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Exploiting artificial intelligence's enormous potential to succeed in business is no longer just a pipe dream. Since many companies have already realized this, it is evident that machine learning and marketing go hand in hand as technology develops quickly.

No business can afford to do one without the other in this day and age if they want to stay competitive.

Data insights are more critical than ever and help to improve customer engagement. The fact that there is a greater reliance on data is not surprising. According to Gartner research, over 75% of businesses will invest in big data over the next two years.

Businesses must today be able to predict customer behavior to optimize marketing campaigns. This article will examine how machine learning can boost and improve a company's marketing initiatives.

What is Machine Learning in Marketing?

Machine learning is a subfield of artificial intelligence that involves using computers to process large amounts of data to identify patterns and then allowing the computers to make decisions based on those patterns. In essence, it is the use of computers by businesses to analyze and interpret data with minimal manual labor.

In a marketing context, machine learning is mainly concerned with consumer and behavior data to predict a customer's next move and then act on it. Machine learning algorithms can identify common trends and occurrences and their root causes, allowing marketing teams to create more tailored and effective campaigns.

Because of computing power, machine learning approaches can sift through data and conclude much faster than the average human. As a result, machine learning marketing is most useful when working on time-sensitive projects or analyzing real-time data. More nuanced issues are likely to be handled better by actual people, but this may change over time.

10 Ways Machine Learning Can Enhance Marketing

Machine learning is already used in many fields, from assisting financial institutions in risk calculation to providing personalized healthcare via the Internet of Things.

Following are some of the ways machine learning enhances marketing.

Enhance Customer Experience

According to studies, 57% of senior executives think machine learning can be most helpful in marketing.

Machine learning can improve customers' online shopping experiences in a variety of ways, including:

• Make sure your online store never runs out of inventory and offers alternatives if it does
• Assist the customer in purchasing by offering personalized product recommendations to help them find what they want
• Provide customers with 24-hour support

The rise in popularity of drop shipping over the last decade has enabled many e-commerce companies and solo entrepreneurs to use machine learning to improve the customer experience.

Kate Somerville, for example, has successfully combined a Magento e-commerce platform with nChannel. They used machine learning to create a more personalized shopping experience by responding to real-time data. This has increased traffic, conversions, and revenue.

Create New Revenue Streams

Data is the foundation of digital marketing in the modern era. Due to the abundance of data available, marketing is frequently seen as the top priority for many businesses because it directly contributes to growing revenue. 

The retail behemoth Amazon has used machine learning like no other company has, with personalized product recommendations accounting for 35% of their annual revenue.

Using data insights to customize their services to the customers' needs, their cloud computing service, Amazon Web Services (AWS), offers opportunities for other businesses to profit from AI. As a result, Amazon will be able to generate new, innovative sources of revenue.

Many marketers had worked toward this alleged marketing prophecy for years before machine learning became prominent. Decision-makers are much more able to predict what customers want before they realize it when they have data insights at their disposal.

Improve Personalization

People want to feel cared for by brands. 52% of consumers say they are likely to switch brands if they believe a firm is not investing enough time and effort into personalizing its communications.

Machine learning is the foundation of Amazon's success in e-commerce personalization. To customize the online shopping experience, they gather vast amounts of data about their customers' online actions, interests, and prior purchases.

Every touchpoint in the purchase journey, including emails to product offers, is individualized. 

Ironically, machine learning contributes to making experiences more human.

Customers who shop online feel more valued since the experience has been designed to meet their requirements and interests.

This fosters loyalty. A brand that gives customers the impression that they are being heard will earn their trust. According to research, 44% of customers who had a personalized shopping experience said they would return to make further purchases.

Reduce Marketing Waste

It is pretty helpful to have a system in marketing that can swiftly recognize trends and behaviors in real-time and then react appropriately without requiring human input. Machine learning will continue to play a significant role in marketing in the years to come because of its capacity to "learn" while in use.

Many marketers used to base their advertising campaigns largely on speculation. In the past, a huge amount of money was wasted on marketing initiatives that didn't connect with the target audience because the marketers didn't understand their audience well enough.

This marketing waste is eliminated via machine learning.

In the digital age, marketing in a disorganized manner is not only unnecessary but also foolish. By eliminating guesswork, machine learning enables marketers to approach their audience with offers for products and information with the highest likelihood of generating interest and, eventually, conversions.

Chatbots Engage Customers

Friendly chatbots that appear in the bottom right corner of many modern websites to provide assistance or advice as soon as a visitor loads the page are becoming a more common sight.

The success of chatbots depends heavily on machine learning because it enables them to continuously learn from interactions with visitors, collecting data and analyzing it to provide more accurate answers gradually.

Chatbots not only eventually replace virtual human assistants but also allow businesses to revolutionize marketing campaigns.

Businesses can tailor their marketing strategies to serve their customers better and ultimately deliver a more personalized experience with the insights that machine learning provides. It will make it easier to develop a devoted customer base that will grow to trust your brand and return for additional goods and services.

Develop New Products and Services

Machine learning algorithms can assist in more precisely customizing new goods and services to meet customer needs. For instance, it becomes possible to carry out surveys with prospective customers worldwide and then use the information to deliver a product.

