TikTok’s “Guess” Trend Is Actually Genius Psychological Manipulation—And We’re All Falling for It

Introduction

If you’ve spent even a casual amount of time scrolling TikTok in the last few weeks, you’ve probably run into a video that ends not with a punchline but with a single, maddening word: “Guess.” The trend—which crystallized around Charli XCX’s single “Guess” (featuring Billie Eilish) and surged in visibility around September 2025—looks innocuous on the surface: creators tease something juicy, cut the clip to the song, and then, when viewers swarm to ask “What happened?” or “Who is it?” they reply with “Guess.” It feels playful, a low-effort way to stay mysterious. But there’s a darker, highly systematic logic underneath. What seems like entertainment is actually a compact, repeatable strategy that weaponizes basic human psychology to harvest engagement—and, by extension, ad dollars.

This isn’t just about a catchy hook or a celebrity track. TikTok, with roughly 1.6 billion active users as of early 2025 and an average session length of about 58 minutes per day, is the world’s largest behavioral experiment in attention capture. The platform’s ad reach—1.59 billion people, or roughly 19.4% of the world’s population—combined with ByteDance’s $23 billion revenue in 2024 (a reported 42.8% year-over-year increase) creates enormous financial incentive to amplify tactics that boost comments, shares, and watch time. The “Guess” trend is a micro-optimized engine for exactly those metrics.

This exposé pulls back the curtain on how the trend works, why it spreads so quickly, who benefits, and what it means for digital behavior. I’ll unpack the psychological mechanics—information gaps, intermittent reinforcement, social proof—and show how a tiny creative maneuver turns everyday curiosity into a monetizable commodity. I’ll also cover practical use cases (for better and worse), the risks and ethical questions this trend raises, and what users, regulators, and platforms might do next to tilt the system away from manipulation and back toward genuine value.

If you think “it’s just fun,” keep reading. If you already feel a bit exploited, you’re not imagining it.

Understanding the “Guess” Trend

The “Guess” trend is simple enough to explain in three steps: introduce ambiguity, cue a catchy audio clip, and respond to engagement with the single-word reply “Guess.” Within that economy of motion, multiple powerful psychological levers are pulled simultaneously.

First, creators craft a curiosity gap. They begin with an incomplete story—“I made a huge mistake…” or “You’ll never believe who walked in…”—and deliberately withhold the resolution. Psychologists call this the information gap: when people perceive a gap between what they know and what they want to know, they experience an aversive feeling that motivates them to close that gap. TikTok videos are the perfect vehicle for this; the short-form format encourages cliffhangers and unresolved stories.

Second, the music cue—Charli XCX’s “Guess,” featuring Billie Eilish—functions as both a cultural shorthand and an attention amplifier. Using a recognizable audio clip creates a predictable framing device; viewers quickly learn that the clip signals a “tease + reveal” dynamic. Over time, the song itself becomes a meme that primes the brain to anticipate drama, increasing comment velocity when another video uses it.

Third, creators weaponize the comments. When viewers demand a reveal, the creator replies with “Guess” instead of answering. That reply turns a single question into many: other viewers brainstorm possibilities, friends tag friends, and the comment section fills with speculation. Each new comment is additional evidence of engagement, which the algorithm interprets as social validation. The more comments, the more likely TikTok’s recommendation engine will surface the video to new audiences, completing the feedback loop.

This is not random virality. It’s optimized virality. TikTok’s system rewards content that generates interactive metrics—comments, likes, rewatches—far more heavily than passive views. With roughly 58 minutes a day on the app, the average user offers a huge window for creators to trigger these interactive loops. The platform’s 1.6 billion active users amplify every meme and hack at global scale; a tactic that reliably increases comments by even a small amount can become a mass manipulation tool overnight.

The trend also leverages basic social dynamics. Social proof—the psychological phenomenon where people copy the actions of others to assume those actions reflect the correct behavior—makes the comment section a self-perpetuating engine. When users see 2,000 guesses, they feel not only compelled but expected to add one more. And if creators occasionally reward a guesser with a reveal (intermittent reinforcement), the whole system becomes addictive: occasionally you get the payoff, and that unpredictability makes you keep participating.

