DeepSeek's fast rise and faster fall: User engagement drops sharply after initial surge

DeepSeek made headlines when it debuted, heralded as a cost-effective and powerful alternative to OpenAI's ChatGPT. Backed by strong marketing and glowing early reviews, the platform quickly gained traction, with experts touting it as a significant leap forward in AI-driven conversational tools.

For the first few weeks, usage data painted a positive picture, showcasing a strong user adoption and rising interest. However, the momentum appears to have been short-lived.

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According to recent insights from Bobble AI's Market Intelligence Division, DeepSeek began to see a sharp decline in engagement after its initial launch window. While the app enjoyed an early surge, it struggled to sustain user interest beyond the third week. Sporadic spikes in activity were observed but proved insufficient to maintain the platform’s early promise or compete with the steady performance of ChatGPT.

ChatGPT continues to lead

Comparative data reveals a contrast between the two platforms. ChatGPT not only attracted more sessions per user but also boasted significantly longer average session durations. Even at its peak, DeepSeek's engagement was inconsistent, suggesting that while users were intrigued, the platform failed to retain them effectively.

"The report shows that duality between marketing and performance," said Ankit Prasad, Founder and CEO of Bobble AI. "The data reflects how marketing can create initial excitement around a product. However, the long-term success of a product depends on several other important factors such as consistent performance. This is an important lesson for brands aiming for sustained traction."

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A tough road ahead for DeepSeek

Despite its low-cost development and early enthusiasm, DeepSeek now faces the daunting challenge of improving its core offering to win back users. Metrics including open rates, session time, and repeat usage have seen notable declines, underscoring the need for a stronger retention strategy and product refinement.