Product Recommendation
Like applying more advanced recommendation algorithms in worldwide video streaming services such as Netflix and YouTube, customers want a service that shows recommendations based on their interests rather than trying to find a product on their own. Targeting the products that a specific customer wants is the key to marketing.
If you use deep learning to quickly respond to changes in customer behavior using variables such as product classification, price, and special price, you will have a great impact on sales growth. Artificial intelligence quickly learns consumer data (customer profile information), reviews, and demographic purchasing behavior patterns to recommend products tailored to user profiles and habits. The product recommendation system is a great marketing tool that is useful for increasing your business' profits and sales.
Main function
1. Product Recommendation
- Product recommendation service tailored to specific customers
- Increased revenue through improved customer satisfaction
- Active exchange with customers through recommendation system and gradual AI supplementation
2. Data Security System
- Thorough data security through security processing
3. Providing various services
- Interlocking between apps, web and programs is possible by providing various programming languages
API Summary
| Data | Data type | Content | Use mode |
|---|---|---|---|
| Input data | CSV | Customer data : review scores, customer profile information, customer historical product purchase information, etc. | API |
| Output data | CSV | Recommended product | API |
Application procedure
| Payment | Subscription method | Attached file upon application |
|---|---|---|
| Prepaid charge | Online | Customer data required for model creation |
| Application procedure |
|---|
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Pricing
| Category | Price |
|---|---|
| API Setting | $1,800 ~ |
| API Predicting | $0.002/row |