AI
As products in an emerging industry, identifying core user groups and building product barriers are key points.
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Optimizing the product to enhance core competitiveness
Even for emerging AI apps, it’s difficult to avoid imitators when a product becomes popular. To remain competitive among similar offerings, strengthening product capabilities through in-depth data analysis is essential.
Guide users to engage with core functional modules to increase perceived product value
Analyze traffic distribution across different modules to unlock feature potential
Optimize key conversion processes to reduce passive user churn
Rapid iteration and testing to find the optimal ad placements strategy
Due to the novelty of AI app categories, there is currently a lack of mature advertising models in the market. Therefore, exploring and developing more competitive ad placements strategies can effectively create competitive barriers.
Test across multiple channels and adjust quickly to find the best acquisition platform
Achieve ad material direct ROI, with hour-level (T+0) selection of high-quality creatives
Customize event-based feedback to create tailored advertising strategies
User operations to increase lifetime value
AI apps are inherently technical, so the key point to profitability lies in ensuring that their AI algorithms and large model capabilities consistently serve the target user base and generate ongoing value.
Deeply analyze user characteristics to discover new operational strategies
Segment users across multiple dimensions to refine operations with data support
Monitor operations in real time for instant feedback, enabling rapid iteration and optimization
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