How can you use product recommendations to increase your e-commerce sales? How can you offer a personalized shopping experience to your users with product recommendations? Read on and find out.
Cross-selling e up-selling are, without a shadow of a doubt, the most effective strategies for increasing your e-commerce sales and raising the average receipt of orders placed. To be materialized, they require dynamic product recommendation systems that, in the first case, will recommend products from a different but complementary category to the potential customer than their last purchase, while, in the second, they will show products that will push the user to spend more on the product they are buying.
But how do you set up recommendations? Let’s get some clarity.
Product recommendation: the basis of any dynamic up-selling and cross-selling strategy.
Product recommendations are, as the word suggests, shopping recommendations in which products are dynamically populated for each user who is browsing a Web page, app or e-mail, based on data about his or her shopping behavior or the occurrence of particular events, thus providing a personalized shopping experience. The selection of products to be shown to the customer is usually handled by a product recommendation engine that is responsible, based on input data, for choosing the most appropriate products to display.Product recommendations should be considered as the basic activity for all companies that want to offer a personalized shopping experience to their customers. We know that personalizing the user shopping experience is crucial in the e-commerce world: suffice it to say that, according to a study conducted by Accenture, 91 percent of consumers are more likely to buy products from brands that are recognized and remembered and that offer relevant product recommendations.
Thus, it can be said that consumers today expect a personalized experience while using the Web
Companies that personalize the browsing experience of their users thus see a 19% increase in the number of sales, while, more than 56% of users choose to visit again a site that offers them recommendations on products to buy. It is no coincidence that Netflix recently stated that its personalized recommendation engine is worth at least a billion dollars.The most famous example certainly remains the case of Amazon: according to data released by the company itself, more than 35 percent of total revenues come from purchases made through dynamic product recommendations.
Product recommendations: where can I use them?
Blendee, as a marketing automation platform, provides its users with its own product recommendation engine, which, combined with the ability to segment audiences, allows them to customize product recommendations at any level. The recommendations can then be inserted into various sections of one’s e-commerce:
- Home page
- Product Detail Page
- Category Page
- Cart Page
- Search Page
- Landing Page
- User Registration Page
- Checkout Page
- Other Page
You can, when creating the recommendation, select the type of algorithm you want to use to choose the products to show the user.
Product recommendation in Blendee: some successful examples
Let’s look at some examples of recommendations that can be cues for your marketing strategies with Blendee.
Saninforma
The online pharmacy has decided to focus on a customization strategy that we can call “total”.The web pages of the online shop are composed almost solely of recommended products.Let’s analyze the home page:
- Type of Recommendation: personalized recommendation by browsing history-that is, products are suggested based on those that the user has recently viewed.
- Audience: All audiences
- Condition: The product must not belong to the category Drugs and must be in stock.
The chosen recommendation allows products already previously viewed by the customer to be shown, reducing the time it takes the user to purchase.
Here is another example below:
- Type of Recommendation: trending recommendation-that is, the most popular products by amount of views and clicks are shown.
- Audience: all audiences
- Condition: The product must belong to the Christmas Showcase category and must be in stock.
The layout of the recommendation, as you can see from the graphic example, is perfectly integrated with the layout of the site.
Imetec
- Type of Recommendation: personalized recommendations-that is, products are shown from the user’s recent history.
- Audience: Users who are looking at the detail page of a product in the category.
- Conditions: The products to be shown are selected from a predefined list provided by the customer.
We have given above some examples of product recommendation implemented through Blendee, how about taking a cue from them and boost your e-commerce sales?
