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Three Ways Retailers are Using AI to Improve Customer Experience
To detect fake transactions, a supervised decision tree is built. Ecommerce merchants may avoid chargebacks and increase profitability by using accurate fraud detection for each transaction.
Fremont, CA: The technology that will have the most significant impact on e-commerce in the future years is artificial intelligence (AI). AI does more than giving personalized product recommendations to customers, from optimizing inventory levels to sophisticated fraud management. Here are three uses of AI in retail:
Advanced data analytics and machine learning for intelligent fraud management
The majority of the scams take place online. One of the most common reasons for shopping cart abandonment is security worries while making a payment. To combat various types of e-commerce frauds, machine learning and artificial intelligence (AI) tools are helpful. Smart data analytics and AI-based systems can be used to determine what constitutes legitimate customer behavior, such as false declines. To detect fake transactions, a supervised decision tree is built. Ecommerce merchants may avoid chargebacks and increase profitability by using accurate fraud detection for each transaction.
Algorithm-powered personalized product recommendations
Product recommendation engines use both a historical and a predictive method to make recommendations. Historical approach algorithms will recommend products depending on the customer's previous decision. On the other hand, the predictive approach algorithm will offer products based on what clients might buy next.
Predictive analytics to improve product offerings
Predictive analytics is a statistical analytical method that predicts future events using data mining and machine learning. Predictive analytics in the context of e-commerce allows store owners to gain a better understanding of customer decisions and behaviors.
It identifies many motivators in target consumers' behavior so that e-commerce store owners can use the information to better their present product offerings. Every customer has a different experience with an online store. Predictive analytics aids in the understanding of all variables that influence customer behavior and the adaptation of product offerings as a result.