Adobe /Magento Product Recommendation: Elevating your business with Adobe Sensei 

In the growing era, businesses endeavor to stay ahead of one another and deliver exceptional customer experiences. Talking about ecommerce companies, meeting and understanding the ever-evolving needs and choices of customers is prime to success. This is where the power of product recommendation comes into play, and Adobe, with its innovative solution, Adobe Power Sensei, takes it to a whole new level. 

In the world of ecommerce, Magento has established itself as a leading platform, empowering businesses to make online stores with seamless user experience. Analyzing the need for personalized product recommendations, Adobe has integrated its advanced AI technology, Power Sensei, into Magento, elevating the platform’s capabilities to help businesses grow. 

In this blog, we will delve into Adobe Power Sensei’s world and everything you need to know!

Product Recommendations – A Brief Introduction

Product recommendations are the most powerful tools in the market to boost revenue, increase conversions and stimulate shopper engagement. Adobe commerce product recommendations are powered by Adobe Sensei. It uses ML and AI algorithms to perform a deep analysis of mass visitor data. Product Recommendation can be found as a feature of the Adobe Commerce Cloud. 

To make data more engaging, relevant, and for a personalized experience, this data is combined with your Adobe Commerce catalog. 

With the help of adobe commerce admin, you can directly deploy, create and manage the product recommendation across the store views. These surfaced on the storefront as units with labels such as ” Customer who viewed this product also viewed.”

What is Adobe Power Sensei?

Launched in 2016, Adobe Sensei is a powerful machine learning and artificial intelligence tool that helps in improving the design and delivering the perfect customer experience. It helps analysts, marketers, creatives, advertisers, and business professionals to create effortlessly informed decisions and target marketing for better results. These are some things that are possible with the help of Adobe Sensei.

• Free your creativity 
• Personalize the campaign to get results 
• Speeds collaborations
• Makes ad budgets go further 
• Find insights to inform decisions

With the help of Adobe Sensei, both small and big businesses/brands can make use of cutting-edge technology at the affordable price. Once it is configured after installation, the storefront starts gathering behavioral data. The merchant can further deploy, create and manage product recommendations to the storefront directly from the admin panel. 

Here is one of the most potent products available in the Adobe Sensei- 

Adobe Sensei GenAI 

With Adobe Sensei GenAI, a new technology assists the customer experience teams in using natively embedded Generative AI to amplify their expertise and deliver better, more accurate, and personal customer journeys. 

1. Benefits of Adobe Sensei GenAI. 

• Personalized Experiences 
• Native Generative AI 
• Build for Enterprises
• Responsible Content

2. Feature of Adobe Sensei GenAI 

• Real-Time CDP 
• Market Engage 
• Journey Optimizer
• Experience Manager Assets 
• Experience Manager Sites 
• Customer Journey Analytics

Benefits of Using Product Recommendation with Adobe Sensei

Adobe Sensei offers a range of functionalities that assist in acquiring profound understanding, enhancing tasks and workflows, streamlining the process of making well-informed, immediate decisions, and enriching the capacity to generate and provide tailored eCommerce experiences to customers.

1. Revenue and Sales 

At the admin panel of Adobe Commerce, the merchant can easily manage and deploy product recommendations resulting in the an increasing the revenue and a boost in sales. The charts related to the clicks, views, impressions, and revenue are also very helpful. 

2. Streamline Workflow

Adobe has introduced a streamlined workflow in order to simplify the creation of product recommendations. When this feature is enabled, merchants can promptly suggest products to their customers. By integrating this functionality with the product recommendation feature, merchants can enhance their ability to improve the overall shopping experience for customers. This not only saves time for merchants but also enables them to deliver relevant and seamless digital shopping experiences.

3. AI-Driven Retail 

Adobe Sensei AI leverages machine learning algorithms to automatically analyze shopper behavior, enabling you to extract maximum value from it. Upon implementation, Adobe Sensei takes charge of customer data analysis by generating customer profiles based on their interactions with the website and its products. Utilizing this compiled data, it delivers appropriate recommendations for products, content, and videos that are most relevant to each customer at any given moment.

4. Different Types of Recommendations 

Sensei provides a variety of recommendation options for merchants to choose from, including trending items, similar products, customer views, popular purchases, personalized recommendations, and more. These recommendations are generated using artificial intelligence and machine learning algorithms that analyze aggregated shopper data in-depth. By combining this data with the product catalog, Sensei enables merchants to deliver engaging, relevant, and personalized experiences to shoppers.

Types of AI Product Recommendations Available in Adobe Sensei Product Recommendation 

To merchants, there are different types of ecommerce product recommendations available. The admin can either place the recommendation at the top of the page or the bottom of the page. The bottom of the main content is enabled by default, and it showcases the recommendations below the main content area and before any other content blocks on the page. Whereas the top of the main content showcases the recommendations above the main content area just below the top navigation bar.

These are the types of recommendations provided by the Magento Product Recommendation Engine.

