The development of artificial intelligence has led to the emergence of many applications and tools that predict customer behavior on the Internet, helping online stores find new ways to target the right audience.
But to understand customer needs and preferences, marketers need to collect and process large amounts of data received from web reports, open databases, search queries, etc. Previously, data analysis was expensive and time-consuming, but now it can be done With almost no human intervention.
Ecommerce giants are developing massive data usage and deep learning for years, so Amazon knows a lot about you: favorite brands, and new products you might want to buy, using smart tools designed to analyze your behavior.
Netflix and Amazon already use the company’s services to predict the behavior of its customers and make accurate recommendations to increase customer satisfaction. Although there are many analytical tools in the market to meet the needs of large companies, only a few of them can be used by SMEs.
We mention, for example, the Xineoh platform that successfully uses deep learning and artificial intelligence to predict customer behavior. The platform matches individuals with products, inventory with available buying opportunities, prices with customer spending trends, and people with usage patterns, all at exceptional speed. This data improves decision making, allowing marketers to set up targeted campaigns to achieve sales results Best.
Of course, you can analyze site data and ask them directly about preferences and interests, but this data is not enough to predict customer behavior, and to deliver a product that already meets their needs.
In this aspect, Dynamic Yield helps you determine the interests of your target audience and predict long-term purchasing behavior through an artificial intelligence solution to create custom emails.