How Personalization Enhances Engagement And Sales in E-Commerce
Increasingly important for billing, e-commerce has become crucial for businesses. Therefore, several strategies are being adopted by the sites to optimize performance and increase sales. Today, product recommendation is one of the most commonly used tools to improve the user experience and also increase conversion.
But many websites choose a selection of items that are presented to all consumers who access the environment in a random and indiscriminate manner. The question is: If my preferences are different than yours, an e-commerce should not display the same products to me and you, right?
Exactly! Virtual stores that offer a more accurate product suggestion achieve results that not only translate into sales, but also increase the conversion, the average ticket and better use of the media. Thus, increasing the “Holy Grail” of digital marketing, ROI (Return on Investment). Most e-commerce businesses sin in recommending any product without intelligence. In order for this tool to be applied effectively, it is necessary to understand the behavioral profile of the site visitor, and then, according to the data collected, suggest products that are in fact relevant to the consumer.
This is what we call the personalization of the recommendation windows. This type of tool analyzes the visitor’s behavior online based on their browsing history in order to suggest products that have synergy with their interests or needs.
There are three main types of recommendations that usually bring better results in sales:
1) Recent browsing history recommendations – Identifies in real time the products and categories the customer is browsing and generates a history that is applied in real time in a recommendation block. With blocks of this type, a customer can easily find the products he/she likes. When he feels the need to close the sale, the products will be there and ready to be added to the cart. Findability is the word that defines this type of recommendation, since the products that the customer visited are always visible.
2) Similar products based on navigation – Different from the previous recommendation, in this case the solution will understand only the products visited by the customer and use this navigation to be accurate in whole windows. This is according to what that user demonstrates as intention purchase. With a customized home page the user experience is unique; the feeling is of being in a local store where he has been serviced for a long time, and the seller of that store already knows what he wants.
User Experience is the central term of this type of intelligence, since the ease in finding products that are relevant is the key point of this type of recommendation. The most expressive result is the increase in conversion, since the user has a few less reasons to abandon e-commerce.
3) Recommendation of supplementary items – When the customer accesses an item such as a mobile phone, e-commerce will recommend a memory card or accessory. Facilitating the purchase and not allowing the customer to make an “incomplete” purchase is the main attribute of this solution and the increase of the Average Ticket without a doubt is its greatest return. This strategy guarantees an increase in items / order and also in the average ticket of the site.
Even considering all the advantages offered by personalization, this type of strategy is not adopted in large scale. Example can be large e-commerce in Brazil, mainly due to the high cost involved. Since most of the companies work with artificial intelligence for data analysis, it makes the solutions quite expensive.
AUTHOR BIO:
This is Yousuf A. Raza, a professional content writer and digital marketing expert at Dream World Travel who enjoys writing, playing football and cooking during spare time.