1. Contextual Popularity Based 

• Most Purchased:- In the past seven days, the most purchased items by the shoppers have been recommended. 
• Most added to cart:- The items that are most added to the cart frequently by most of the users. 
• Most Viewed:- The items that are most viewed by the shoppers in the past seven days are recommended to the users. 
• Trending:- According to the popularity, the product item is being recommended to the users. 

2. Content Similarity Based

• More like this:- The users are recommended items that are similar to content and attributes. 

3. Shopper Based 

• Recommended for you:- On the basis of the past history and selection of the product, the items are recommended. 

4. Item Based 

• Viewed this, viewed that:- The recommended products that are viewed by the specific users on the repetitive time.
• Viewed this, bought that:- The users are recommended similar products and bought some other. 
• Bought this, bought that:- The customers are recommended the items that most of the users review and purchase. 

Types of Data Required for Product Recommendation

Product recommendations require certain data i.e.

• Behavioral:- Adobe Commerce and Adobe Sensei do not collect personally identifiable information. The data here is data from the shopper’s engagement on your site, such as items added to the cart, purchases, and product views. 
• Catalog:- These are the product metadata such as price, name, availability, etc. 

When you download the product recommendation module, Adobe Sensei aggregates catalog and behavioral data, creating product recommendations for each product type. This is then deployed to your store, resulting in a better product recommendation. 

How to Get Started with Adobe Sensei Product Recommendations?

To get started with Adobe Sensei Product Recommendation with Magento, here are some steps you can follow- 

Step 1- Sign up for the Adobe Experience Cloud Account

Visit the Adobe Commerce website and get started with the first step, and sign up for the account there. Fill out all the details, such as email address, create a password for the account, and then give some basic information that will include yourself and your organization. 

Step 2- Access Adobe Sensei Product Recommendations

Once you have an account ready in the adobe experience cloud now using the same credentials, you can log in to its console. From the console, you can navigate to the “Services” section and locate Adobe Sensei Product Recommendations. Click on the same and access the product. 

Step 3- Set up Your Catalog and Data 

To use the Magento Product recommendations, you’ll need to provide your product customer data and product catalog. The product information, including name, attributes, description, and customer data, should have their behavior and product history details to analyze their shopping pattern. With this data’s help, Adobe Sensei analyzes everything and provides the appropriate personalized recommendation to the users. 

Step 4- Configure Your Recommendation Strategy

Based on your business goals and objectives, define your recommendation strategy. Decide the area where you want to display recommendations, such as mobile apps, email campaigns, and websites. Also, choose which type of recommendation you want to put, such as related to the frequent bough together, related products, or personalized suggestions. 

Step 5- Implement the Adobe Sensei SDK

To integrate Adobe Sensei Product Recommendations into your app and website, you’ll need to implement the Adobe Sensei SDK. This provides the necessary tools and APIs to fetch and display recommendations. Adobe offers documentation and guides to help you with the integration process. 

Step 6- Monitor and Optimize Your Recommendation 

After implementing the Adobe Sensei Product Recommendations, with the help of the analytics and reporting tools provided, monitor the performance of your recommendations. Analyse metrics like conversion rates, click-through rates, and revenue generated to understand the effectiveness of your recommendations. Using this data, make sure to optimize your recommended strategy and make informed decisions. 

Step 7- Time to Time Improve Recommendations

Adobe Sensei Product recommendations use machine learning algorithms to improve over time. Regularly update your product catalog and customer data to provide accurate and relevant recommendations. Monitor users’ feedback and iterate your recommendation strategy to deliver a better user experience. 

Remember, Adobe Sensei Product Recommendations is a powerful tool, but it requires thoughtful planning and ongoing optimization to achieve the best results.

Why Choose Emizen Tech for Integrating Magento Product Recommendation Powered by Adobe Sensei?

We at Emizentech as a Magento( Adobe Commerce Cloud) Development Company, an excellent choice for product recommendation integration. Here are some points that we take care of while executing the process.  

1. Expertise in Magento

We are a renowned Magento development company with extensive experience working with the Magento platform. Our expert developers are well-versed in Magento’s architecture, functionality, and best practices. This expertise ensures seamless integration of Adobe Sensei’s powerful product recommendation engine into your Magento store.

2. Adobe Sensei’s Advanced Capabilities

Adobe Sensei is a great technology that leverages artificial intelligence and machine learning algorithms to provide intelligent product recommendations. We understand the intricacies of Adobe Sensei and how to harness its capabilities to enhance the user and experience on your Magento store. Our team can effectively configure and customize the recommendation engine to meet your specific business requirements.

3. Seamless Integration and Support

Adobe Sensei will be seamlessly integrated into your Magento store by us without affecting the current functionality. Following industry best practices, our team of specialists offers continuing help to handle any problems or worries that may come up during the integration process. This ensures that everything goes smoothly and that you and your clients have a pleasant experience.

Conclusion 

In this blog, we have covered various facets of product recommendations with Adobe Sensei. With the use of Adobe Sensei Product Recommendation, the business can gain a lot of benefits such as higher conversions, dedicated reports and matrics, time-saving and cost-effective, and many more. Though we cannot say that there are any definite marketing strategies or methodologies for driving better results, a personalized recommendation is a powerful marketing tool that can help you increase revenue and user experience.