NPTB AI Engine
DeepSales
DeepSales is a business marketing service that uses machine learning AI engine to recommend NPTB (Next Product To Buy) and content most wanted by customers.
It collects and analyzes various usage patterns of customers to extract a behavioral data model.
● Usage information
DeepSales collects and analyzes structured data such as customers’ purchased items, checked content, time, location and routes.
● Property information
DeepSales classifies/analyzes the category of products, content, and promotions to understand customer taste.
● Interest information
DeepSales classifies and tracks the customer’s interests based on social standards such as age, gender, region, and occupation.
Through customer behavior data and AI engine, DeepSales predicts customers’ future behaviors.
Target offering engine
New product planning and themed products (season, promotion, etc.)
Product recommendation (Up/Cross-selling)
Partnership product engine
Partnership membership-linked product recommendation
Development of partnership discount, partnership pricing schemes
Providing partnership benefits when changing cellphone devices
Personalization engine
Product/content recommendation through web/app
Message/location-based offering
Application of digital contact center (ex. Chatbot)
We provide the optimal NPTB through recommended products, customized information and personalization offering.
By providing the most favored product or content based on user proclivity and behavioral patterns, we can maximize your product purchase conversion rate and usage rate of your service/content.
We provide various services to domestic and foreign travelers as well as online service users.
We are working with Visit Korea and its flagship service ODII, an audio-based tour guide service, to analyze user proclivity and usage patterns to provide a recommendation and personalization service.
GET IN TOUCH
Recommendation of product and content desired by customers is an essential business strategy in the digital era.
DeepSales Enquiry
9F, 507, Gangnam-daero, Seocho-gu, Seoul, Republic of Korea