Role of ML in Marketing

Published on 24 Oct 2022

ML, Marketing

What if you could automate your marketing process's tedious and time-consuming portions? That is now possible owing to artificial intelligence. While machine learning has been used for various purposes ranging from banking to healthcare, it is now used by organizations of all sizes to enhance their marketing measures.

Data is now dominating the digital world. Machine learning may help us enhance our predictions and decisions in marketing initiatives, from lead scoring to churn reduction and beyond.

At the same time, many marketers still need clarification about how AI works and what it can be utilized for. This blog will teach you more about Machine Learning for Marketing.

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What is Marketing Machine Learning?

Machine learning is a kind of artificial intelligence which employs algorithms to produce predictions and judgments from data. It is used in various modern sectors such as advertising, finance, and healthcare, and it may be immediately integrated into marketing activities such as lead scoring and email marketing.

It is useful in marketing since it may disclose information about customer behavior that would otherwise be overlooked. For example, a company may have a wealth of data on website visitors who filled out contact forms, but it may need to be clarified whether or not to optimize that data for increased lead flow or if those visitors would convert.

They can use machine learning to create models that predict who is more likely to make a purchase. Machine learning is the capability of a computer to understand without being explicitly programmed. In terms of marketing, this means that a computer can detect patterns in data and utilize those patterns to predict future outcomes effectively.

A machine learning model, for example, may predict which leads would convert and then take targeted activities to enhance their user experience based on their past behavior.

The development of increasingly advanced machine learning algorithms has enabled computers to acquire new data continually, utilize that data to enhance future judgments, and, therefore, automatically improve their performance over time without the need for human intervention.

Traditional marketing makes extensive use of statistics to guide business choices. Machine learning progresses by employing this data to make judgments autonomously rather than just supplying information about what is occurring on a macro level. In other words, without the assistance of human labor, robots are already learning how to maximize outcomes.

Why Should You Utilize Machine Learning To Promote Your Company?

Although quantifying the benefits of marketing campaigns may be difficult, fundamental business planning reminds us that client acquisition is critical for long-term success.

Marketing teams are usually responsible for numerous parts of their company's process, from product development to price decisions. As a result, predicting which actions will have the largest long-term influence on income creation may take time and effort. Machine learning helps companies better understand and respond to their consumers.

For example, consider an eCommerce platform such as Shopify or BigCommerce, where a company sells things. They might build a machine learning model that predicts which client groups are most probably to convert based on previous conversion rates and then use that model to send targeted emails or place ads in certain channels to those clients.

Businesses can improve the average order value, a key sign of long-term revenue development. Furthermore, marketing teams are responsible for creating customer profiles, determining their target demographic, and producing messages based on that knowledge.

However, determining whether these activities are being done properly or gaining insight into how different demographic groups respond differently to the same marketing message may take time. Data science may provide several insights about customer traits that can be leveraged to improve marketing and targeting.

For instance, you may utilise machine learning to determine a user's preferred email language based on their location or whether pop-ups or banners are more successful based on their device. This adds to more lucrative marketing, leading to increased business growth.

Improving Your Marketing Using Machine Learning

We are aware that marketing teams always have more data. Marketers need help understanding and utilizing massive amounts of data. In this inquiry, machine learning comes into play.

Machine learning should be an important part of your marketing stack since it can analyze massive volumes of data faster and more effectively than people.

This strategy can utilize data to identify patterns and make forecasts rapidly. Marketers may then use these insights to improve a large portion of their workflow, from doing further tests and improving the user experience on their website to customizing the user experience for each customer and automating consumer interaction.

The main message is that machine learning can be used to improve almost every area of your digital marketing efforts. Below, we will go through five of the most important strategies for integrating Machine Learning in Marketing.

Examine Data Sets

Analyzing data sets is most likely the initial step in any machine learning method you use in your marketing initiatives. For example, machine learning may be used to analyze and find patterns in user activity on your website.

Instead of spending hours looking through data in your Google Analytics profile, an algorithm might perform the process in seconds, projecting future visitor behavior and identifying patterns that can be used to enhance your website.

