Successful marketing depends on many factors, not by just developing a brand strategy, or creating engaging content, or competitor’s analysis. In the digital era, no marketer can survive without mastering data, analytics, and automation.

Machine Learning (ML) solutions are already delivering significant value and revolutionizing the marketing niche. ML can help marketers to extract insights from the data to provide actionable insights in order to improve their marketing campaigns.

ML enhances a system in a way that it learns from past and current experiences. It can improve marketer performance on several tasks such as generating branded collaterals, customer segmentation, customer communication, classifying relevant content, and overall productivity and output. This all happens without human intervention as the entire process is automated.

Utilizing the immense potential of Artificial Intelligence (AI) to excel in business is no more a far-fetched pipe dream. More and more companies have already discovered technological advances spontaneously and understood that Machine Learning and marketing go hand-in-hand.

Artificial Intelligence and Machine Learning are often used interchangeably but are not the same. AI has a border meaning – an idea that computers and machines can complete tasks normally that require human intelligence. Machine Learning is a branch of AI that automates systems for data analysis.

The concept behind ML is that a machine or a computer model can learn from the input data, identify patterns and provide insightful applicable results. Ultimately, ML technology can make decisions without human interventions.

What Does This Mean For marketers?

Marketers are already using AI and ML technologies to help improve their marketing campaigns and increase revenue by optimizing the customer experience. AI-powered marketing tools help to achieve better conversion rates and sales as it is backed with specific data about target customers such as customer behavior, shopping patterns, and much more.

Models powered by several AI and ML algorithms can help with all kinds of different aspects of marketing. They help to create tailored content, create a great user experience, improve customer outreach and trigger a response.

Customer behavior is an important part of optimizing a marketing strategy for business today. In this article, you will learn about how Machine Learning can help marketers to improve and enhance their marketing campaigns and achieve better conversion rates and sales

1. Real-Time Marketing And Lead Scoring Is A Reality Now
Lead scoring is a means to rank prospective customers based on their value to the company. It helps to improve and perfect lead scoring accuracy that prioritizes lead generation strategies. Calculations in lead generation is a complex task and Machine Learning plays a huge role in making everything straightforward.

Marketers use Machine Learning algorithms to monitor customer behavior to track:

• Websites visited
• Emails opened
• Downloads
• Clicks

It also helps in tracking customers’ behavior on social media sites such as the post they like, pages or accounts they follow, and ads they engage with. Ultimately, a marketer can plan for campaigns using all this data and create personalized profiles for their customers, thus, boosting their marketing.

2. Boosts Customer Experience
Machine Learning plays a vital role especially in enhancing the online shopping experience. It can boost customer experience and make everything convenient and straightforward.
ML can boost customer experience in many ways such as:

• Provide customers with a 24-hour support service
• Personalized product recommendations.
• Provides alternatives that may suit.
• Dropshipping

The significant rise in the popularity of drop shipping in the past few years has paved the way for many eCommerce and online retailers to utilize ML to improve their customer experience.

3. Incorporate Chatbots To Improve Customer Service
A common sight on almost every modern website is chatbots that pop up in the bottom corner of the screen. These chatbots assist soon after a visitor arrives on the site. Chatbots enable businesses to provide customers with 24-hours support, by answering simple customer questions and referring them to the right customer care executive if they can’t assist.

Chatbots can also be used for several other purposes such as:

• Sharing company information
• Sharing new offers and discounts
• Announcing new products and services

Chatbots represent one of the most ubiquitous applications of AI, but most marketing chatbots are completely scripted and use minimal Natural Language Processing (NLP) and Machine Learning algorithms. AI-driven chatbots keep learning from their interactions with website visitors and collect and interpret data to offer more accurate and personalized answers.

ML can improve how chatbots operate by using sentiment analysis to guess the mood of the customer by identifying keywords in the message. When paired with social media sites, ML can further assist marketers by gathering more data about customers from social media profiles and their activities.

As a result, this will improve product recommendations to target customers. In simple terms, ML can help chatbots further personalize the customer experience.

4. Content Optimization
Content optimization is one of the most important aspects of SEO which helps to increase visibility in organic search. Unique content that receives a lot of attention or clicks gets a better position in the search engine and drives more traffic to a website.

A popular way that many marketers practice content optimization is through A/B testing. Whether it’s an article headline or email subject line or graphics, A/B testing allows digital marketing service providers to try out different options and collects data to determine which connects best with the audience.

Machine Learning helps in providing information on what content performs best, whether it’s article headline or email subject line, or graphics. Insights extracted from huge amounts of customer data about their interests, past purchases, and online behavior can help marketing teams to create content that will most engage audiences.

5. Develop More Products and Services
In the digital era, people have quickly become familiar with shopping in innovative and streamlined ways. As a result, online shoppers’ expectations are higher. This provides more opportunities for business to personalize their marketing strategy specifically to the target audience within their industry or even with their own customer base

ML algorithms can help to develop new products and services more efficiently and accurately according to consumer specific needs or they can develop to cater to a new group of potential customers. Many businesses are already in the process of developing new products and services based on the findings from Machine Learning models.

6. Easier to Predict Customer Churn
Customer churn is nothing but customer turnover. It measures the number of customers quitting or ending their relationship with a business. For instance, in a business-like SaaS, the customer churn occurs when their client cancels its service or unsubscribes from its membership.

For the successful growth of a business, the churn rate must always be lower than the number of customers getting on board. The churn rate is calculated by the percentage of clients or subscribers who leave a business within a specified period of time. Calculating churn rate will help businesses to realize two things:

• Your clients are not satisfied with your services.
• How to predict the rate for future prevention.

How can you predict the churn? Here’s a machine learning discovery model that can make predictions based on certain behaviors like:

• How do customers engage with a product or mobile app?
• When was the last time they signed into their profile?
• When was their last purchase?

Machine learning helps analyze this data on a much larger scale. The technology gives insightful information to marketers to predict the future churn so that it can be prevented.

7. Improve Personalization
Online shoppers, especially millennials, want brands to care about them. So much so that 52% of online shoppers are likely to switch to another brand if they feel that the current brand isn’t making enough effort to reaching out to them with their specific needs.

There are many ways in which Machine Learning can improve the shopping experience of customers. It can help to create specific ads for a particular group of customers. ML can guide marketers on the journey of buyers and make personalized products recommendations.

Does Machine Learning Replace the Role of the Marketer ?

Good marketers are still as important as ever, and machine learning doesn’t replace their role.

However, it is ironic that ML helps to humanize their marketing efforts and have the ability to reach customers effectively at every touch-point in their journey. With the technological advancements in ML, now it is possible to analyze and predict which customers are more likely to make purchase decisions. ML can also predict which customers are about to churn and understand which content is most effective and bring the best results in personalizing ads for particular groups of customers.

Conclusion
Artificial Intelligence and Machine Learning are the way to go for business marketing. Marketers are already using Machine Learning technology to change the way they operate. A new wage of ML technology in marketing is becoming a game-changer and has leveraged power into the hands of marketers. ML is enabling a new era for marketers to understand consumers better and enhance customer experience.

In the coming years, it is likely to become even more evident how ML changes the way companies interact with their customers and offer more personalized and authentic experiences to engage and sell their products.