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5 Important Ways Machine Learning Is Changing Digital Marketing

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Recently, machine learning has been making waves across different fields and sectors.

Marketing is a field that has been affected the most by machine learning. It has not only revolutionized traditional marketing principles but those of digital marketing, too.

Although machine learning is a term that has been used interchangeably with artificial intelligence, they are not the same.

Artificial intelligence employs the idea that computers and machines can handle tasks that require human intelligence.

Machine learning is a branch of artificial intelligence that automates the building of models for data analysis. For machine learning, the machine or computer can learn from the data it analyzes by identifying and recognizing patterns. This technology enables data-driven decisions.

This technology has many benefits, including optimized customer experience, improved marketing campaigns, and automated repetitive processes. ML facilitates an increase in revenue generation and a decrease in business expenses.

Let’s take a look at how machine learning is changing the marketing world.

Enhancing Customer Experience

When it comes to customer experience, machine learning has made improvements in so many ways, such as:

  •  Ensuring online stores do not run out of stock by giving alerts and creating alternatives when inventory is low. 
  •  Guiding the target audience through a buyer’s journey 
  •  Making personalized recommendations based on customer data to assist customers in getting what they want faster.

One of the best features of machine learning, with regards to marketing, is the recommendation system. 

Customer Happy

We all know how recommendations by friends or family members most often lead us to discover things that we like. So this is because these people know us and know what we want, sometimes even more than we do.

A good example is how a friend would never recommend products made from peanuts since they know you are allergic to peanuts.

Well, in the same way, machine learning enables systems to recognize customers’ preferences and make personalized recommendations based on that data.

Much like how it’s easier to find movies or series you love with Netflix’s recommendation system.

Machine learning enables marketers to learn about the types of products customers want, according to their browsing histories and the shopping items they add to cart. Product suggestions like these facilitate and increase customer conversions if all the generated data is confusing there are more ways that machine learning helps make better decisions.

Sentiment Analysis

From having conversations with people, it is relatively easy for us to perceive how they feel. By making judgments on their voice, facial expressions, or body language, we can assess their emotions.

However, it isn’t easy to comprehend people’s emotions in this digital age, especially with face-to-face conversations, which are being replaced by customers reaching out to businesses online and through visual texts.

With sentiment analysis, machines can determine whether a piece of writing is negative, neutral, or positive.

Sentiment Analysis

Overall it enables marketers to analyze customer feedback and segment it into either a positive or negative response. It can even help customer service judge the emotion of a client complaint or email to know how best to answer it.

Sentiment analysis can also examine the general mood of comments on social media to perceive a business’ online reputation and evaluate how well the brand is doing. Through sentiment analysis, a company can see whether customers are unsatisfied or happy with their products and services. Sentiment analysis helps them target the most frequent complaints and give solutions as soon as possible. It can even find influencers that are pleased with your brand and help you turn them into brand advocates or ambassadors.

This ability of machines that enables them to read emotions has countless possibilities in the marketing world.

Highly Consumer Personalized Ad Targeting

Machine learning is helping marketers to target their ads more efficiently. It also personalizes ads based on consumer experience and predicts the type of content that is most efficient with a particular buyer. Hence, two consumers can visit the same website and get different ads according to their choices.

Machine learning automates the process of content and consumer segmentation. It ensures that customers get the right value at the right time through the correct media at whatever stage of the journey buyer is. 

With machine learning’s ability to create personalized ads and messages based on consumer data of preferences, likes, behaviors, and interests, the cost of targeting ads is reduced, making it more efficient.

Developing Better Products With Optimized Pricing Strategies

Before the digital age, companies released product features and their pricing based on guesswork, which resulted in unnecessary expenses. With items released on little or no customer data and feedback, most of them failed. 

Nowadays, consumers are increasingly adopting ways to shop better and smarter, which results in higher expectations from brands.


 

With the use of polls and customer surveys, marketers can recognize what buyers prefer. Even reviews, likes, and posts serve as data sources to learn about products that customers would want.

Machine learning gives businesses opportunities to streamline their products, specifically for their customer base or industry niches.

Optimized pricing strategies enable businesses to decide on flexible rates for their products or services. With machine learning, the right prices can be obtained based on consumer choices and the values of goods, all in real-time.

Machine learning makes pitching strategies easier and ensures that a product or service’s price is not too high or too low for the consumer. It allows businesses to be more dynamic and agile in responding to supply and demand fluctuations.

Predicting Customer Churn

For a business to grow, it is necessary for the number of new customers to be higher than the churn rate. Predicting customers who are likely to churn helps minimize the rate at which customers move to other competitors by taking action that makes these customers want to stay.

Machine learning facilitates customer churn prediction. With the ability to analyze consumer data, machine learning algorithms can identify customer behavior and predict customers who are most likely to end their relationship with the brand this is especially important because of the impact of COVID-19 to businesses everywhere.

Churn rates can be calculated with simple metrics. However, the predictive ability of machine learning algorithms makes this process faster and easier. It even shows the customers who are most likely to move to a competitor in real-time.

Machine learning goes a step further by presenting necessary moves to prevent customers from leaving through check-up emails, special offers, etc., without human involvement.

Wrapping Up

Machine learning is offering new opportunities to the marketing world. Marketers that are adopting it are gaining an edge over their competition.

Applications of machine learning are transforming marketing strategies and showing excellent results.

With the integration of machine learning in marketing, products and services are growing more efficient, data-driven, and customer-oriented.

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