Topic

Topic enables editors and agencies to create content briefs in a short time. Also, it will help one to produce high-quality content helpfully. Therefore, it also offers SEO optimized and developed with great insights that would be nearly impossible to get manually.

Frase

Frase is an AI content marketing tool that uses artificial intelligence and machine learning. Its integrated content optimization, site search, and conversational AI tools help one engage with visitors on the site.

Surfer

Surfer crafts content marketing strategy through producing guidelines and insights with its artificial intelligence. Hence, its algorithms prepare a plan adjusted to the domain, niche, and audience without wasting time. Therefore, it is a valuable tool for copywriters, content creators, SEO agencies, bloggers, and freelancers to improve and optimize their content.

Ways to Use Machine Learning for Digital Marketing

Improved customer experience

Producing a high-end customer experience is one of the things in whatever an organization does. Thus, integrating ML-enabled chatbots in the digital marketing process can add to the customer experience one delivers.

Approximately 80% of customers want their chat queries answered quickly. Hence, that’s when an AI and ML-based chat software can be the savior.

Therefore, chatbot integration assures 24 x 7 x 365 availability, apart from zeroing the wait time for customers. Hence, it also allows one to broaden the database without manual interference once trained and implemented successfully.

Meanwhile, chatbots also allow one to transfer calls or chats to human agents at any period during the conversation.

Content creation and curation

Indeed in 2021, content is still the king. Hence, content rules all forms of marketing. Without content, one would not be able to market the brand.

Content creation and content curation both demand ampere-hours of brainstorming and digging. Hence, machine learning tools can save plenty of time to use in other crucial areas. Thus, it can help one to improve what to write and publish.

Therefore, some of the most popular content curation tools are Curata, Flipboard, Pocket, and Vestorly. Hence, one can use these to create deeply engaging stories to post and share.

However, the use of ML applications has also eased the way people create content. The auto-correct on the cell phone or Gmail compose box are a perfect example of machine learning technology.

As a technology that can write on its own is yet to develop. Though there is a tool, Quill, that can create descriptions from a broad set of data.

Website UI/UX

The user interface (UI) and user experience (UX) of a website are the most critical aspects of digital marketing. They are directly related to the website’s search ranking and visibility.

Hence, machine learning can improve website design. Thus, one can examine and find valuable insights related to the behaviour of users and the performance of the website using advanced ML tools.

Therefore, the technology allows one to create websites that users find practical and valuable. Leading website building tools like Wix, Weebly, and WordPress use technology and analytics to build simple yet effective and helpful websites.

Marketing automation

If using marketing automation tools, one can expect more than 10% revenue growth within a year. Hence, that’s the reason why over 79% of notable brands have begun using marketing automation in past years.

Therefore, automating one’s marketing will take the growth strategy to the next level. However, tools built on machine learning can decode and learn from trends, recommend actions based on history and past experiences. It also presents accurate analytics to help develop strategies and take steps that yield.

Hence, customer segmentation, pitching to the exact audience, and sending follow-ups becomes non-human tasks with excellent ML-based marketing tools. Therefore, after every implementation, the tool learns and gives scopes for development for future campaigns.

More optimized advertising

The usual way of advertising includes choosing the right ad content. Also, it includes selecting the right channel or platform to display the ad. Thus, one will also need to work on finalizing the right time to show the advertisement. Hence, this is more a manual job with high chances of ads not performing to expectations.

Therefore, with AI-based advertising tools, such as Facebook Ads or Google Ads, one can pitch well-optimized ads to the audience. They allow one to find the right audience for the ad and cut the advertising cost significantly.

However, apart from reaching potential customers, one can display ads in multiple formats and increase the outcomes from diverse angles using these excellent ad channels. Hence, just for a glimpse, one can find potential customers based on the traits of existing customers or the customers of the competitors.

Not just that, one can send ads when the average audience is most active. Thus, this new-age technology saves time and spends while improving the returns on investment.

Conclusion

Digital marketing is an industry full of opportunities and challenges. Hence, it isn’t exhibiting signs of going anywhere anytime soon. So, if digital marketers aim is to increase engagement and brand awareness with leads, they must understand their customers.

ML won’t substitute existing digital marketing jobs. Alternatively, it will help improve the capabilities of the modern digital marketer, providing a base to do and be better at what one does.

Also Read:

EXAMPLES OF MACHINE LEARNING IN MARKETING EXPLAINED

WHAT IS THE ROLE OF MACHINE LEARNING IN AFFILIATE MARKETING?

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