What are the 3 key factors to optimize your sales thanks to personalized recommendations?
.17 Feb

What are the 3 key factors to optimize your sales thanks to personalized recommendations?

The benefits of the recommendations on the e-Commerce sites are no longer to prove: very clear improvement of the User Experience, loyalty, increase of the average basket and increase in sales. That’s how 35% of Amazon’s revenues are generated by their recommendation engine. And according to an Accenture survey: “75% of consumers are more likely to buy on a site that offers them personalized recommendations.

There are hundreds of Cross-sell and specialized recommendations modules in Prestashop addons marketplace. Yet the majority of sites ignore the performance of its recommendations or finds disappointing results. How to optimize your sales thanks to personalized recommendations?

1) Seduce your customers

The first factor is the improvement of the User Experience. The recommendations inspire them to come up with product ideas to buy. It makes them want to discover the products of your site. The navigation between the recommendation banners is extremely intuitive. It creates a link with your customers who appreciate being recognized when they come back to your site.

Here are 5 levers to seduce your customers:

Relevance:

The relevance of the recommended articles is paramount because if no customer clicks on your recommendations, you will have no impact on their experience and your sales.

If your catalogue has a small number of products, you can easily associate with each product a dozen similar and complementary products. But when your catalogue grows, it becomes much more difficult to know the good associations and updates become very tedious.

The choice of a customization engine based on Artificial Intelligence improves the relevance of Cross-sell and Upsell recommendations. Collaborative filtering algorithms used by Amazon analyse all interactions between all users and all products and deduce the best associations between products and between users. They statistically find the best recommendations that will have the greatest impact on most visitors. Learning speed also has a significant impact on relevance for new sites with reduced traffic.

Cross-sell:

Most CMS classify recommendation modules in the Cross-sell category. But the Cross-sell has a specific objective: to present complementary articles to those that are displayed.

The banner is usually placed at the bottom of the basket or product card. Cross-sell makes the visitor want to buy complementary products to the product he has chosen. It often has a small price that allows a purchase of impulse without thinking. It also makes it possible to make the delivery costs profitable. It must not disturb the current purchases. It increases the number of items per basket and the average basket value. Its average impact on turnover is often of the order of 5%.

Upsell:

The Upsell banner is usually placed at the bottom of the product page and offers similar items to the product displayed in close categories with equal or greater price ranges.

The titles of the most used banners are: “Also viewed by our customers”, or “similar products”.

The visitor can browse from product to product via Upsell recommendations. Each banner widens his choice and engages him more in the discovery of the articles of your site. The Upsell has a major impact on frugal visitors who like to compare similar products and anxious visitors who are comforted in their choice by the wisdom of the crowd. Its average impact on turnover is similar to that of Cross-sell.

Personal Matching:

Personal Matching recommends the most relevant products from your visitor’s browsing history. Each recommendation is personalized when the visitor views the page because each visitor is unique. The banner is usually placed very early in the shopping journey on the homepage and category. The manual rules are unable to present personal matching recommendations.

These are the most relevant recommendations that inspire and appeal to your visitors. They have the biggest impact on your turnover.

Coordinate essential recommendations on all your pages

Consumers have typical profiles: novice, demanding, frugal, anxious and loafer.

To accompany them all throughout their purchase journey, you will complete the recommendations based on Artificial Intelligence with more classic recommendations: Bestsellers, Sales, and New arrivals and Recently viewed. They are much more relevant on the category pages to better target the products that interest your customers.

The joint management of the 7 types of essential recommendations improves consistency of recommendations and your productivity.

These 5 levers allow our customers to increase their sales by an average of 10 to 20%.

2) Simplify your life

The benefits of personalized recommendations are attractive. But is it worth the money? Here are 2 levers to simplify your life:

Automatic learning

If you manually configure the best associations between similar and complementary products you must update each product sheet. This operation takes on average 3 minutes. It can reach 7 hours with 150 products and 50 hours with 1500 products.

AI algorithms automatically discover the best associations between products. You save this time each time you update your catalogue.

Configuration in a few clicks

This time saving can be lost if you must spend days understanding a configuration manual filled with algorithm names, and settings to adjust. The first customization modules dedicated to larger sites required months of integration and development.

To improve your productivity, it is essential to choose a module that automatically finds the best settings. For example, the MyDreamMatch module allows you to activate each type of recommendation on each page in 1 click. You can optionally change the title, the number of products to display on each banner or move the banner on each page in 1 click. The banners integrate perfectly with your design by taking the style of your site. A unique method of automatic placement of products to highlight on all banners of your site allows you to master your business rules and save a considerable time.

The simplification of the configuration makes Artificial Intelligence’s personalized recommendations accessible to all e-commerce in order to benefit from the same advantages as the major players.

3) Optimize your performance

An Analytics page on your dashboard will allow you to measure the performance achieved. For example:

  • The number of recommendation clicks over time
  • The impact of recommendations on your orders and your revenues
  • The display rate and click rate on each recommendation banner

Also do some tests on the choice of banners to present on each type of page, the title and the location of the banners on each page.

A performance diagnostic after one month of service usage will help you optimize your performance.

The data analysed by the recommendation algorithms provide you with essential information about the interactions of your visitors with each product and category. For example, the number of views, clicks of recommendations, additions to cart, abandonment, purchase and related revenues. So, you have the means to immediately understand the contribution of each product and each category to the animation of your site and the impact on your sales.

For example, a Salesforce survey of 250 million visits to e-commerce sites found that personalized recommendations by the AI ​​have a significant impact on sales. In fact, visits for which the customer has clicked on a recommendation represent only 7% of visits but generate 24% of orders and 26% of turnover. In addition, visitors who click on the recommendations have an average basket of 10% higher than the others and are twice as loyal. MyDreamMatch measured even better results.

You have all the cards in hand to analyse your data, manage your recommendations and increase your sales by simplifying your life.

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