3 tools of artificial intelligence to predict consumer behavior on the internet

Helped the development of artificial intelligence in the emergence of numerous applications, and tools that predict the safety of workers on the internet, which help e-shops to find new ways to target the right audience.

But to understand the needs of customers and their preferences, it is incumbent on marketers to collect and process large amounts of data that is presented to them from the reports site, the rules of open data, search requests, etc., previously was operations the analysis of these data is expensive and time-consuming, but now it can be done without human intervention almost.

Works giants of e-commerce on the development of the use of big data, anddeep learning for years, therefore the Amazon know about you a lot like: favorite brands, new products that you might want to buy them, using intelligent tools designed to improve your behavior.

The following are the 3 tools rely on artificial intelligence to help you understand customer needs and launch campaigns targeted accurately:

1 – tool Xineoh:

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Used Xineoh successfully deep learning and artificial intelligence to predict the behaviour of customers through a revolutionary platform able to collect million dollars from US investors, the Canadian in 2017.

The organization works to match individuals with products, inventory with purchase opportunities available, and prices with the tendencies of spending clients, and with usage patterns, all at exceptional speeds, and this data to improve the decision-making process, allowing marketers to set up campaigns targeting of minutes to get the results of better sales.

Used both (Netflix) Netflix and(Amazon) Amazon already has the services of the company to predict the behavior of their customers, and provide accurate recommendations to increase customer satisfaction. It also helps Xineoh companies to connect users to the content you are looking for, this feature will bring millions of dollars to the company.

Although there are many analytical tools in the market to meet the needs of large companies, but few of them can be used by medium and small businesses. Expects Xineoh fill this gap by providing a user-friendly tool that collects large amounts of data and analysis in several minutes.

2. the tool Dynamic Yield:

dynamic yield

We can say that email marketing depends largely on luck, since you never know what needs your customers exactly, of course you can analyze the location data, and ask them directly about the preferences and concerns, but these data are not sufficient to predict the behavior of customers, and provide a product that meets their needs already.

Tool helps you to Dynamic Yield in identifying the interests of your target audience, and to predict also the safety of long-term purchases, by a solution depends on artificial intelligence to create emails customized.

Analyzes the application behavioral patterns of groups of buyers different, and generates related messages inserted in email templates. These personal messages are more effective because they take into account the intention of the customers, and help sales representatives to choose the most effective ways to showcase product.

Using a company Lacoste, the French for the manufacture of sports clothes, services, Dynamic Yield to get the best customer service, where customers of the company on the e-mail messages regularly with Special Offers are sensitive to their needs and their preferences. So you get these messages a higher response rate.

3. the tool Match2One:


Recent studies show that 82% of internet users feel the pressure when they see the ads useless on their screens, and this fact makes ads with precise targeting is inevitable for marketers who work in the field of e-commerce.

Managed Match2One of the use of artificial intelligence techniques to solve this problem, as the company has developed a tool for distributing ads precisely on the visitors to electronic stores who need to become clients. Used this tool of machine learning to improve the behavioral patterns and buying habits have visitors.

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