AI Engine
(Recommendation scenario)

For homepage and category page :

Key point: Increase click rate, purchase rate
Popular Item: Based on the cumulative number of items having multiple indicator behaviors (such as click, search, like, share ,etc.) to comprehensively recommend every month, not ranking by sales.
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Trending Items: Based on the growth rate of multiple indicator(such as click, search, like, share ,etc.) be cumulated every week(or two weeks) to recommend on trend.
Hot item: Based on the growth rate of multiple indicator be cumulated in the few days to recommend immediately.
Recommend just for you: Based on the relevance of items(or content) and preferences to recommend.

For product page

Key point: increase purchase rate, conversion rate, Average transaction value

Contextually Personalize with Similar Items

Based on automatically recommend similar items which according to individual preference when the visitor is viewing.
Based on similar items which be promoted or on sale by the customer recently viewed product or browsing essays .
Based on browsing history automatically recommend related items which the visitor is viewing.

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Content based

Based on the relevance of items(or content) to be recommend, and also according to consistence about category.

Similar Items Based on Attribute

According to products which the visitor is viewing, automatically recommend the highest related items.

For check out page

Key point: increase purchase rate, conversion rate, Average transaction value

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Frequently bought together

Based on combinations of products frequently bought with what the customer is viewing , or has already put in the shopping cart.

Low price complementary

Based on similar products a price that matches the consumer's average order value to recommend plus items.

Viewed this buy that

Customer shopping behavior mostly checked out the unrelated items after browsing many products. So, based on automatically recommend items from different category but mostly want to buy which according to consumer preference and relativity when the visitor is viewing.
Last modified 14d ago