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When designing the best-in-class shopping experience on an ecommerce platform, we have to take into consideration the user experience at every touch point. We’ve identified two foundational types of behavior as users discover products on an ecommerce site or app:
Undoubtedly, Search plays a central role in the end-user experience on an ecommerce website. The impact of effective search solutions on key merchandising performance metrics cannot be underestimated. There are multiple ways in which a Search and Discovery experience on your platform can be enhanced and optimized for various ecommerce user-journey scenarios:
In the example below, sporting goods fashion retailer Gymshark is boosting its revenue using Algolia Recommend API powered by machine learning in addition to powering Gymshark’s site with Algolia Search:
Gymshark’s success metrics:
To learn how leading ecommerce retailers leverage the AI-powered Recommendations engine’s capabilities to crash their digital merchandising goal: Gymshark adds Algolia Recommend to handle crucial Black Friday period.
Recommendations are the smart way to leverage AI capabilities to increase discoverability, upsell related or frequently bought together products, and increase average order volume and boost revenues.
There are multiple ways to use recommendations on category pages and beyond:
For example, on a category page featuring running shoes, users can see recommendations for products that are frequently bought together with running shoes, such as socks.
For example, a user clicked on a light blue color t-shirt. They are not sure this product completely matches their style. They notice a similar blur t-shirt under the “similar product” gallery that is exactly what they are looking for and add it to their cart. Additionally, they see a short under the “frequently bought together” gallery that is part of a matching set with their t-shirt, and decide to add this product to their cart, as well.
For example, a user has added a jean and a blouse to the cart and are now ready to check out. Your store offers free shipping for orders over $99, but this customer’s order falls short of the free shipping minimum. This is an opportunity to suggest additional products, such as matching belts, socks, or hats. This is a win-win situation for the company, gaining more revenue and order volume, and for the customer, receiving a discount in the form of free shipping.
Leveraging Recommendations capability at multiple touch points in the customer journey and combining it with advanced Search capabilities empowers ecommerce retailers to provide their users with a superior user experience on their platforms. Implementing Recommendations helps increase order rates, “add to cart” rates, average order value, and items per order.
To learn how to implement product recommendations on your ecommerce website with minimal effort, view this short live coding video recording.
To learn how to leverage product recommendations on high-importance sales events, such as Black Friday, refer to: How Composable Commerce can boost customer spending during Black Friday and Cyber Week.
For B2B retail Recommend implementations, refer to B2B commerce digital transformation: merchandising and AI optimizations.
Program Manager for GTM Strategy