Context

“In the contemporary landscape, content generation predominantly owes its proliferation to revenue models anchored in advertising strategies”

Marketing, a colossal global industry, is instrumental for major technology firms such as Google, Meta, and Twitter, which derive their earnings by monetizing audiences through an intermediary role between advertisers and the target demographic.

Occasionally, this intermediation involves influencers or media outlets capable of garnering massive audience attention, subsequently impacted by advertisements from businesses investing heavily to scale their operations.

Given that individual attention is a finite resource, securing this attention to promote products or brands is critical for business success, a phenomenon known as the Attention Economy.

"This dynamic necessitates content to be optimized to maximize attention generation capability."

This has spurred the development of strategies solely aimed at maximizing content viewership and appeal to potential readers. Tactics like Clickbaiting (headline exaggeration, emotional appeals, controversial topics) or the creation of low-quality, rapidly produced content tailored to search demand (SEO) have become widespread.

Companies have devised proprietary content strategies that, in some instances, have proven more efficient in accessing these audiences by reducing intermediation, notably in content creation. This has led to an intensely competitive content landscape, where the ultimate goal is generating advertising-derived revenue. In this context, content that achieves maximum dissemination has fulfilled its purpose, as subsequent campaigns will be personalized for the consuming audience.

"Specialized and high-quality content faces challenges competing in this environment. The most profitable content is that which is most viral and least costly to produce."

The drive to reach massive audiences explains the trend of offering content for free to eliminate any access friction.

However, recent years have seen a resurgence in paywalls as the only viable means to sustainably produce higher-cost content, albeit typically through hybrid models.

Disintermediation of Advertising

Exploring the possibility of bypassing intermediaries to access audiences directly poses an intriguing question: Could advertisers directly engage massive audiences without intermediaries? Is it feasible to tap into the scarce resource of Attention without the current extensive marketing infrastructure?

Achieving this would negate the need for content aimed at audience generation, as direct access would be more efficient. Consequently, content creation would pivot to different objectives.

"One approach could involve directly compensating users for their attention."

In a social network where all social data is public, audience information is accessible, allowing potential connection with all users, akin to possessing every individual's email worldwide.

Moreover, access to information on group involvements and content activities would enable even targeted segmentation insights, typically obscured in traditional social networks.

However, this could lead to a surge in spam, somewhat mitigated by the inherent cost of messaging in networks with structural limitations. Social networks would need to implement spam filters, effectively concealing messages.

The possibility to filter advertising messages based on criteria such as payment amount or interest (e.g., ads deemed interesting by similar users) could emerge.

There might even be a guaranteed minimum monthly income for consuming social media advertising, requiring more engagement than merely watching a video. This could represent a basic income for many individuals.

The subsequent challenge would be to ascertain if this direct user engagement could become mercenary without yielding tangible results.

"The primary challenge is determining the efficacy of compensating users for their attention."

Advertising effectiveness remains a significant industry hurdle. Typically, ads are avoided as intrusive barriers to content, yet forced exposure results in brand recognition.

The main challenge would be convincing audiences that investing time could be beneficial. For income-sensitive populations, this could be a sufficient incentive. For middle-class users, the incentive might be less compelling, potentially deterring their engagement.

However, advertising could offer higher rewards if contextualized to specific life moments. Access to user transactions could identify opportunities for increased compensation, such as targeting a user engaged in equestrian groups with horse-related product ads.

Companies could allocate specific budgets if they could identify all their target demographics. Incentives could extend beyond financial rewards, offering tokens exchangeable for services related to their activities.

An advertising protocol could organize this model, allowing users to customize how they receive advertising revenue. Brand loyalty programs could evolve beyond offering discounts to directly compensating users of competing brands.

Implementing controls to minimize mercenary consumption of advertising content is essential, although such strategies remain effective in current practice. For example, conference stands offering gifts to attract attendees, despite some visitors only seeking freebies, succeed by providing businesses an opportunity to present their products.

"The goal is to digitize effective physical incentive strategies."

This model would translate the mercenary approach of advertising to the digital realm, potentially replacing physical tokens with NFTs.

The success of these incentives at conferences leverages the fact that clients are already present. A similar approach in social networks, where users daily engage, could alert them to economic incentives.

Revenue from Attention

A intermediated billion-dollar industry could shift towards providing revenue to the population, potentially disincentivizing content creation solely for audience access.

Content creation would thus return to quality-driven models