Why you should opt
Konan Smart Match
Are you having trouble recommending products and content that match your User preferences?
Konan Smart Match, the AI-based personalized recommendation solution,
will establish an optimal recommendation system that offers personalized choices.
Konan Smart Match is an “AI-based personalized recommendation solution”
that analyzes behavior pattern data of users to provide personalized recommendation results.
BENEFITS
Benefit 01.
Personalized Recommendation Service
Establish a personalized recommendation service strategy through
Konan Smart Match.
User behavioral patterns allow you to predict actual traits of
users and their choices.
Based on a customer’s purchase history and profile analysis,
you can boost sales by inducing additional purchases through
recommendations on products that users will like.
Benefit 02.
Establishment of Recommendation
Service Tailored by Business Sector
Konan Smart Match is applied as a recommendation service across
various industries such as online shopping, job searching/recruiting,
content streaming (OTT, music, education), real estate, bookstores, and news,
demonstrating significant business results.
You can provide customized recommendation services by utilizing users’ information that matches
the sector of service.
Benefit 03.
Acquisition of Active Users
The solution constantly recommends content and products
that match the user’s tastes to induce them to make additional purchases.
You can regularly send recommended product information through
emails, app notifications, etc., to induce repeat user visits.
Benefit 04.
Recommended Model Simulation & Statistics
You can configure recommendation models through the web-based
management interface to run simulations and receive statistics
for the visualized results.
FEATURE
Behavior Data Collection
Provides the capability to collect user behavior data and item information from online services or legacy systems.
User Traits Analysis
Able to create a more sophisticated personalized model by analyzing users’ traits, including age, gender, and residence along with behavioral patterns.
Behavior Targeting & Data Analysis
Analyzing user behavior patterns to predict actual areas of interest. Based on this prediction, it establishes a recommendation system by forecasting products or content highly likely to be bought by users.
Cooperative Filtering
Equipped with a feature that calculates similarity between users or items based on behavior data analysis
TECHNOLOGY
Concept Map - Konan Smart Match
USE CASES
CASE 01. Personalized HR Recruitment System Based on Big Data (Saramin)
Implementation Effect
- Provides personalized recommendation services based on AI using the online service user’s behavioral pattern and profiling information.
- As a recruitment portal, Saramin has built a personalized recommendation system through 'Konan Smart Match' that accurately analyzes jobseeker's history data and swiftly matches them with companies
- Saramin became a successful use case as the recommendation service between job seekers and companies led to a dramatic increase in the number of applicants.
Major Features
- Pre-examination of quality issues through recommendation simulator
- Provides web-based UI that allows the hybrid combination and configuration of recommendation algorithms, including collaborative filtering algorithms, AR, and SEG.