How do you merchandise your Shopify store like Amazon?
The main objective of eCommerce merchandising, whether you have a small or extensive product catalog, is guiding your visitors through the buying journey. So, the act of merchandising ensures visitors get a consistent, on-brand experience; no matter how they arrive on your site or navigate around it.
In physical retail stores, merchandising relies on simple tactics applied across the entire store. The number of paths visitors can take through the store is small, shopping behavior is quite well known and changes only during seasons or special events.
For online stores, merchandising teams are faced with a complex problem – the need to apply and manage many different strategies all at once. Unlike physical stores, information about most online visitors is unknown and often changing – these visitors can follow an endless number of paths, while their preferences and behavior changes frequently.
How Amazon merchandises across the entire Customer Lifecycle:
As the first stage in a customer’s lifecycle, this is where new visitors are being exposed to your brand for the first time. They may enter your website at different pages.
At this stage of the customer lifecycle, a visitor is showing signs of interest on your site. Behind the scenes, session-based algorithms are detecting those signals of interest and modifying your recommendation strategy to create more relevant suggestions.
It’s well established, the buying stage starts when a visitor adds something to their cart. From here, your merchandising goal is to increase the average order value. You would typically do this through various up-selling or cross-selling recommendation strategies. When it comes to Amazon.com, it appears they introduce up-selling and cross-selling recommendation strategies even before a visitor adds a product to their shopping cart.
This stage of the lifecycle is about returning visitors and customers. Recommendations for the ‘Discover’ stage are dynamically populated based on general site results and incoming visitor attributes. However, as soon a visitor starts engaging with the site – with the system detecting their interests in real-time – the recommendation strategies radically alter.
And it’s not only the products that change but also the types, quantity, and ordering of the recommendation templates. As the climactic phase of the Customer Lifecycle, ‘Engage’ further demonstrates the depth and breadth of recommendation strategies available to use on your own eCommerce site.
HiConversion Recommend’s merchandising strategies connect the advanced technology behind Amazon’s personalized recommendations to your daily operations. What this really means is you can now benefit from the power of machine learning without needing to understand it.