Apps
Comprehensive insights into user social behavior to unlock monetization potential.
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Exploring the user relationship building path
Understand how effectively the product guides new users and assess user demand for different modules. Regularly monitor changes in key product metrics and evaluate the conversion pathways of user relationships within the product.
Understand the user journey within the product
Explore the conversion of user social relationships
Analyze user matching efficiency and smoothness
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Focusing on user social preferences
Categorize user groups based on their usage preferences and analyze the payment conversion rates and retention of different preference types. This helps in making targeted improvements to the product and designing effective payment options.
Track the time users spend in different product modules
Explore monetization points within the app
Analyze retention differences among users with varying usage preferences
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Optimizing and iterating the user matching module
In social apps, matching is a key feature for user conversion. By monitoring metrics like matching efficiency and post-matching activities we can gain insights into user matching patterns and effectively optimize matching strategies.
Optimize the core user matching process
Analyze user behavior after successful matches
Examine the distribution of matching duration
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Products
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  • Data visualization
  • User behavior analysis
  • User segmentation
  • Intelligent alerting
  • ROI-Master
  • Data pipeline
  • Data management
  • Channel attribution
  • Open API
  • Data security and deployment
  • Pricing
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  • DataTower.ai on Github
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