Overview
This document provides instructions on how to customize the parameters that influence the Related Items recommendations.
Note: These settings are global and apply to all Related Items recommendations across your store.
How to optimize Related Items recommendations:
Navigate to Engine Parameters:
Log in to your LimeSpot account.
Go to the Optimization Hub section.
Click on Engine Parameters.
Customize Related Items:
Use the following parameters to adjust and fine-tune how your Related Items are generated.
Related Items Parameters:
Move the sliders to the left or right to increase or decrease the weight of each parameter. A higher weight means that the parameter has a greater impact on related item recommendations.
Similarity: Adjust the weight given to product similarity in determining related items. Product Similarity is based on parameters such as Product Collection, Item Type, and Vendor and you can customize the weight of each parameter using the Similarity Parameters below.
Price Range: Control the influence of price similarity on related item recommendations.
Item Prevalence (Advanced): Set the weight of item-specific prevalence in related item rankings.
Collection Prevalence (Advanced): Determine how collection-specific prevalence affects related item rankings.
How to Optimize Product Similarity Parameters:
Move the sliders to the left or right to increase or decrease the weight of each parameter. A higher weight means that the parameter has a greater impact on item similarities.
Product Collection: Adjust the weight of common collection memberships in calculating product similarity.
Item Type: Control the influence of common item types on similarity.
Vendor: Set the weight of common vendors in determining product similarity.
Additional Notes:
The default values for these sliders are optimized for most use cases, but you can adjust them based on your specific needs and preferences.
Experiment with different settings to see how they affect your related items' recommendations.
Keep in mind that changes to these settings may take some time to reflect on your recommendations.