AI personality is the core variable determining the quality of video call experience, and its influence can account for up to 60% of the user satisfaction weight. According to a 2024 study in the field of human-computer interaction, after analyzing a sample of 10,000 users, it was found that when the personality traits of AI characters were highly matched with the Big Five personality Model, the average call duration of users would increase by 5 minutes, reaching a median level of 18 minutes per session. For example, in the video call with ai character scenario, an AI character with high extraversion (with a value set above the 80th percentile) and agreeableness (with a value above the 75th percentile) can increase user engagement by 40%. This effect is similar to how an excellent TV host can increase the program’s viewership by 30 percentage points.
The precision of an AI’s personality is directly related to the intensity of emotional resonance. Modern generative models can simulate a continuous spectrum from humor to empathy by adjusting over 1,000 personality parameters, with an emotional response accuracy of up to 85%. Data shows that when AI demonstrates a moderate frequency of humor (1.2 jokes per minute) and precise emotional support (with an accuracy rate of 90% in identifying users’ emotional states) during conversations, users’ anxiety levels can drop by 15 basis points within a 10-minute call. Referring to psychologist Carl Rogers’ personality theory, this kind of unconditional positive attention achieved through algorithms made 70% of users feel “understood” in subsequent surveys.
The ability of personalized configuration significantly enhances user stickiness. Market analysis shows that platforms that allow users to customize AI personality traits (such as adjusting the amplitude of extroversion to between -10 and +10) have a monthly active user retention rate 25 percentage points higher than that of fixed personality systems. For instance, a mainstream application offers 16 basic personality templates. Users can adjust dimensions such as humor intensity and knowledge density through the slider, optimizing the interaction matching degree from the benchmark value of 50% to 85%. This strategy is similar to how streaming media platforms increase the click-through rate of content by 35% through recommendation algorithms, ultimately leading to an average daily usage frequency of 3.5 times per user.
From a commercial value perspective, AI personalized design directly affects the conversion rate. A/B tests show that the “encouraging” personality designed for educational applications (with a 30% frequency of supportive statements) increases the course completion rate by 20%, while the “expert” personality in e-commerce scenarios (providing parametric product data as fast as 0.3 seconds) boosts the sales conversion rate by 15%. The input-output ratio of this personalized strategy reaches 1:3, as the development cost only accounts for 10% of the total project budget, yet it can drive a 40% increase in the user lifetime value.
The future trend points to the dynamic evolution of personality. Neuroscience research shows that AI systems that can adjust personality parameters based on conversation history (updating weight coefficients weekly) have a 50% higher six-month user retention rate than static systems. Just as the interaction duration increased by 200% after ChatGPT introduced the character memory function in 2023, the next-generation video call with ai character system will achieve an exponential growth in the efficiency of establishing the relationship between AI personality and users through real-time sentiment computing.