What is Episerver Product Recommendations?
Episerver Product Recommendations is a next generation personalization tool powered by AI and machine learning. With Product Recommendations, you can easily enable personalized recommendations for products in your catalog throughout your website, mobile app and email.
Manual personalization can be a daunting and cumbersome task, especially for B2B organizations who have tens of thousands of SKUs in their catalog. However, with Episerver Product Recommendations, B2B companies can automatically offer the right products, at the right time, to the right customer. It is real-time suggestive selling.
Many manufacturers and distributors are well-known for their customer-first approach. They pride themselves on delivering the highest quality products and unparalleled customer service. B2B companies know their customers well and have built their businesses around relationships. However, when you use product recommendations you can deliver experiences that are data-driven and hyper-relevant by leveraging intelligence. It’s the superior customer experience you’re accustomed to delivering, except it’s all digital.
What benefits can product recommendations bring to B2B companies?
Product recommendations have the potential to help B2B companies provide a more targeted and personalized experience that helps drive engagement, create efficiencies for your team and drive revenue.
Drive engagement with always-on personalization
By leveraging comprehensive data about your users’ sessions, micro-factors like time of day or channel, and other successful purchase journeys, Product Recommendations help companies deliver hyper-relevant, data-driven recommendations.
Product Recommendations offer a great way to tell your users, “We understand you and we can help solve your challenges.” It’s like a concierge service. You can predict your customers’ needs before they do. A personal profile is created for every visitor, enabling you to provide personalized recommendations at an individual user level.
Personalized experiences will also have a positive impact on website KPIs like time on site, engagement, conversions and others.
Build team efficiencies
By allowing AI and machine learning to drive product recommendations, you create efficiencies for your team. You let the machine learning algorithm optimize for the best product without requiring you to setup manual rules that are often difficult to create and a pain to maintain. Instead, your team can focus on other responsibilities, while you let the AI genius run through the site.
In addition, the Product Recommendations dashboard brings your team actionable insights that help you optimize your program and in turn, your site. Quickly and easily identify emerging trends and better understand how your products can serve specific customers.
By enhancing your cross-sell and upsell strategy you can drive more revenue for your organization. There are multiple ways product recommendations can help drive revenue:
- Increase awareness of the breadth of your product catalog
- Evaluate margin by products
- Increase lines per order
- Increase conversion rate
- Grow revenue from abandoned carts
While product recommendations are designed around helping organizations increase sales, reporting and managed services are added benefits. With Episerver, you get a team of experts who can help guide you by recommending campaigns and A/B tests and a performance dashboard that helps you track success of certain product recommendations.
How do Episerver Product Recommendations work?
Product Recommendations use Episerver’s machine learning algorithms optimized for commerce to deliver personalized product recommendations in real-time. Our machine learning algorithms help companies drive revenue by optimizing which products are shown to each visitor based on real-time behavior, order history and similar journeys. What exactly does that look like?
First, let’s break down the kind of data product recommendations utilize:
Catalog Data – The data found in your B2B ecommerce platform like products, categories, attributes, costs, etc.
Customer Behavior Data – The data your users create from their views, searches, additions to cart, checkout history and past purchasing behavior.
Catalog and customer behavior data are fed into a profile store where the association of which products to recommend to which customers is generated. The profile store then enables you to send product recommendations to any device (desktop, mobile apps, emails, etc.) and also feeds into the Product Recommendations performance dashboard to track success.
Episerver’s implementation partners can help you get Product Recommendations up and running in a matter of one or two weeks. From there, you can start making recommendations immediately. Many companies will spend the first 30 days or so allowing Product Recommendations to learn more, take order history and turn on machine learning recommendations.
Product Recommendations are setup through widgets on your site. You can apply product recommendations on any page with a widget. Product recommendations can be applied to pages where your customers are browsing, like brand details, homepages and search results or areas of your site where customers are making buying-decisions like order confirmation, review and pay and my list.
Additionally, for B2B customers, Product Recommendations is not limited to understanding online order history, it takes advantage of all order history – not just online but offline as well, a key element to any B2B company’s omnichannel strategy.
Use Case: Dakota Supply Group leverages Product Recommendations to make it faster, simpler and easier for customers to do business with them
DSG decided to invest in product recommendations because to do it manually would be an enormous task. Instead, the product recommendations tool harnesses the power of AI and machine learning to access years of omnichannel order history, current history and in-session behavior and, in turn, recommend relevant products to their customers and deliver a hyper-personalized experience.
“At DSG we’re obsessed with making it faster, simpler and easier for our customers to do business with us. Episerver Product Recommendations was easy to implement on our ecommerce site and helps us achieve all of those objectives,” said Todd Sisson, Digital Commerce Manager at Dakota Supply Group.
Over the course of just 30 days, 2.84 percent of DSG’s online orders were influenced by product recommendations. DSG runs product recommendations on pages including brand detail, home, cart, my list, order confirmation, search results and others.
“Our goal with our website is to create an atmosphere that’s similar to that of Cheers – where everyone knows your name. Leveraging Product Recommendations gives our customers the sense that we know who they are and can provide them with expert guidance and solutions to solve their problems,” continued Sisson.
In today’s digital-first world, it’s becoming harder to stand out online. However, with Episerver Product Recommendations, B2B companies can provide their customers with a hyper-relevant experience and up their ecommerce game.