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Intelligent Selling Services for SAP Commerce Cloud (ISS) supports merchants in enhancing the customer experience through AI-powered merchandising capabilities, taking the site visitor on a personalized product discovery journey, which eventually leads to higher order values and merchant profitability. In this blog post, you can read about how to add merchandising carousels to your e-commerce site to reduce bounce rates.
Sarah is employed as a merchandiser for BestRun's e-commerce site. In her web analysis tool, she sees high bounce rates from online searches and ads. On average, more than 70% of BestRun’s visitors leave after visiting only a single page. This causes customer acquisition costs to rise and leads to lost orders. To improve this situation, she needs to find a way to quickly catch visitors’ attention and present them with alternative products to entice them to stay on the site, even if the initial product did not interest them. She decides to do a quick test using the merchandising capabilities offered by ISS. She logs into the ISS Portal to create product mixes and strategies for related, trending, and complementary product recommendations. She then goes to SmartEdit to assign them to merchandising carousels on the product, home, and cart pages, respectively. Based on tracking of customer behavior and order data, these carousels now use AI to present customers with relevant product recommendations as they browse through the storefront. Sarah publishes the changes and decides to wait for a week to evaluate the results.
In the meantime, Peter, a customer, is looking to buy a new TV and types in the corresponding keywords in the search engine of his web browser. He types in a known brand name, plus the keywords ‘Ultra HD Smart TV’ and clicks on a result that leads him to the model’s product details page on the BestRun e-commerce site. The model does not meet his requirements, but right below he sees a carousel with related products, namely smart TVs from a couple of other brands, as well as similar models from the same brand. He clicks on one of the suggested products. He reads the product details and concludes that this is the model he has been looking for. He then adds the TV to the cart. Before checking out, he wants to see if the site has anything else that could interest him, so he goes to the homepage. At the top of the page, he sees a trending products carousel displaying a new sound bar model with great ratings. He adds this to his cart as well. He goes to the cart to review the products he has selected. On the cart page, he sees a complementary products carousel displaying a set of rear speakers compatible with his soundbar. He adds it to the cart, proceeds to checkout and places the order.
A week later, Sarah, the merchant, checks the merchandising reporting tool in the ISS Portal to see how the AI-powered merchandising carousels performed. From the report, she sees that the carousels have led to improved click-through and conversion rates. Eagerly, she goes to her web analysis tool to evaluate the bounce rate and general sales performance compared to last week. Not only does she see a reduction in the bounce rate, but also an increase in session duration, add-to-cart, and conversion rates, as well as a higher number of orders and higher average order value. Adding the AI-powered merchandising carousels had a significant impact beyond the initial business outcome she was aiming for, so she is now eager to take further steps to optimize the customer experience and merchant profitability by applying additional merchandising strategies with the help of Intelligent Selling Services.
To learn more, check out Part 2 of this blog post series, on how to Optimize Merchandising Results with Intelligent Selling Services for SAP Commerce Cloud (Part 2).
For a hands-on video guide illustrating how to set up product recommendations and merchandising carousels, please view this video trail.
Or if you’re just getting started on deploying ISS for the first time, your technical team may enjoy this video trail and blog post explaining how to set ISS up.
Sarah is employed as a merchandiser for BestRun's e-commerce site. In her web analysis tool, she sees high bounce rates from online searches and ads. On average, more than 70% of BestRun’s visitors leave after visiting only a single page. This causes customer acquisition costs to rise and leads to lost orders. To improve this situation, she needs to find a way to quickly catch visitors’ attention and present them with alternative products to entice them to stay on the site, even if the initial product did not interest them. She decides to do a quick test using the merchandising capabilities offered by ISS. She logs into the ISS Portal to create product mixes and strategies for related, trending, and complementary product recommendations. She then goes to SmartEdit to assign them to merchandising carousels on the product, home, and cart pages, respectively. Based on tracking of customer behavior and order data, these carousels now use AI to present customers with relevant product recommendations as they browse through the storefront. Sarah publishes the changes and decides to wait for a week to evaluate the results.
Reduce bounce rates and drive engagement with AI-powered merchandising carousels.
In the meantime, Peter, a customer, is looking to buy a new TV and types in the corresponding keywords in the search engine of his web browser. He types in a known brand name, plus the keywords ‘Ultra HD Smart TV’ and clicks on a result that leads him to the model’s product details page on the BestRun e-commerce site. The model does not meet his requirements, but right below he sees a carousel with related products, namely smart TVs from a couple of other brands, as well as similar models from the same brand. He clicks on one of the suggested products. He reads the product details and concludes that this is the model he has been looking for. He then adds the TV to the cart. Before checking out, he wants to see if the site has anything else that could interest him, so he goes to the homepage. At the top of the page, he sees a trending products carousel displaying a new sound bar model with great ratings. He adds this to his cart as well. He goes to the cart to review the products he has selected. On the cart page, he sees a complementary products carousel displaying a set of rear speakers compatible with his soundbar. He adds it to the cart, proceeds to checkout and places the order.
Peter's journey through the BestRun e-commerce site.
A week later, Sarah, the merchant, checks the merchandising reporting tool in the ISS Portal to see how the AI-powered merchandising carousels performed. From the report, she sees that the carousels have led to improved click-through and conversion rates. Eagerly, she goes to her web analysis tool to evaluate the bounce rate and general sales performance compared to last week. Not only does she see a reduction in the bounce rate, but also an increase in session duration, add-to-cart, and conversion rates, as well as a higher number of orders and higher average order value. Adding the AI-powered merchandising carousels had a significant impact beyond the initial business outcome she was aiming for, so she is now eager to take further steps to optimize the customer experience and merchant profitability by applying additional merchandising strategies with the help of Intelligent Selling Services.
View performance of AI-powered merchandising carousels in merchandising reporting.
To learn more, check out Part 2 of this blog post series, on how to Optimize Merchandising Results with Intelligent Selling Services for SAP Commerce Cloud (Part 2).
For a hands-on video guide illustrating how to set up product recommendations and merchandising carousels, please view this video trail.
Or if you’re just getting started on deploying ISS for the first time, your technical team may enjoy this video trail and blog post explaining how to set ISS up.
