Overview
Promote products often purchase behavior patterns found by Boxalino’s Deep Learning: Neural Collaborative Filtering based on products bought by the same customers as than the last products already bought by the customer has purchased.
Read more about Neural Collaborative Filtering.
WPOS | Use Cases | Mode | Requirements |
|---|---|---|---|
ALL | You need to have enough statistics of customers buying several products over time.confirm with Boxalino that this Collaborative Filtering has been computed for your account |
Variables
type: collaborative-filtering-bought_-same_-customer
Cases to consider
Other types could be considered:
collaborative-filtering-bought_-after: same idea, also with products bought by the same customer, but which happened after (so if customers by product A, find products often bought after buying product A by the same customer)
bought_first_second_collaborative-filtering-first-second-purchase: same idea, but solely for purchases done as second purchase (after the first purchase)
collaborative-filtering-bought_-together: same idea, but with products bought in the same basket
basketed_in_same_collaborative-filtering-basket-same-session: same idea, but with products often added to the basket in the same sessionviewed
_in_same_collaborative-filtering-viewed-same-session: same idea, but with products often viewed in the same session
end_up_buying: same idea, but with products often bought in the same session after viewing this product
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.
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