A study conducted by Google showed that people were 40% more likely to exceed their budgets if they felt their shopping experience was more personalized. No wonder retailers across the globe are searching for innovative ways to deliver better and more relevant shopping experiences to their customers.
Although many e-commerce platforms provide their users with the tools required for building feature-rich websites, few of them can deliver the technology capable of completely personalizing the online shopping experience. This is because adapting your products and branding to your customers in real time is nearly impossible unless you’re able to leverage the power of artificial intelligence.
On April 14th, 2020, Adobe launched the Magento Product Recommendations extension for Magento Commerce users. This extension delivered the power of AI and machine learning through Adobe’s proprietary technology — Adobe Sensei.
What is Adobe Sensei?
Adobe Sensei is the AI-powered technology behind all Adobe products that allows its users to simplify creating and delivering personalized experiences. It integrates with the Adobe Experience Cloud to bridge the gap between ideation and execution using the data gathered across multiple digital touchpoints of a business.
It predicts customer behavior using aggregate data and allows businesses to tailor their content effectively to their customers’ needs. Adobe Sensei also provides insights into other aspects such as the advertising strategies of an organization by monitoring their campaign performances and forecasting impacts.
By predicting customer behavior and forecasting the impact of different advertising strategies, Adobe Sensei reduces the guesswork involved in advertising. As a result, certain users of the technology have reported an 81% decrease in the cost-per-click in their video advertising campaigns.
Artificial intelligence has always been a high-cost technology that’s inaccessible for most small and medium businesses globally. At the same time, giants like Amazon.com and Netflix have been using AI and machine learning to power their website functionality for years.
Through Adobe Sensei, small businesses can access cutting-edge technology at an affordable cost. You can integrate Adobe Sensei in Magento
Although Adobe Sensei is only available to those subscribed to Adobe Experience Cloud, Magento Commerce users can leverage the technology on their stores through the Product Recommendations extension at no extra cost.
Magento Product Recommendations
The Product Recommendations extension is a tool that helps retailers stimulate customer engagement, increase conversions, and boost revenue on their Magento stores. It facilitates the deployment of automated and targeted product recommendations that helps customers discover relevant products effortlessly as they make their way through the sales funnel.
Using AI on an e-commerce store helps merchants improve the customer’s buying experience while also saving valuable time that can be refocused towards growing other aspects of their business.
Benefits of using Magento Product Recommendation
1. Automated page tagging and catalog sync
Adobe ensures a seamless integration of Magento with Adobe Sensei that doesn’t require any coding or custom Magento development. They achieve this by tagging storefronts automatically to ensure everything is deployed without errors.
To avoid overloading the website servers when processing data, they sync the store’s catalog to a dedicated cloud service. This offloads the resource-heavy data processing to a dedicated server so that customers can enjoy engaging shopping experiences without interruptions.
2. Embedded admin experience
To ensure that store admins also enjoy a seamless experience, they’ve integrated the user interface of Adobe Sensei into the Magento 2 admin panel. This allows merchants to easily create, deploy, and manage product recommendations without leaving the admin panel.
Simplifying the management allows store managers to minimize distractions, save time, and stay on top of vital store performance metrics like views, clicks, impressions, and revenue while also performing other essential administrative tasks such as catalog and order management.
3. Streamlined workflow
Maintaining their focus on ensuring a seamless experience, Adobe has streamlined the workflow of creating product recommendations into well-defined and intuitive steps. Its documentation provides a detailed breakdown of the process that’s easy to understand and follow.
This reduces the time required to leverage its benefits by allowing merchants to start recommending products to their customers in a matter of minutes after implementing the functionality on their website.
4. AI-driven retail
Once implemented, Adobe Sensei takes over the shopper data analysis using multiple machine learning algorithms by creating customer profiles as consumers interact with the website and its products.
All customer profiles are saved as hashed entries in a database and include the entire digital footprint of the customer’s interactions with the brand and business across all their databases, devices, channels, and departments integrated with Adobe Sensei.
5. Multiple product recommendation types
Product Recommendations gathers two types of data to generate its recommendations:
- Behavioral data,
- Catalog data.
Behavioral data collects data from a customer’s shopping experience, such as viewed products, items added to a shopping cart, and past purchases. At the same time, catalog data contains product metadata like SKU, price, name, and availability.
By collecting and analyzing this data, it generates nine different recommendation types that can be configured to be displayed in various locations such as the home, catalog, product, cart, and order confirmation pages.
The following table lists the recommendation types and their possible placements:
6. Page Builder compatibility
By making the Product Recommendations extension compatible with the official Magento Page Builder, Adobe has helped merchants fill the gap between content management and intelligent merchandising. Using the Page Builder’s drag-and-drop functionality, merchants can intuitively place product recommendations across the website pages.
They can also add recommendation units to various content types such as blocks, dynamic blocks, pages, and even individual fields. By assigning dynamic blocks to different customer segments, they can refine their recommendation targeting for specific customers.
Moreover, they can customize the Page Builder’s recommendation units to match their brand’s color and styling without developer assistance.
Other ways of leveraging AI in Magento
The capabilities of leveraging AI with Magento extend well beyond Adobe Sensei. Rapid innovation across the globe is helping more businesses introduce AI and machine learning in other aspects of their e-commerce operations.
Here are a few more ways you may use AI to boost your business.
Inventory management
Solutions powered by artificial intelligence can streamline the inventory management process of businesses while increasing efficiency. When it comes to inventory, efficiency means maintaining the right stock levels without ending up with dead-stock in your warehouse.
AI-powered inventory management can analyze your website’s sales trends and anticipate potential changes in product demand. This helps to avoid overstocking and significantly reduces the chances of running out of stock of popular products.
Marketing
Using AI to support your marketing efforts can breathe new life into your campaigns by tailoring them to your audience more accurately. After all, a customer is unlikely to find a marketing email annoying if it contains content that’s relevant to their interests.
Email marketing that’s powered by AI can pull data from various digital touchpoints and consolidate all information to provide better insights into the customers and their preferences. With such insights, you can easily create customer segments on your Magento store to target using personalized promotions.
Product trials
Product returns and refunds due to incorrect sizing are plaguing e-commerce businesses. Recent innovations in augmented reality have led to the development of applications capable of measuring clothing size using images and allowing customers to try on products virtually.
One such example is the SPEQS app that allows users to virtually try on eyewear before making a purchase. The app was integrated into Magento using its REST API.
Customer service
Retailers can also use AI to assist with customer service on their Magento stores. In recent years, the development and adoption of AI-based chatbots have seen rapid growth. The latest Business Insider Intelligence shows that nearly 40% of users worldwide prefer interacting with chatbots over virtual agents.
These chatbots can even be integrated into the store to access product attributes and other store data to allow customers to interact with them via online chat to address frequent customer service issues.
Say, for example, you’ve implemented a Magento event management extension on your website to manage appointments for your business. When customers who’ve booked an event ticket or webinar wish to cancel, reschedule, or update their booking, they would be able to do it themselves using a chatbot that’s integrated with your store instead of having to jump on a call or emailing your customer service department.
The future is here
The scope of AI in Magento extends far beyond sales and advertising to other aspects of running a successful e-commerce business, such as website security and even offline warehouse management. Although some might argue that implementing AI into their business is expensive, it isn’t meant to be a short-term investment.
AI, just like a well-built e-commerce store, is a long-term investment. When implemented correctly and integrated properly into your Magento store, it can save your business money and fuel its growth for years to come.