The TikTok “Guess” Trend Is Actually Psychological Manipulation—And Creators Are Getting Rich Off Your FOMO

Introduction

If you’ve scrolled TikTok in the last year you’ve probably seen it: a tight, tantalizing hook—“You’ll never believe what happened”—a few cryptic hints, then, when a comment asks for the payoff, a clipped reply: “Guess.” The audio. The pause. The comments exploding with people speculating, begging for the reveal, sharing theories—and the creator racking up thousands of additional views, new followers, and a flood of comments that supercharge the video’s distribution. What started as a playful format for teasing stories and pranks has metastasized into one of the platform’s most poisonous attention hacks.

This exposé unpacks why the “Guess” trend is less a quirky format and more a sophisticated application of social-media psychology and algorithm manipulation. We’ll trace the mechanics—how curiosity gaps, FOMO, and the Zeigarnik effect are weaponized on a platform whose metrics favor immediate engagement—and we’ll quantify what’s at stake. TikTok is now among the world’s biggest attention economies (reported at roughly 1.59–1.6 billion monthly active users and about 1.2 billion daily active users spending an average 58 minutes a day on the app). The platform generated roughly $25 billion in revenue in 2025 and registers engagement rates around 2.5% per post—about five times higher than Instagram. Those numbers are the incentive structure; the “Guess” trend is one of the tactics.

This is not a harmless meme. It’s a revenue engine and a behavioral lever. Creators use it to inflate engagement (comments, rewatching, shares), which the algorithm rewards with more reach. That attention is convertible: to followers, to sponsored content, to TikTok Shop sales (TikTok Shop reported $33.4 billion GMV in 2024), and to brand deals. Hashtags like #TikTokMadeMeBuyIt—already topping some 75+ billion views—show how readily curiosity-driven attention translates to purchases. Meanwhile AI-generated content now accounts for roughly 52% of TikTok’s supply, magnifying the risk that these manipulative formats will be automated and scaled.

This piece breaks down the psychological playbook behind “Guess,” how the algorithm amplifies it, who benefits (and how much), and what practical steps users, creators, platforms, and regulators can take to push back.

Understanding the “Guess” Trend: what it is, where it came from, and why it works

At its simplest, the “Guess” trend is a content format: creators tease a story or fact, invite speculation, then refuse to reveal the answer (or reveal it only after extended engagement). The sound that popularized it—Charli XCX’s track “Guess” (featuring Billie Eilish)—gave the format a recognizable audio stamp that helped it go viral. But the sound alone doesn’t explain the trend’s rapid spread. The method exploits several documented cognitive biases and platform dynamics.

Curiosity gap: The human brain is optimized to close incomplete narratives. When we encounter an unresolved story—especially one implying social stakes—we experience an unpleasant tension (a psychological itch) that drives us to seek resolution. Media theorist George Loewenstein called this the “curiosity gap.” TikTok creators deliberately make that gap wide and emotionally charged (“I found something illegal at my neighbor’s house… guess what it was”), prompting comments and repeat views.

Zeigarnik effect: This is the tendency to remember unfinished tasks better than completed ones. Online, an unresolved thread in comments or a cliffhanger video increases the probability that users will return, rewatch, or keep engaging until the narrative is closed—if it ever is.

FOMO (Fear of Missing Out): The trend implies exclusivity—someone “knows” something we don’t—and that invites public participation. The comments section becomes a social arena where early guessers can claim status, and latecomers scramble to keep up. Because 82% of Gen Z are active on TikTok, and the platform skews young, FOMO is particularly potent: younger users socialize identity and status via platform engagement.

Reinforcement/dopamine loops: Micro-rewards (likes on a reply, heart reactions to speculative comments, the thrill of being among the first to guess correctly) create a small dopamine reward. When creators withhold gratification, the intermittent reward schedule becomes addictive—users return, refresh, and re-engage in expectation.

Algorithmic incentives: TikTok’s recommendation engine prioritizes signals like watch time, replays, comments, and shares. A video baiting comments and replays spikes these metrics. Reported average engagement rates on TikTok are roughly 2.5% per post—about five times higher than Instagram—so formats that intentionally increase comments (engagement bait) enjoy outsized amplification. In a system that sees roughly 34 million videos uploaded daily (around 270 per second), attention is scarce; anything that reliably engineers engagement gets fed to more viewers.

Monetization bridge: The attention harvested through “Guess” can be monetized. TikTok’s creator monetization channels—Creator Fund, brand partnerships, and the platform’s commerce integrations—reward scale. TikTok Shop’s $33.4 billion GMV (2024) and ubiquitous campaign hashtags like #TikTokMadeMeBuyIt (75+ billion views) demonstrate how platform attention converts to purchases. Creators who build large, engaged audiences through manipulative hooks can monetize via direct product pitches, affiliate links, or brand deals that pay far more than simple ad revenue.