People may do their own data analysis but need help to do it as rapidly or accurately as AI-powered solutions. Marketers may also use machine learning to understand their customers better.

Consider the approach for consumer segmentation. Segmenting your audience into several groups may considerably enhance your marketing efforts, but doing it manually takes time.

On the other hand, a machine learning program may automatically classify your clients based on behaviors and activities you could never expect to foresee.

Content Creation and Optimization

The importance of content in your digital marketing initiatives cannot be overstated. However, you may want an additional explanation of how machine learning may improve the content you create and distribute and why it is critical to include it in your content marketing strategy.

To begin, machine learning may help your content rank higher in search engine results. It's one thing to be a brilliant writer; it's quite another to write in a style that pleases Google and gets you results in the SERPs. You must use all appropriate language, cover all relevant issues, and cover all of your bases.

It's easier to do this with intelligent content creation tools like, which compares your material against Google's top results using machine learning to guarantee you cover all the important aspects.

You can use algorithms to create content for yourself. Phrasee, an AI-powered copywriting tool, uses machine learning to create email subject lines and push notifications that maximize return on investment.

It is also feasible to use AI to curate content for your consumers. Curata offers machine learning content curation tools to help marketers locate and distribute the most relevant and entertaining information to their customers.

Enhance Personalization

Customers appreciate customization. According to an Accenture study, 91 percent of consumers prefer companies that remember their preferences and respond with relevant offers and ideas. More than half of customers are also prepared to move to a competitor if they still need to obtain a personalized experience.

The good news is that machine learning allows clients the most personalized service possible. You may apply an algorithm that analyzes user activity, identifies the goods they want, and creates a customized homepage and suggestions list.

Amazon, for example, utilizes AI algorithms that examine customer purchase history, goods in their basket, and viewing habits to make product suggestions that are most likely to be bought.

The same algorithm might generate customized offers for each client and send them when they are most likely to buy.

Enhance Marketing Automation

Better personalization is one-way machine learning may impact how your organization communicates with clients, but there are others. Furthermore, better automating your marketing operations may significantly enhance customer participation.

Assume you automatically email customers who sign up for your newsletter or leave their shopping carts unattended. While most companies would send generic emails to their clients, organizations that employ machine learning may tailor content and offers to depend on the consumer's browsing habits.

If they had previously looked at your company's assortment of dog toys before signing up for your email, a relevant offer on chew toys would boost their probability of connecting with your business again.

AI-powered marketing automation tools can scan larger and more diversified datasets to better categorize leads for SaaS companies. This allows sales personnel to prioritize prospects considerably more likely to convert.

Marketing automation is a powerful instrument. Marketing automation, according to Invesp, enhances sales productivity by more than 14% while lowering marketing expenses by more than 12%.

This is doable without machine learning but AI significantly boosts the strength and personalization of your automation efforts.

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Use Chatbots

The chatbot is an effective customer support tool. They are virtually required if you own an internet company. Eight of ten clients who have engaged with them have had a positive experience.

When employing chatbots, you don't need a human on staff to support clients. On the other hand, chatbots powered by machine learning may automatically deliver astonishingly accurate responses to consumer inquiries. This is due to the fact that your chatbot will constantly modify the replies it provides depending on the material on your website and the conversations it has with people.

With more talks, the chatbot will give an even better customer experience since it is always learning and growing. You may choose to have your chatbot direct a particularly complicated inquiry to a person at first, but the bot will soon become so efficient that a human will not be necessary to step in.

You'll ultimately have a chatbot that can upsell the consumer rather than merely answer their inquiries. Furthermore, buyers are unlikely to realize they are conversing with a robot. Certain chatbots, such as IntelliTicks, employ Natural Language Processing (NLP) for customer interactions, which is another field of artificial intelligence.

Furthermore, data gathered by AI-powered chatbots may be analyzed by a separate machine learning algorithm to provide insights marketers can utilize to improve their future efforts.

Businesses may enhance their decision-making across the customer lifecycle by using machine learning in digital marketing, from lead scoring and sales funnel optimization through churn reduction. By learning about consumer issues, you may improve the customer experience, increase customer engagement, and minimize customer turnover.


Featured image: Image by macrovector


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