Personalization of the e-shop offer


Not so long ago, the personalized recommendation systems were mainly used only by companies that had the status of leading companies in the online distribution industry. In the personalization activities at that time, the company from the USA Amazon definitely came out. Currently, most shops on the Internet use these types of solutions. Therefore, it is necessary to become familiar with the specificity of this function, paying attention to its potential and its advantages.


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Benefits of personalizing the offer in e-commerce

The customization of the e-commerce offer is usually to tailor the offerings so that they fully or at least in large part coincide with the specificity of the previous Internet activity of the Internet user. So-called recommendation engines take into account various factors, such as the time of visiting a particular website, the search history, the purchase history and the date of the last visit. Based on all this data, suitable offers will be sent to the user in the form of a newsletter or as hints that will be displayed after registering with a specific portal. In this way, a potential customer learns that other consumers, for example, who have chosen the same smartphone model, have also bought a specific case for it. Thanks to such tools as the personalization of an e-shop offer, the customer receives information about the most popular products in a particular category. In this way, book lovers will find out, for example, which novels currently deserve the title Bestseller. The existence of systems like SaaS contributes to the fact that this solution does not have to be expensive, contrary to appearances.

How can you personalize the offer of the online shop?

Usually, the personalization of the e-commerce offer is based on dedicated recommendation systems. However, such a solution usually proves to be very expensive, which is why more and more smaller companies opt for the SaaS model mentioned here. Basically, working with this service is letting software available on the server of a particular software company. By entering appropriate commands in the HTML code, the recommendation engine is started.