长视频剧综赞助营销 为何搞不定AI产品？

This article examines why most AI products currently avoid sponsorship marketing on long-form dramas and variety shows, and summarizes the industry's current status and core challenges as follows:

1. There are two key reasons AI brands shy away from drama marketing. First, AI products have moved beyond the early user acquisition phase and now prioritize high-intent, convertible traffic: low-quality users from generic audience pools consume large amounts of computing power and raise operating costs. Long-form dramas focus on mass-market, lower-tier audiences, and cannot deliver the precise targeting AI products require. Second, existing drama placement tactics are outdated and intrusive, relying heavily on forced integrations that fail to build the emotional, human-centric perception users expect of AI products.

2. AI brands are more receptive to variety show placement, but common traditional placement strategies still frequently underperform. For example, when Alibaba's Tongyi Qianwen sponsored *Viva La Romance 2026*, the brand was supposed to appear when athlete Sun Yang got lost and needed navigation and translation, but failed to show up at all, severely undermining the campaign's impact. To win AI brand sponsorship, long-form platforms must integrate AI products naturally into realistic scenarios and imbue them with human-like warmth.

This article analyzes the current state and core challenges of AI brand marketing via long-form dramas and variety shows, offering actionable insights for AI brands' marketing strategies:

1. The core logic of AI brand marketing has shifted. Unlike the "scale for growth" playbook of the mobile internet era, invalid users from generic traffic consume significant computing power and push up operating costs. AI brands should therefore prioritize channels that reach their precise target audience. For example, AI office product WorkBuddy prioritizes advertising in first- and second-tier city office buildings and internet communities, and avoids generic long-form video marketing.

2. For brands that do choose long-form video placement, it is critical to avoid the pitfalls of traditional integration tactics. Brands should require platforms to embed their products in realistic scenarios that align with product features, and arrange for natural exposure exactly when users would have a need for the product. Brands should also select niche variety shows that match their positioning: for example, a children's companion AI robot will see far better results and stronger brand building from sponsoring parenting-focused shows than mystery variety programs.

This article notes that the AI sector is a high-growth market with strong capital interest and abundant marketing budgets, creating untapped growth opportunities for long-form video marketing practitioners:

1. Opportunity outlook: The AI boom has left multiple segments including AI assistants, AI hardware, embodied intelligence, and AI education with large marketing budgets to deploy. The long-form video industry has not yet developed effective strategies to win over AI brands, leaving this an untapped incremental market. Securing AI brand clients can substantially boost long-form players' commercial revenue.

2. Required optimizations: On the drama side, platforms should not only focus on mass-market hits targeting lower-tier audiences. They need to maintain the capacity to produce high-quality niche content, to deliver precise audience targeting for AI brands. They also need to innovate integration tactics, moving past outdated forced placements to adopt AI-aligned marketing approaches.

3. Core key to success: To win over AI brands, long-form players must address AI brands' core demand: building human-centric warmth for their products by integrating them naturally into authentic scenarios in programming.

This article analyzes shifts in marketing and market demand across the AI industry, offering business opportunities and development insights for AI-related manufacturing factories:

1. Business opportunities: The ongoing AI boom has left multiple categories of AI products—including AI hardware, embodied intelligent robots, AI glasses, and agricultural robots—with substantial marketing budgets for large-scale promotion. Factories can partner with AI brands to expand OEM and collaborative manufacturing business, capture AI industry growth dividends, and scale their operations.

2. Product design insights: Market demand for AI products has shifted from a focus on technical specifications to practicality and human-centric warmth. When designing and manufacturing products, factories should develop features aligned with real-world daily user needs, strengthen products' ability to solve practical pain points, and better match market demand.

3. Digital marketing insights: When promoting their own brands, factories should prioritize precise traffic channels, avoid blindly investing in generic traffic, cut unnecessary costs, and improve conversion rates.

This article analyzes industry trends and client pain points in AI marketing, outlining a clear path forward for marketing service providers that serve AI brands and long-form platforms:

1. Industry trend: AI is one of the fastest growing incremental client segments in the marketing services industry today. It attracts strong capital attention, has abundant marketing budgets across market players, and offers broad market space and huge growth potential, making it a key priority for providers to expand into.

2. Core client pain points: AI brands' marketing needs have evolved from early-stage scale building and brand awareness to acquiring precise, convertible traffic. They also need marketing to imbue AI products with human warmth and upend the stereotype that AI is cold and impersonal. Existing outdated long-form video marketing tactics cannot meet these two core demands.

3. Solution roadmap: When developing long-form marketing strategies for AI brands, providers should, on one hand, connect brands with niche content resources on long-form platforms that match AI brands' target audiences to deliver precise traffic. On the other hand, they need to innovate placement tactics and help brands integrate naturally into authentic scenarios to meet brands' core demands.

This article outlines existing problems and improvement directions for long-form platforms looking to attract AI brand marketing investment, helping platforms capture AI marketing growth dividends and boost their commercial capabilities:

1. Core demands of AI brands for long-form marketing are twofold: first, to access precise target audience traffic that delivers high conversion; second, to build human-centric warmth for AI products through content placement, and change consumers' perception that AI is cold and impersonal.

2. Core problems facing platforms today: On the drama side, most content focuses on mass-market hits targeting lower-tier audiences, which cannot deliver the precise traffic AI brands need, and placement tactics are outdated and forced. While AI brands have already begun advertising on the variety side, platforms still rely on traditional tactics such as logo display and host read-outs, which often lead to misaligned scenarios and campaign results that fall short of brand expectations, discouraging AI brands from increasing their investment.

3. Directions for improvement: Platforms need to adjust their content strategy to retain high-quality niche content that meets AI brands' demand for precise traffic. They also need to innovate marketing tactics to push for natural, scenario-based product placement. These changes will attract more AI brand sponsorship and open new avenues for growth.

This article presents new developments in long-form drama and variety show marketing, analyzes the new challenges and opportunities AI industry growth brings to long-form video commercialization, and offers high reference value for relevant research:

1. New industry development: The marketing logic of the AI industry has fundamentally changed. Unlike the mobile internet-era growth model where larger audiences translated directly to higher profits, low-value users from generic traffic create unnecessary computing consumption and raise operating costs for AI companies. As a result, AI brands now prioritize precise, convertible traffic, a new feature that distinguishes AI industry marketing from traditional internet industry marketing.

2. New industry problems: Long-form video's existing marketing system was built around the needs of traditional consumer goods and traditional internet brands. Both its traffic structure and placement tactics cannot adapt to AI brands' core demands, creating a clear supply-demand mismatch that requires industry-wide adjustment and optimization.

3. Future research direction: The long-form video industry needs to restructure its marketing business model around the needs of AI brands to capture growth dividends from the AI boom and drive commercial growth. This is an emerging research topic that merits in-depth exploration in the media and marketing field.