Finally, the commercial incentives are enormous. ByteDance reported $23 billion in revenue in 2024, and the company’s growth depends on maximizing time spent and active engagement. Trends like “Guess” are not explicitly sanctioned corporate strategies, but they align perfectly with platform incentives. The line between spontaneous user culture and behaviorally optimized growth tactics is blurry—and intentionally so.

Key Components and Analysis

Let’s deconstruct the “Guess” trend into the levers it pulls and why each is so effective.

Information Gap and Curiosity

- Mechanic: Videos introduce an unresolved question or story fragment. - Why it works: People are wired to resolve uncertainty. The discomfort of the information gap leads to a compulsion to seek closure—commenting is an easy way to do that. - Impact: High comment rates per video; users produce content that intentionally induces this discomfort.

Audio Signal and Meme Conditioning

- Mechanic: Using Charli XCX’s “Guess” as the audio cue. - Why it works: Repetition conditions users to associate that audio clip with teasing/withholding. Once the audio becomes meme-adjacent, it primes viewers to respond with curiosity. - Impact: Faster recognition and higher engagement velocity; audio becomes shorthand for a manipulative format.

Social Proof and Comment Herding

- Mechanic: Comment sections fill with guesses, tags, and speculation. - Why it works: Large numbers of comments signal correctness or relevance to others; people mimic behavior. - Impact: Rapidly snowballing engagement that signals TikTok’s algorithm to boost distribution.

Intermittent Reinforcement

- Mechanic: Occasionally revealing the answer or engaging a commenter. - Why it works: Random rewards (a reveal or a shoutout) make participation addictive—users keep commenting in hopes of being chosen. - Impact: Repeat engagement across multiple videos from the same creator; sustained attention.

Algorithmic Feedback Loop

- Mechanic: TikTok’s recommender system amplifies high-comment, high-watch-rate content. - Why it works: The algorithm optimizes for dopamine-producing behaviors (surprises, curiosity, social interaction) to increase session length and ad impressions. - Impact: Small engagement hacks become large-scale memes; creators rapidly scale followers and views.

Celebrity Acceleration

- Mechanic: The trend uses a widely recognized song and is amplified by big creators. - Why it works: Celebrity association offers instant credibility and replicability. Charli XCX’s involvement turned a tactic into a mainstream meme. - Impact: Faster cross-pollination across creator tiers; trend moves from micro to macro behavior in days.

Contextualizing these components with platform-scale data makes the manipulation clear. With 1.59 billion people reachable by ads (19.4% of the global population) and 875 million app downloads in 2024, TikTok’s ecosystem is uniquely suited to broadcast and monetize micro-behaviors. The platform has effectively cultivated an environment where curiosity can be engineered and sold: increase comments, increase session time, increase ad exposure, increase revenue. That ByteDance pulled in $23 billion in 2024 is not incidental; it’s the payoff for a product that learns how to push human buttons at scale.

The “Guess” trend is a textbook example of behavioral design creating a low-friction, high-reward manipulation loop. Where early social platforms relied more on network effects, TikTok optimizes at the individual attentional level. The consequence: a higher velocity of influence, for better and for worse.

Practical Applications

For marketers, creators, and researchers of digital behavior, the “Guess” trend is a case study in both opportunity and responsibility. Here are concrete ways different stakeholders are using—or could use—the mechanics, followed by the ethical line each must reckon with.

For creators: - Follower growth tactic: Use the “Guess” format to drive comments, which improves the video’s algorithmic standing. Many micro-influencers report higher follow rates after deploying it. - Community-building: Turn guesses into user-generated content—feature funny or creative guesses in duet chains or follow-up videos, creating participatory narratives. - Content funneling: Use a “Guess” video as the top-of-funnel hook, then drive interested viewers to deeper, more meaningful content (longer videos, livestreams, product pages).

