How Machine Learning Enhances Conversion Optimization

Many companies are benefiting from the limitless applications of artificial intelligence (AI) and machine learning (ML) in particular. When it comes to conversion optimization, machine learning has the potential to maximize conversion for businesses. Given the right data, the complex algorithms of machine learning can observe a customer’s preferences and behaviors to determine the most effective way to convert their visit into a sale. Here are a few applications of machine learning in conversion rate optimization, and how companies can take advantage of ML to boost conversion optimization.

Machine Learning Applications In Conversion Rate Optimization

There are several ways businesses can use machine learning to drive higher conversion rates. Here are a few of the most common applications among companies today.

Chatbot

As much as 80% of businesses online use chatbots. While most companies have used chatbots long before the dawn of artificial intelligence and machine learning, AI and ML take this tool to the next level. 

“Machine learning chatbots are capable of offering 24/7 support and simulating human conversation with customers,” explains Elizabeth Johnson, a business writer at Write My X and 1day2write. “Thanks to natural language processing, these bots are better equipped to engage customers, assist with their queries, and improve their experience.” The constant assistance and engagement offered by ML-powered chatbots could result in higher conversions for companies. 

Personalized Recommendations 

As a result of machine learning’s complex algorithms, machine learning fueled by high-quality data can personalize product recommendations for customers. After learning the customer’s activity and preferences, ML can recommend the products that the individual is most likely to buy. 

Since the customer has probably purchased a similar product in the past or visited the product page before, recommending these products can significantly increase conversion rates. Personalized recommendation urges the customer to view the familiar product and consider purchasing it. A report found that 91% of consumers are more likely to purchase from a brand that remembers their preferences and offers relevant recommendations. As a result, product recommendations created by machine learning are incredibly effective at driving sales. 

Source: https://getwiser.ai

Personalized Product Results 

In addition to personalizing recommendations, machine learning algorithms are capable of personalizing product result pages for customers. In the same way that ML can learn which products to recommend based on the consumer’s past behavior, it could determine which products to display at the top.

Placing products that the consumer is most likely to like and purchase as the top results can have a positive impact on conversion rate optimization. Since some products have a better chance of converting the consumer’s visit into a sale, showing them at the top of the results page ensures they are highly visible to the consumer. 

Source: https://www.maccosmetics.com

Personalized Offers

Another advantage of using machine learning as a business is the ability to understand consumer preferences better. Learning which products a consumer is most interested in allows companies to boost conversion rates by providing a discount or offer specifically for these products.

Source: https://global.direct.asda.com/george/women/D1M1G20,default,sc.html

Machine learning can identify products that the customer has viewed in the past or added to their cart without checking out. Offering a discount or deal on these products increases the probability of the consumer following through with a purchase.

Is Machine Learning Right For Your Company And Conversion Rate Optimization?

If you’re interested in improving your conversion rates and growing as a business using machine learning, there are a few things to consider before investing in this technology. 

Validate your concepts for performance during the design stage with AI-generated attention analytics

Access To Data

As powerful as artificial intelligence and machine learning technologies are, they are only as effective as the data available. Machine learning requires extensive high-quality data to provide consumers with a personalized experience. 

“Without vast amounts of high-quality data, businesses won’t be able to use machine learning to its fullest potential,” warns Tricia Knight, a journalist at Originwritings and Britstudent

Lack Of Variety 

While most consumers find personalized recommendations and product results enhancing their shopping experience, those who prefer to try new and different products might not like the lack of variety. 

Since machine learning determines recommendations based on past behavior, it’s likely to choose products that are extremely similar to each other. Shoppers who enjoy a vast variety of product offerings may not benefit as much from personalization as others.

AI Testing

To make sure your website is attractive and the most important objects receive plenty of user’s attention, one of the tools is Attention Insight Google Chrome Extension to help with the inquiry.

An algorithm takes into account various aspects of your design – the amount of text, text size, and text contrast, colorfulness, number of images, and their size. The higher the score (Clarity Score), the more clean-looking the design is. On the other hand, a low score indicates that your design is cluttered and important elements are not easily visible.

Meanwhile, AI Heatmaps are a visual representation of data that helps you determine whether users view and observe certain elements.

Source: www.wix.com

Conclusion

In the same way that artificial intelligence and machine learning are changing other aspects of digital marketing, this technology can improve conversion rate optimization. With the right data, AI and ML could drastically increase company sales and improve the customer experience.

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