Finally, scale and automation intensify the problem. With AI-generated content reportedly making up 52% of TikTok’s output, the risk is that engagement-bait formats will be codified into templates and scaled by automated accounts that have no ethics or empathy—only optimization goals.

Key Components and Analysis: the playbook, the math, and the actors getting paid

Break down a typical “Guess” video and you find a formula designed to game human attention and the platform’s metrics.

1) Hook + cliffhanger (0–3 seconds): Rapid visual or auditory cue that promises drama. Example: “My apartment smelled like gas—guess why.” This immediately triggers the curiosity gap.

2) Partial stakes + social cue (3–12 seconds): The creator provides a salient, emotionally loaded hint—someone was there, something illegal, an awkward reveal—then encourages comments (“What do you think? Guess!”). Social cues (pointing to comments, onscreen text) direct behavior.

3) Withholding payoff / pettiness reply: Instead of answering in the video, the creator fosters interaction by replying in comments, doing occasional reveals to high-engagement users, or promising a follow-up video (“I’ll post what happened if this gets 100k comments”). That conditional reveal is the sweet spot for generating engagement.

4) Engagement multiplier: Every additional comment, reply, share, and rewatch sends algorithmic signals that broaden reach. Creators can seed comments (sockpuppet accounts or friends), pin comments, or reply to comments in ways that loop viewers back.

The math matters. Reported metrics show:

- Engagement rate ~2.5% per post (average), significantly higher than Instagram. - TikTok's user base around 1.59–1.6 billion monthly active users; roughly 1.2 billion daily users spending on average 58 minutes per day. - 34 million videos uploaded daily, creating brutal competition for attention. - Advertising reach reportedly hits 1.59 billion people (≈19.4% of global population), making every engagement worth potential ad or commerce conversion. - TikTok Shop’s $33.4 billion GMV (2024) and massive hashtag-driven commerce activity (e.g., #TikTokMadeMeBuyIt) turn engagement into measurable sales. - Creators leveraging these tactics turn engagement into brand deals, sponsored posts, or TikTok Shop commissions—income streams that can quickly dwarf ad-sharing payouts.

Who’s profiting? It’s not just the superstar creators you see on the For You Page. Micro-influencers who master these hooks can create rapid follower growth and then monetize via niche affiliate funnels, merch, or product drops. The platform’s Creator Fund pays per view/engagement in ways that favor consistent high-performance formats. Brands and advertisers also benefit indirectly: high-engagement creators can command higher CPM-equivalent fees for sponsored posts because their audiences are so active.

The role of AI and automation cannot be overstated. With approximately half of TikTok content now reported to be AI-assisted or generated, templates that reliably extract comments and replays can be automated, multiplied, and optimized far faster than human creators can produce original content. That means the exploitation of attention-per-second becomes industrialized, with creators (and companies behind them) extracting value from human cognitive biases at scale.

Finally, context: the trend builds on platform dynamics—short-form vertical video, an algorithm that privileges immediate engagement, and a user base (young, socially driven) prone to FOMO—all of which together create fertile ground for engagement-bait strategies.

Practical Applications: how creators use it, how brands exploit it, and how users get pulled in

For creators who want fast growth, the “Guess” trend is an efficient growth hack. Here’s how it’s used in practice—and how brands and sellers exploit it.

Creators: - Growth loops: Post a cliffhanger with a promise to reveal; pin comments and reply to fan theories to prolong engagement; post the “reveal” in a separate video to create a chain that drives more views across multiple uploads. - Monetization funnel: Use “Guess” to grow followers, then convert followers to buyers via TikTok Shop, affiliate links, or limited drops. With TikTok Shop reported at $33.4 billion GMV in 2024 and U.S. users reportedly spending around $1,200 annually on TikTok shopping, a few high-converting posts can pay materially. - Cross-platform play: Use viral TikTok content to drive followers to Instagram, YouTube, or newsletters where monetization is diversified.

Brands: - Engagement-first campaigns: Partner with creators who specialize in curiosity hooks to drive product discovery. Brands know that engagement begets visibility; a product reveal tied to a “Guess” format can surge awareness and sales. - Hashtag amplification: Leverage proven viral hooks (#TikTokMadeMeBuyIt is a prime example) to convert views to purchases. Brands can seed comments through brand accounts or influencers to boost early engagement.

Users: - Social signaling: Many users participate because commenting is a low-effort way to appear social and “in the know.” The public record of comments becomes a badge of identity, especially among Gen Z where 82% are active on the platform. - FOMO spending: The fear of missing out on a viral find or a limited product drop drives impulsive clicks on TikTok Shop, sometimes leading to poor purchasing decisions.

