When visitors enter an online store and see a product of their interest, they rarely purchase immediately. Before making a decision, they usually check the products’ features and compare them with those from similar products and other alternatives, especially when it comes to technology, electronics, and other significant purchases. Since it usually takes more than a day to complete an order, the buyer will have time to switch between different devices several times. That’s why retailers’ mission is to provide the user with a unique and convenient shopping experience for both desktop and mobile versions.
Since customer behavior differs between devices, it is crucial to understand that product recommendations should also be different, developing a marketing strategy for both versions.
Thanks to the Artificial Intelligence capabilities, you will comprehensively personalize the online store for all versions and customer communication channels. Using the user’s behavioral information from different devices and collecting it in a single source will allow you to create a 360-degree buyer profile. Updating this data in real-time will let you segment your audience and automate your marketing tasks to show the most relevant offer for every user, thus increasing their satisfaction and business revenue.
Our recommendation to achieve this is to design a marketing plan based on:
- Developing a comprehensive personalization strategy to increase customer loyalty by enriching their 360-degree profile.
- Determine the merchandising strategies that work best for the desktop and mobile versions;
- Testing and implementing the most effective hypotheses to improve KPIs;
The importance of personalizing the recommendation blocks for desktop and mobile versions
Shopping on a mobile device allows the user to see less information than on the desktop version. Therefore, it is essential that on smartphones or tablets, whose screens are smaller, the recommendation blocks work as efficiently as possible, leading the customer through the sales funnel.
Using as much data as possible previously collected about customers’ interaction from all the online store’s versions will allow the sophisticated mathematical model to make a relevant offer to every customer at the right time and channel.
The AI technology implementation provides the user with a unique shopping experience, regardless of the device used. Personalizing the online store’s Customer Journey will allow, for example, to select and send a product to the cart from the mobile version on your smartphone, and then go to the website’s desktop version and continue browsing the catalog. Artificial Intelligence will process all the data and consider the behavior of the same customer on different devices and versions.
Using the website’s mobile version also opens up new possibilities to complete the 360-degree customer profile. This data will be updated in real-time, gathered in a single profile, and used to segment the audience. The more we know about the customer, the better the chances of making the most relevant offer and finishing the purchase.
Considering that customers’ behavior and expectations differ across versions, we recommend developing a marketing strategy for every type of device. Besides that, sometimes even the audience may also change: some buyers may use only a computer to select a product, while others may use only a smartphone. Therefore, what works efficiently on desktop may be less effective on the mobile version and vice versa. While for some sites, the recommendation algorithms on different devices may be the same, they may be entirely different for others. You should make the best choice by testing the effectiveness in each specific case.
Let’s look at some examples of how to personalize the offer depending on the online store version to help each user find what they are looking for and get the best results.
#1 Personalize and rebuild the online store’s showcase in real-time for every user
Unlike physical stores, every visitor can get their personalized version of online shops adjusted to their particular preferences. Thanks to the most advanced AI technology, product characteristics such as color, size, brand, and price, among others, will be taken into account to determine when and what offer to show to each specific customer.
Supposing a new visitor lands on an online store for the first time, since nothing is known about their interests and preferences yet, they will probably feel attracted by the bestsellers bought by other customers. On the other hand, the showcase displayed to regular customers will offer a multitude of versions, as many as there are users. That’s because recommendations will be personalized based on the data stored with the buyer’s behavior on all the devices used.
In the Eldorado online store, the recommendation algorithms differ in different versions of the site. On the desktop version, a personalized product selection is displayed based on the user’s interests. On the other hand, on the mobile version, users are shown personal bestsellers based on their behavior and purchase history, i.e., products that other customers often purchase, matching their preferences.
2# Personal recommendations on the Product Card Page
When a user reaches the product page and shows interest in a particular item within the catalog, they provide relevant data about their preferences. We recommend integrating Artificial Intelligence in your online store and use this information to display related products and similar ones as an alternative. This way, you will help the user in their search by facilitating the shopping process. And to achieve the best results, it is highly effective to personalize recommendations for both versions.
In the Eldorado online store, the recommendation blocks are placed differently depending on the website version. For desktop, a selection of related items is displayed below the product card information, while in the mobile version, this block is located at the page’s bottom under other shoppers’ reviews. For example, customers viewing a TV will be shown related products, such as antennas and other complementary items needed for the installation. Offering products frequently bought together with the one a user is viewing will help increase the average order value and the online store’s revenue.
If the product a user is looking at does not quite fit their needs, displaying a selection of others with similar features is a perfect option that will help the user advance to the next stage of the sales funnel, preventing them from leaving the online store. While in the desktop version of the Eldorado, this block is located at the bottom of the page, in the mobile version, it is right below the product description.
#3 Search page personalization
When a visitor uses the search bar to look for a specific product, it’s a clear sign of interest for buying something in particular that will most likely be added to the shopping cart. Make the most out of AI and this willingness to purchase to show products that may interest the buyer based on their behavior and preferences to increase motivation and facilitate the search.
#4 Personalized recommendations when the search does not return any results
When a user does not get any search results, making a relevant and personal offer with similar products will increase purchase probabilities, preventing them from abandoning the website. For example, a customer searching for a specific brand of coffee beans might also be interested in other brands in the catalog.
5# Discounted product recommendation blocks
The promotions page of an online store is a magnet to attract buyers who want to purchase products with the best discounts. The Eldorado online store knows it and uses Artificial Intelligence personalization on this page to show special offers that will increase the number of happy visitors who find what they are looking for at the best price. In this case, both versions of the site use the same algorithm with the most popular discounted bestsellers.
6# Don’t Forget About Recommendations on the 404 Page
Often the 404 error page tends to be undeservedly forgotten when it comes to displaying product recommendations. But even if a customer reaches a non-existent page, showing a relevant offer is a perfect opportunity to get them to the next stage of the Customer Journey.
On Eldorado’s desktop version, new visitors are offered a selection of bestsellers of interest to other shoppers. Existing customers, on the other hand, are shown product recommendations based on their behavior and preferences. In the mobile version, the algorithm is different: here, the customer will only see personal offers based on the information stored in their profile.
Get the most out of Artificial Intelligence by adapting the algorithms for both versions of the website to help customers buy from any device in the most comfortable way possible. That will facilitate the purchase process, shortening the Customer Journey, increasing customer satisfaction and retention as well as your business’ revenue.