WE CAN GUESS MERHANTS' FAVOURITE ITEMS
FROM THEIR FEEDBACK
FROM THEIR FEEDBACK
What is Recommendation Engine?
Recommendation engine is an information filtering system, the system learns from the past purchase and browsed records to predict user's preference, hence choose and match up different products to increase the cross sales.
Primary Product
Category:
Selected:
Bundle Products (Pick
6
items you love from the list.)
We can guess users' favourite items based on their choices
NEXT
How Recommendation Engine works?
Global Data
User Feedback
Transaction History
User feedback (User based)
User feedback reflects their behaviour and preference, and system will recommend similar products to users it’s just like Facebook recommended "common" friends to you, including:
- Bundle sales of merchants
- Buyer's browsing history
Transaction History (Item based)
Recommended engine is based on the correlation between items and users, the transaction history of the product will be clearly recorded by system, including:
- Multiple purchase records for a single item
- Purchase records for several different items
Global Data
Viewider gathered all data from Google News and Wikipedia in the past 3 years to strengthen own database, make predictions more accurate.
Real Time Learning
Users’ browsing history will be real-time tracked and recorded.
Regular updates
System will weekly update the users’ preference as to make sure data are up to date.