Effective merchandising increases online revenue through higher conversion rates, higher average orders value, fewer cancelled orders and lower returns.
It is achieved through controlling the prioritization of product sequencing throughout the site so that retailers can tailor what they display.
GrapheneHC is a revolutionary new merchandising platform designed to provide retailers with all the tools they need to merchandise their online stores effectively.
Define the merchandising effects to be applied.
Retailers can choose from a range of pre-defined Merchandising Strategies such as High-value Trending or Popular New-In.
They can also create and edit an unlimited number of their own Merchandising Strategies to suit their business objectives.
Additionally, Merchandising Strategies control the look and feel of Page Elements, including Facets, Filters, and other attributes. These settings are easy to change within GrapheneHC.
Gain precise control over product prioritization.
GrapheneHC gives the retailer complete control over how products are sequenced on their site.
This includes determining the importance of attributes such as Color or Stock Availability, as well as defining the sortation order for items such as Price or Brand, etc.
The prioritization tools within GrapheneHC enable the retailer to merchandise down to an extremely granular level.
Define custom ranges for product attributes.
Enables retailers to determine the importance of product sequencing across a size, color, or price range.
For example, you could choose to promote women's dress sizes 8-12 more heavily than sizes 4-6 or 12+. Similarly, you could promote mid-priced electronic devices ahead of the cheaper or more expensive items.
Custom Ranges provide a more sophisticated sequencing option than standard linear min/max sortation and can be used for any numeric attribute associated with a product.
Define the conditions that determine when certain Merchandising Strategies will be applied.
Conditions can be almost any action or event on the site such as a search term, browsing a category, clicking on products, adding to basket, or even the device being used by the user to view the site.
Custom Triggers enable retailers to set up different Merchandising Strategies to match an action or event.
Create custom Merchandising Concepts.
Enables retailers to create and define what a Merchandising Concept such as "Winter Colors" or "High Definition" actually means in terms of specific colors, or resolution.
Merchandising Concepts can be created with any combination of product attributes, and can be used in conjunction with Merchandising Strategies, Custom Ranges and other features.
Multiple Merchandising Strategies
Combine Strategies to create powerful Merchandising effects.
GrapheneHC enables retailers to create a cascading sequence of Merchandising Strategies.
For example, a PLP page could be prioritized using a Sale strategy initially, followed by a Clearance strategy and finally a Descending Price strategy.
Combining multiple merchandising strategies can provide a sophisticated solution to complex merchandising requirements.
Decide where Merchandising Strategies are deployed.
Merchandising Templates determine where within a Page Element, Merchandising Strategies are applied.
Creating a Merchandising Template is like painting shapes on the page and using those shapes to determine where Merchandising Strategies will be deployed.
Define how to merchandise Fragmented Stock.
Enables retailers to determine what to do when a stock starts to fragment.
Options might include demoting fragmented stock from the Product Search or switching sales channels for the fragmented stock.
Additionally, GrapheneHC enables retailers to decide which attributes are used to calculate fragmentation and what their relative importance is in that calculation.
Automate the Merchandising process.
Auto-Merchandiser enables retailers to offload some of the merchandising process to the Machine Learning component of GrapheneHC.
Retailers can choose between fully automated Merchandising, where the system uses Machine Learning to select the best performing Merchandising Strategies.
Alternatively, retailers can use a mixture of automated Merchandising plus pre-defined Merchandising Strategies.