For brands and marketers: - Awareness campaigns: Brands can use a sanitized version of the trend—teasing a product reveal or limited-time offer—to harness curiosity without misleading consumers. - Social listening: Use surges in “Guess” comments to identify consumer sentiments and speculate on what piques curiosity about your category. - Creative A/B testing: Try both playful “Guess” teases and straightforward reveals to measure differences in conversion rate vs. engagement metrics.

For platform/product teams: - UX experimentation: Design affordances that make honest reveals and follow-through easier—e.g., pinned answers, structured Q&A responses, or time-bound follow-ups. - Moderation signals: Use spikes in “Guess” patterns to identify potential misinformation vectors or harassment concentrations and route them to moderation.

For researchers: - Behavioral experiments: The “Guess” trend offers a real-world testing ground for studying information-gap effects, intermittent reward schedules, and the transition from curiosity to compulsive engagement. - Longitudinal studies: Track cohorts exposed to “Guess”-style manipulation to see whether their attention patterns or trust in creators change over time.

Action matters. There’s a difference between employing curiosity ethically—where the reveal delivers real value—and weaponizing it to boost vanity metrics with no substantive payoff. Creators who answer responsibly (e.g., revealing promptly, providing follow-up value) can use the trend to build durable relationships with audiences. Brands that lean into transparency can harness the tactic without exploiting users. But many actors will choose the path of least resistance—maximizing short-term engagement where the payoff is purely algorithmic.

Challenges and Solutions

The “Guess” trend surfaces deep challenges tied to attention economies, content quality, and regulatory oversight. Here’s a candid look at those obstacles and practical solutions stakeholders can implement.

Challenge 1: Erosion of trust and content value - Problem: Repeated use of manufactured curiosity fosters cynicism. If creators never deliver reveal value, audiences learn to expect manipulation. - Solution: Norms and platform nudges. TikTok could introduce a “teaser/reveal” structure that requires creators to post a follow-up answer within a set time, or add a UI cue that shows whether a question has been answered. Creators should adopt community-first standards: if you tease, commit to delivering value.

Challenge 2: Gamification of attention with little accountability - Problem: Intermittent reinforcement mimics gambling mechanics; unpredictable rewards sustain compulsive participation with minimal benefit. - Solution: Platform-level transparency on engagement practices and clearer guidelines about manipulative hooks. Tools like cooldowns for repeated “Guess” posts or labeling conspicuous manipulative formats could reduce compulsive cycles.

Challenge 3: Mis- and disinformation vectors - Problem: The same curiosity mechanics can be weaponized to spread falsehoods. A “Guess” that implies scandal or wrongdoing—without evidence—can spawn harmful speculation. - Solution: Strengthen community moderation and verification signals. When a trend uses a song or phrase to signal a potentially harmful tease, algorithms can deprioritize content until accounts post verifiable follow-ups.

Challenge 4: Regulatory scrutiny and ethical gray areas - Problem: As public awareness grows, regulators may clamp down on platforms that permit systemic attention manipulation—especially affecting young users. - Solution: Proactive compliance: platforms should commission independent audits of behavioral optimization systems, implement age-sensitive safeguards (Gen Z is overexposed to these mechanics), and work with regulators to craft measured rules that don’t stifle creativity but limit exploitation.

Challenge 5: Creator incentives vs. audience welfare - Problem: Creators are financially incentivized to maximize engagement—even at the cost of audience fatigue. - Solution: Diversify monetization channels so creators aren’t solely dependent on engagement metrics. Sponsorships, subscriptions, and direct commerce models that reward genuine value can reduce reliance on manipulative hacks.

None of these solutions are quick fixes. They require collaborative effort—platform product teams, creators, advertisers, researchers, and policymakers must align incentives around user welfare, not merely short-term engagement growth. But incremental changes—like a platform nudge encouraging honest reveals, or advertiser standards that penalize manipulative formats—can start to shift norms.

Future Outlook

Where does the “Guess” trend point us next? Based on platform dynamics and historical patterning, several plausible trajectories are emerging.

Sophistication and Hybridization

Expect creators and brands to iterate. Simple “Guess” teases will morph into layered experiences—multi-part narratives, interactive polls, paid “reveal” livestreams, or AR filters that hide and reveal content. The mechanics will grow more sophisticated, leveraging AI-driven personalization to tailor curiosity hooks to individual users.

