56% of users prefer to shop online at home


Two major analytical agencies Burke and Thrive Analytics conducted a study on online purchases, the places where they are committed and the mobile devices through which they are carried out. It turned out that the most popular device is a smartphone, and the most popular place is a sofa that users have at home. Purchases in the global network, as practice showed, do not have to be done in shopping malls or on the streets near stores.

The survey involved more than 1100 consumers from the United States. As a result of the research, it was found that 56% of them buy goods in online boutiques while at home. 28% of respondents like to “buy” on the run, 9% – in the store, 5% – at work and 3% in the car. Another interesting detail is that not all use the phone for commercial purposes. As it turned out, the smartphone is mainly used to collect general information about the product / service or reviews about them, and also to compare prices in several stores and find out about the availability of the desired product in a particular store. Hence we conclude that marketers were wrong, believing that users entering inquiries about products are already at the bottom of the sales funnel. In fact, at the moment when users begin to search for information about the product, they only fall into the top layers of the funnel. By the way, among the most popular information requests in this segment are the following: “popular models”, “where to buy”, as well as the “indicative price”.

Among users looking for information about the required product in the open spaces of the network, 57% collect only general product data, 43% get acquainted with reviews and reviews of the product, 42% compare prices in different stores, 41% make a discount on the goods, 29% check the availability of goods in the online store, and 8% read the manufacturer’s warranty for the desired product. It turns out that the time necessary for users to make a purchase in an online store should be much more than what marketers expected.

The author of the article: rSEO

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