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Promote products or content with attribute values matching previously viewed productsin the same Price Quadrant as previously viewed products.
Each product is connected to a price percentile according to its group (e.g.: category), lower percentiles (e.g.: <20%) are labeled Low-End while top percentiles (e.g.. >80%) are labeled High-End.
WPOS | Use Cases | Mode | Requirements |
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ALL | You will need to select the name of the product attribute you want to promote |
Info |
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* the Use Cases configuration is provided as SCORER with a default weight of 500. You will need to adjust the weight to have the desired strength in the results or change the Mode to RANKER or FILTER if you want the returned suggestions to always match this Best Practice. |
Variables
field: the name of the product attribute
Cases to consider
You might want to configure this Best Practice several times, for example for the following cases
Products matching the brands of products the visitor recently viewed
Products matching the categories of products the visitor recently viewed
Products matching the gender of products the visitor recently viewed
Products matching the other attributes of products the visitor recently viewed which you use as search and navigation facets
Products matching the price range of products the visitor recently viewed
Products matching the price level of products the visitor recently viewed (price level are low-medium-high and will depend on the category of the products so you can separate the “expensive” products according to their categories from the “cheap” ones)
Product matching the Search Discovery Tags of products the visitor recently viewednone
How to configure it?
You can import the JSON below directly in the Admin (use the Import button on the top right), as in this screen-shot, you will need to select a field (product attribute)
Tip |
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You can use the search icon on the right of the field parameter to get help to select the right field and value. |
Tip |
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There are no parameters to change, as the product attribute is already selected (bq_high_low_end) |
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