Team Analysis|Cluster Analysis|Resource Allocation|Economic Analysis
Five easy-to-use apps combine knowledge of personality psychology, portfolio theory, macroeconomics, customer relationship management, and machine learning to make it easy to share ideas and increase productivity.Get started
Career3A can quickly test your “Behavioral style”, “Work motivation” and “Core skills”. Career3A lists the most suitable occupations based on your personality traits to help you think about your career development direction. You can invite friends and colleagues to form a team, and use the “Team Analysis” tool to query the team’s test results. By learning more about yourself and the people around you, you can better build relationships with friends and colleagues with different personalities.
You can use the ranking results to understand your personality traits and preferences.
You can use the ranking results to understand what drives your career.
You can use the ranking results to understand which core skills you value most in the workplace.
Cluster analysis tools.
For most people, it is difficult to obtain the information they need directly from raw data. Machine learning can transform disordered data into useful information. Clustering is an unsupervised machine learning technique that groups similar objects into the same cluster. Cluster2A combines the two most popular clustering algorithms, K-means and DBSCAN, to help you discover interesting patterns in the data.
For example, Cluster2A can perform cluster analysis based on customer consumption behavior and provide results for customer segmentation. Customer segmentation is the use of specific characteristics to identify and organize customers. These characteristics can be demographic, behavioral/psychological characteristics and geographic location. Customer segmentation can identify customers and provide products and services tailored to their needs. This personalization will provide you with a competitive advantage, increase customer conversion rates and brand loyalty.