‘Views’ are lies

Online video metrics, particularly view counts, are prominently displayed across various internet platforms. Seemingly real-time views are tracked on platforms like YouTube, Instagram, TikTok, Facebook, X, and Threads, suggesting a universal measure of success. This emphasis on social media views creates an illusion that higher numbers equate to greater popularity or engagement. However, a closer examination reveals the misleading nature of these figures.

The Illusion of Views: Why Online Metrics Can Be Deceptive

Despite their perceived importance, view counts often present a skewed picture of content consumption. Numerous reports and even lawsuits have highlighted the artificial inflation of these numbers. While the worthlessness of view counts has been previously discussed, their continued prevalence necessitates revisiting this topic. The concept of a “view” as a universal metric is fundamentally flawed and often bears little resemblance to actual audience engagement.

Defining a “View”: A Platform-Dependent Metric

The definition of a “view” varies significantly across platforms, lacking a standardized meaning. Instead, it is arbitrarily determined by each platform, frequently with minimal connection to genuine user interaction or content absorption. Platforms possess the autonomy to manipulate these metrics, adjusting the criteria for a “view” to suit their agendas.

Social Media Platforms: Instant Views and Misleading Metrics

Consider the practices of social media giants: Instagram, TikTok, and YouTube Shorts. These platforms register a “view” the moment a video commences playback. This approach is demonstrably inaccurate. Simply scrolling past a video, even momentarily, is counted as a complete viewing. This is comparable to claiming you’ve watched an entire movie simply by walking past a screen showing it – a clear exaggeration of actual consumption.

Facebook’s Evolving and Opaque View Metrics

Facebook’s definition of a view is equally broad, encompassing “the number of times a reel or video was played, plus the number of times photos or text were on screen.” Given the autoplay feature prevalent across Facebook, these metrics become practically indistinguishable. Acknowledging the inadequacy of this metric, Facebook offers creators alternative, though private, metrics such as “three-second video views” and “one-minute video views” – figures undoubtedly lower than the publicly displayed view counts.

Since last fall, “view” has become Meta’s overarching metric, consolidating previous engagement measurements. For photos, text posts, and Stories, a “view” is now counted each time content appears on a screen, including repeat exposures. Formerly termed “impressions” requiring interaction, these instances are now simply categorized as views, further inflating the numbers.

X’s (Formerly Twitter) Sketchy View Count System

This misleading “view” concept extends to X. As users scroll, every post appearing in their feed, search results, or profile pages registers as a “view.” While X’s official documentation on post views remains unclear, their video policy specifies a view if a video plays for at least two seconds with half the player visible. Automatic video playback on X reinforces the pattern: loading equates to viewing.

The Self-Serving Logic Behind Inflated Metrics

The widespread adoption of such flawed metrics stems from a straightforward, self-perpetuating rationale. Platforms employing realistic view counts risk appearing less popular, potentially deterring content creators and advertisers. In the competitive online landscape, perceived momentum is crucial, sometimes necessitating inflated metrics to attract initial engagement.

Platform Control and the Absence of Meaningful Metrics

This view definition model grants platforms complete control. User agency is removed; neither active initiation nor sustained engagement is required for a “view” to register. The process lacks genuine connection between content and audience – it is simply about generating views, regardless of substance.

Netflix and the Trend Towards Lower Engagement Thresholds

Even streaming services like Netflix, initially employing stricter metrics (70% completion for a view), have succumbed to this trend. Netflix now counts a view after just two minutes of viewing, a duration they deem “long enough to indicate intentional choice.” This claim is questionable, particularly considering Netflix’s internal data revealing actual viewership patterns. This metric adjustment reportedly increases view counts by approximately 35%.

Streaming Services’ Opaque Metrics Practices

Ironically, Netflix is relatively transparent about its view calculation compared to most streaming competitors. Many services maintain secrecy, allowing them to promote content as “huge hits” without providing concrete data. YouTube, too, remains vague about standard video view calculations, despite the widely accepted 30-second threshold, the official confirmation of which is difficult to locate.

Data Transparency: Public vs. Advertiser Metrics

The intentional manipulation of public-facing view counts is evident in platform practices. While creators access limited non-public data like watch time and interactions, advertisers receive comprehensive metrics. Platforms like YouTube differentiate between impressions and views for ads and provide advertisers with detailed engagement data (e.g., percentage of video viewed). This discrepancy highlights platforms’ awareness of the limitations of public view counts, using more accurate data internally for algorithm optimization while presenting inflated figures to the public.

Beyond the Numbers Game: Reconsidering Online Metrics

After years of internet evolution, the inadequacy of prevalent online metrics is clear. They have transformed the online space into a competition focused on numerical dominance, even when those numbers are detached from reality. While a metric-free internet may be desirable, it is improbable. Therefore, critical awareness is crucial: “views” as publicly presented are often not genuine reflections of engagement. View counts are, in many cases, misleading representations of actual viewership.