Algorithmic Countermeasures or Encouragement

TikTok’s algorithms will evolve in two possible directions. They may learn to detect low-value “Guess” manipulations and penalize them, favoring content that delivers real follow-through. Alternatively, TikTok might double down—if “Guess” behavior materially increases revenue, algorithmic incentives could amplify it even more aggressively. The company’s $23 billion 2024 revenue and rapid growth present a perverse incentive to favor the latter.

Platform Spillover

Tricks that work on TikTok migrate quickly. Instagram, YouTube Shorts, and other short-form platforms will adapt their own versions. Expect cross-platform “Guess” memes and format cloning that extend the behavioral pattern beyond TikTok’s walls.

Regulatory Pressure and Standards

As public discourse around attention manipulation grows, regulators may introduce transparency requirements for engagement-optimized content, particularly focusing on youth protections. We may see mandated disclosure for “deliberately withheld content” or limits on exploitative intermittent reward mechanics.

User Literacy and Resistance

Cultural backlash is a realistic counterforce. As users become more media literate, some will actively avoid manipulative formats. Communities may develop “anti-Guess” norms—creators who refuse to play the game may gain credibility. Education campaigns that teach digital curiosity awareness could blunt the trend’s power.

Research and Ethical Design

Academic and industry research will increasingly scrutinize how micro-formats reshape attention. Ethical design practices will gain traction among responsible creators and platforms, emphasizing follow-through, transparency, and actual value.

The “Guess” trend is a symptom of an attention economy that monetizes cognitive vulnerabilities. Whether it becomes a footnote or a long-term pattern depends on choices by platforms, creators, and regulators over the next year. The tension between monetization and user welfare will define the future of short-form content.

Conclusion

TikTok’s “Guess” trend is deceptively clever because it turns the most human of impulses—curiosity—into a scalable, repeatable monetization engine. Through a compact set of tactics (information gaps, memeified audio cues, social-proof-fueled comment cascades, and intermittent reinforcement), creators can induce millions of micro-actions that boost algorithmic visibility and, ultimately, platform revenue. With 1.6 billion active users, an average session time of about 58 minutes, and billions in annual revenue, the stakes are large: the attention economy rewards whatever can reliably grab and hold eyeballs.

This isn’t merely a cultural quirk. It’s a case study in behavioral engineering embedded in everyday entertainment. That can be benign—creative creators and ethical marketers can use curiosity to build genuine engagement and community—but it can also be corrosive, fostering cynical audiences, amplifying misinformation, and normalizing manipulative interaction patterns. The responsibility to correct course is shared: platforms must embrace design choices that discourage exploitation; creators should prioritize value over vanity metrics; advertisers should avoid rewarding manipulative formats; and users need better digital literacy to recognize when curiosity is being harvested.

To repeat: if you’ve ever typed a guess into a comment section because you felt an itch you couldn’t scratch, you were participating in a highly optimized loop built to make you act. Knowing that isn’t just explanatory—it’s empowering. Recognize the signals, demand follow-through from creators, and support platform policies that prioritize authentic interaction over manufactured engagement. The “Guess” trend is brilliant in its mechanics—but brilliant should not be a synonym for exploitative. We can enjoy the creativity and learn new participatory forms without letting engineered curiosity become a substitute for real value.

Actionable takeaways: - For users: Pause before you comment—ask whether the exchange will add value to you or just feed a loop. Follow creators who deliver honest follow-through. - For creators: Use curiosity ethically—if you tease, answer. Convert engagement into real community-building, not just algorithmic signals. - For brands: Test curiosity-driven formats but measure conversion and brand sentiment, not just comments. - For platforms: Implement nudges and affordances that reward completed narratives and penalize habitual manipulation. - For policymakers and researchers: Fund and legislate transparency audits of engagement-optimization systems, with a focus on young users.

The “Guess” trend is a mirror. It reflects not only clever content creation but the incentives that shape our digital behavior. Recognize the reflection—and choose whether to change the picture.