The Case:

A B2C shop for car accessories and spare parts does not show a bad performance: steadily growing sales and more purchases from year to year delight the operator. The number of articles per purchase is low, but the shop uses numerous methods for cross-selling and up-selling.

The Goal:

The cross-selling options “related products”, “top sellers”, “newest products” and “other customers also bought” bring only moderate added value and should be optimized..

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The problem of article recommendations

Giving customers good recommendations during the shopping process is not an easy task. The customer is usually preformed with a purchase intention and has an idea of what he wants to buy. Of course, there are also casual shoppers who want to take a bargain with them or spontaneously purchase an item without prior intent. But on the whole, the purchase requirement defined in advance is certain, especially in the case of spare parts shopping, as in the present case.
In order to provide the customer with the best possible support during the shopping experience, shop operators have many ways of flexibly placing the articles in the immediate vicinity of the article the customer is looking for – filling the shelf around the article in a quasi specific way. For example, the following options are available for such cross-selling:

  • Customers also bought…
  • Topseller
  • Weather deals
  • Newest products
  • Discounsts
  • Related products

For this case, we optimized related products and measured

    1. Higher click rates on product recommendations
    2. More clicks with purchase
    3. A significant increase in revenue from related products clicks

Find out more and download our whitepaper here (German)!