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Due-Home achieves an 88% conversion increase with Retail Rocket online personalization

Due-Home achieves an 88% conversion increase with Retail Rocket online personalization

Due-Home.com is an online store with a wide range of furniture and decorative products for both home and office. As defined on the website, they are driven by a passion for creating memorable interiors and environments in which objects are as important as the experiences lived in them. To achieve this, Retail Rocket also plays a fundamental role since the creation of a unique experience for each customer begins within the online store.

Due to this fact, the mentioned goal was the main reason that led Due-Home to implement the Retail Rocket platform back in 2017. It is the integration of our Artificial Intelligence technology that allows the online store to personalize the entire customer journey: from the moment a user enters the web until after receiving their order.

As we can see in the Due-home case study already carried out in 2018, the e-commerce store managed to increase its sales by 30% with Retail Rocket technology.

Let’s see below how the online shop in 2020 continues to obtain excellent results with the online and email marketing campaign personalization.

Retail Rocket personalization for the online store

Furniture is not the kind of goods bought on impulse. The customer needs to reflect and compare the products that best suit their needs before adding them to the cart. Given that, we have enhanced the AI personalization on the following pages where alternative items’ analysis and the purchase decision take place:

  • Homepage
  • Horizontal category menu
  • Category page
  • Product page

Recommendations on the Homepage 

A good e-commerce personalization strategy begins on the homepage, where the user’s journey in the online store also starts. The amount of time the visitor stays on the web will depend on the interest it arouses. To achieve their attraction and drive them to continue the purchase process, recommendation blocks based on user behavior in real-time are effective.

However, what to show when a user enters the web for the first time, and there is still no information about them? In this case, the bestseller blocks and products recommendations based on the other users’ behavior are an excellent resource.

Recommendations on the Homepage’s horizontal category menu 

Recommendations within the horizontal category menu are also displayed on the home page. That makes it easier for the user to search for products, simplifying the visitor’s journey on the website and improving the customer experience in the online store. All this, in turn, means an increase in visits to the product page, where the probability of finishing the purchase is higher.

Category page personalization

The category page is one of the ways that allows the user to show the options that best suit their interests by type. It is also here where the customer defines their preferences by comparing similar items.

Product page personalization

The fact that a visitor gets the product page to review the characteristics of each item is an indication that there is interest in making the purchase.

This stage is when more collected user’s information is available and where, according to the results obtained, the recommendations are more effective. 83.6% of Due-home’s revenue from personal recommendations comes from two blocks included on this page: 48.5% from similar or alternative products and 35.1% of the revenues come from items frequently bought together.

 The selection of products commonly purchased together is a new and tailor-made block. The online store has obtained excellent metrics with it, especially by increasing the average order value, as well as the number of items and product lines per purchase.

Effects of recommendations in figures 

Products per order

Unique products per order Average order value (AOV)

Conversion 

Effects of personal recommendations

+29.11 % +35.24 % +25.56 % +87.95 %

Email marketing personalization: trigger-based emails’ recommendations 

The storage’s user information in real-time allows the e-commerce store to hyper-personalize the entire customer journey: not only in the online store but also once the user either completed the purchase or abandoned the website.

Email personalization is an excellent tool to retain customers and to build the loyalty of those who have already purchased.

Due-home has carried out the automation of trigger-based emails for the following scenarios:

Abandoned search 

If a visitor that has previously made an internal search leaves the website, Retail Rocket will send them personalized recommendations based on the keyword they used.

Abandoned search for non-available products

If a visitor abandons the online store after searching for a product that is not available, a triggered email with similar products to the one that is out of stock will be sent to them. They will be notified when they are back in stock.


Abandoned category

If a visitor didn’t reach the product page and only browsed the category page, they will get a reminder with the most popular products and novelties from this category.


Abandoned viewed product

When a visitor leaves the web after having viewed some product, they will receive an email with personal recommendations based on the viewed products. 

Abandoned cart

This scenario is one of the world’s most popular trigger-based emails. If your customer added products to the cart and didn’t complete the purchase, they will get a reminder of the abandoned cart and personal recommendations based on it.

The Post-purchase scenario: the next best offer

A customer that has purchased in the online store will get an email with the forecast of the next most probable items to be purchased based on their interests and previous order. 

Newsletter Reactivation’s scenario

If a customer did not visit your website for a long time, they will get a reminder email with personalized recommendations and new products on the online store based on their interests.


Email marketing recommendations in figures

Open rate

Conversion rate

Average order value (AOV)

Email marketing recommendations in figures

29.86% 

3.40 %

+5.00 %

 

Conclusions

The obtained results show that after three years since the Retail Rocket technology’s implementation, Due-home continues increasing the key metrics thanks to a comprehensive online store’s personalization.

  • The implementation of Retail Rocket AI technology generates about 13% of the online store’s total revenue;
  • The order conversion when using web recommendations is twice higher;
  • The number of products per order increased by 29.11% on average;
  • The number of product lines per order increased by 35.24%;
  • The average order value with Retail Rocket recommendations was 25.56% higher in the site and 5% in email marketing.


Due-home’s testimonial

After three years since the integration of Retail Rocket platform, the AI personalization technology continues to help us increase orders month by month. The increase in key metrics, the team’s excellent job, and the simple management of the tool are the keys to our satisfaction with the service. 

Jordi Ordóñez, Marketing director of Due-Home

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The art of personalization at Design Warehouse online shop: how to achieve 17.5% revenue uplift with Retail Rocket AI platform

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