RECOMMENDATION SOLUTION
“We provide an AI-based personalized
recommendation service that utilizes Big Data.”
About the Service
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01Analyze behavior history of individual customers visiting the website
A female client in her 20~30s who visited the site because of her interest in Product ‘A’
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02Recommend products with higher purchase rate by looking at past browse history and recent items of interest
Immediate, real-time recommendation of products of interest through Big Data-based AI analysis
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03Make customers purchase product by continuously luring the customers to click products and prevent them from leaving the site
Continuous personalized recommendation of products of similar taste but different styles → customer discovers the product he or she likes and ends up purchasing it
Elicit increase in traffic through product-based recommendation and recommend products with high purchase rate
- Products viewed together（ViewTogether)
- Products bought together（BuyTogether)
- Products related to search term（SearchTerm to Item)
Recommend the most suitable personalized product to the user by considering each user’s traits and recent needs
- Personalized recommendation (based on past history)
- Real-time personalized recommendation (based on recent interests)
- Similar user recommendation(User to User)
Recommendation Solution Outcomes
Competitors have already selected Recobell and are witnessing high performance results through our service.
Log data status
Collecting and analyzing log data as of December 08. 2019
- Customers
- 479
- Cumulative log data
- 82,436,393,600
List of Clients
Multiple clients in various categories such as open markets, online malls, shopping malls, beauty, furniture, finance, and lifestyle
COPYRIGHT(C) 2018 RECOBELL. ALL RIGHTS RESERVED.
