E-commerce is practically a science by now. In an ecosystem of ferocious competition, online store managers restlessly seek the way to increase customer satisfaction and thus sales. A technique which has proliferated in recent years and which provides very high value is cross-selling.
The concept is simple: offering customers products that complement their purchases. For example, an airline can offer hotel rooms or rental cars in the city destination. The monetary profit is obvious: cart size increases. In addition to its most obvious aspects, recommending purchase products has a number of interesting effects, such as the improvement of the useful navigation experience or catalogue discovery.
However, the mere fact of offering alternatives need not yield any of these benefits. Many stores include a cross-sale recommendation banner in every product page on the basis of such criteria as belonging to the same category. This kind of recommendation might be rather catalogues as up-selling (or even down-selling), as in many cases the customer will change his or her mind and buy one of these alternatives, but not both products.
A very common type of cross-sale is based on product co-occurrence in other users’ carts (“users who purchased this product also purchased…”). This very Amazon-like suggestion can work very well if you have a large number of data. In some cases, these suggestions are manually created by configuring discount packs. However, these techniques are based on a premise that can be dangerous: supposing that all customers share the same purchase profile.
In order to carry out quality cross-selling and thus maximise the probability that the ticket price increases, the two main dimensions of e-commerce should be taken into account: on the one hand, the catalogue; on the other hand, customers’ purchase profiles (both individually and with respect to other similar customers). The complexity of cross-sales in this case increases considerably. Many managers of online stores are aware of the potential benefits of including personalized recommendations, but either lack the necessary structure to develop them or everyday problems are simply given precedence over any kind of potential innovation.
Luckily enough, there are providers such as BrainSINS out there in the market, offering this type of service as Software as a Service (SaaS), which can be integrated in a very simple way in any platform.