This can assist companies in finding fresh markets and new products they can create to appeal to fresh customers.

The same solution can assist businesses in distributing specific products or variants of the same product to various markets. For instance, the surveys may show that American drivers favor four-wheel drives while European drivers favor hybrid cars.

With the aid of this information, a car manufacturer would be able to design a vehicle that would be appropriate for the markets in the United States and Europe.

Uncover Trends 

Unstructured data can be mined by machine learning to gain insight into what customers say publicly. It can interpret social media to generate new ideas for content or products directly related to consumer preferences. 

One instance of this is when Ben & Jerry's decided to introduce a line of breakfast-flavored ice cream after learning that people were discussing ice cream for breakfast in the public domain.

Automate Marketing 

The next level of marketing is automation. Number crunching, learning from past results, and providing valuable insights are all aspects of machine learning.

It supports all marketing facets, including customer segmentation, content personalization, recommendation-making, and customer service.

For marketers, this makes decision-making simpler, and as it learns more, it gets better. Marketing automation helps brands control the user experience and generate more qualified leads and sales.

Email marketing powered by machine learning enables marketers to segment their customer base and create highly personalized email campaigns. They can create customized email subject lines and body copy that encourages customer interaction.

They can refer to previous responses to choose the best moment and method for sending messages. Their email marketing could incorporate split-testing to continue increasing ROI.

Target the Right Influencers 

Today, influencers are being used by more and more brands. They want those consistent with their brand values because they know better than to use them carelessly. This can aid in expanding their audience reach and engagement while enhancing brand credibility.

A machine learning tool can assist in finding various indicators in social media posts and recommend influencers who would effectively connect with an audience.

Machine learning assists in combating one of the most serious issues when using influencers: influencers with fake followers and those inflating their performance.

Machine learning-based Natural Language Processing (NLP) tools can make sense of video content posted by influencers and assist brands in selecting the right brand advocates. It also helps them understand how the influencer conveys brand messaging.

Mazda used IBM Watson to select influencers to launch one of their new vehicles at an Austin, Texas, festival. They drove around town in the vehicle and then shared their experiences on social media with the hashtag #MazdaSXSW.

Manage Social Media

Machine learning enables marketers to optimize their social media presence by leveraging the power of data. For example, it can assist them in identifying reviews or complaints that require immediate attention to manage the brand's reputation.

The knowledge gained from studying this data can help brands produce the right kind of content for each platform that deeply engages audiences.

Machine learning-powered social listening tools can track hashtags, keywords, and brand mentions across all social media platforms.

Companies Using Machine Learning in Marketing

Following are some of the companies using machine learning in marketing.

IBM

IBM provides a suite of AI tools to businesses to help them streamline their marketing strategies and customer interactions. Watson, its AI assistant, uses machine learning to conduct audience analytics, personalize one-on-one conversations, and connect with audiences via their preferred channels.

Bluecore

With the help of Bluecore's platform, e-commerce businesses can stay one step ahead of their customers by personalizing interactions for online shoppers.AI and machine learning assist in one-on-one conversations and product recommendations to customers across multiple channels. Predictive automated intelligence also collects data on the best ways to reach out to customers, allowing teams to tailor marketing activities to the preferences of their target audiences.

Ada

Ada, a brand interaction platform with conversational AI features, enables businesses to provide consistent, high-quality customer service. Thanks to machine learning models, Ada's platform can analyze text in over 100 languages and predict customer needs. Businesses can use this proactive technology to reduce the time it takes to resolve issues and provide customers with the answers they seek.

GumGum

GumGum has used AI and machine learning to determine ideal web pages and digital spaces for posting ads as part of its partnership with Appen. Verity is the company's contextual intelligence platform, sifting through videos, audio clips, images, text, and other online elements. Businesses can use this tool to place advertisements on web pages and platforms without accidentally associating their brands with irrelevant or controversial content. 

Applecart

Applecart's marketing platform identifies promising leads and connections, resulting in more effective marketing campaigns. After collecting data from public sources, the company's Social Graph Platform employs machine learning algorithms to determine each individual's professional and personal relationships. Companies can quickly map out their leads' social networks and tailor their content to these audiences.

Future of Machine Learning in Marketing

Machine learning is getting better by the day, but the amount of data we collect is also increasing. The more high-quality data we have, our predictions and pattern analyses will be more accurate. However, because circumstances constantly change, businesses must stay ahead of the curve to remain relevant in the market. Machine learning will affect businesses in many ways other than marketing technology, which you must prepare for to stay current. 

Keeping your company on top or establishing a foothold in the market if you don't already have one are goals that can only be achieved through innovation and creativity. Machine learning in marketing and sales is an excellent place to implement new technology strategies. You can start the modernization of your business by consulting data science and machine learning experts.

Conclusion

Machine learning and artificial intelligence are everywhere. Continuous learning, ever-expanding knowledge, and limitless potential exist in this technology field. It has changed and continues to change businesses of all sizes. 

Machine learning in marketing is starting to change the game. This is opening up a new era in which it will be possible to improve customer experience by better understanding consumers.

The impact of machine learning on how brands interact with customers and provide a more genuine experience in luring, selling to, and serving them is likely to become even more apparent over the following few years.