Ecosystem-level effects: - Commerce amplification: Hashtag-driven commerce and creator funnels mean that attention is directly monetizable. #TikTokMadeMeBuyIt (75+ billion views) is the poster child for attention-to-purchase conversion. - Reinforcement of formats: Because the algorithm rewards engagement, formats like “Guess” spread quickly and become standard operating procedure—pushing creators who want growth to adopt manipulative formats to stay competitive.

User experience consequences are significant: manipulative hooks increase time-on-platform, heighten emotional arousal, and normalize strategic withholding as content practice. For creators, the ethical cost is ambiguous: many feel pressure to adopt these tactics to grow, while others weaponize the format knowingly for profit.

Challenges and Solutions: ethical, platform-level, and user-centered responses

Challenges

Solutions

For users: - Slow consumption: Install friction. Use TikTok’s “Take a Break” and limit features. Pause before commenting or clicking links—ask, “Am I reacting to curiosity or being manipulated?” - Audit follow lists: Follow creators who prioritize transparent storytelling and call out consistent clickbait behavior by unfollowing manipulative accounts. - Protect spending: Disable in-app purchases or remove saved payment methods. Treat TikTok Shop “drops” like marketing: research products independently.

For creators: - Ethical growth playbook: Prioritize value. If using hooks, deliver on promises quickly and transparently. Consider disclaimers when a video teases sensitive content. - Diversify monetization: Build email lists and other off-platform channels so growth isn’t dependent on manipulative tactics rewarded by one algorithm. - Document practices: If you use engagement prompts, disclose them (e.g., “Comment ‘Guess’ if you want the reveal tomorrow”) and deliver.

For platforms: - Policy updates: Create clearer rules against artificial engagement bait—especially when paired with commercial intent. Promote signals that value quality content (time watched per video but also user satisfaction surveys). - Detection & enforcement: Invest in tools to detect coordinated comment-farming, sockpuppetry, and AI-generated manipulative templates. - Transparency: Publish regular transparency reports on engagement manipulation tactics and take action on repeat offenders.

For regulators and researchers: - Measurement frameworks: Fund independent studies into the prevalence and harms of engagement-bait formats and their conversion rates into sales and ad revenue. - Consumer protection: Consider requiring explicit disclosures when content is produced to drive commerce or is part of a paid amplification campaign.

No single solution will fix the problem overnight. But combined, user literacy, creator ethics, platform policy, enforcement, and regulation can reduce the exploitative pressure currently baked into short-form social ecosystems.

Future Outlook: where the “Guess” trend could go—and what it means for digital behavior

Short-term trajectory Expect the “Guess” format to persist and morph. As creators iterate, you’ll see more elaborate multi-part reveal sequences, cross-posted cliffhangers, and higher-stakes manufactured drama designed specifically for comment generation. Because AI-generated content accounts for roughly 52% of TikTok’s reported output, expect automated templates that produce “Guess”-style videos at scale, optimized by real-time A/B testing to maximize comments and watch time.

Commerce integration will deepen. With TikTok Shop’s $33.4 billion GMV reported for 2024 and substantial per-user spend figures in some markets (U.S. users reported to spend around $1,200 annually on TikTok shopping), brands have strong financial incentives to leverage creators who can reliably create FOMO-driven demand. That dynamic will push more creators toward manipulative hooks, especially those monetizing commerce directly.

Platform evolution TikTok’s recommendation engine will keep rewarding immediate engagement unless its metrics are rebalanced. There are technical options—de-emphasize comment volume as a primary amplification signal, introduce friction for large comment surges (bot detection), and boost content discovered by meaningful time and repeat visits that end in long-form value consumption (e.g., informative explainers).

Regulatory pressure and public scrutiny could force changes. As the public becomes more aware of manipulative engagement tactics, platforms face reputational risk. The advertising ecosystem (brands and agencies) will also be a lever—many brands will balk at partnerships that rely on deceptive tactics. If major advertisers demand responsible creator behavior, that could reshape incentives faster than regulation.

Long-term cultural implications If left unaddressed, manipulative trends can restructure digital behavior norms. Younger users may come to expect content that continually withholds gratification as standard; that could normalize transactional attention economies where every interaction is a micro-conversion attempt. Conversely, increased media literacy and a backlash against engineered virality could spur a renaissance of authentic formats—content that prioritizes genuine storytelling over engineered dopamine lifts.

AI’s dual role AI will amplify and potentially mitigate the problem. On one hand, AIs trained to optimize for engagement will discover increasingly sophisticated psychological nudges; on the other hand, AI tools could detect manipulation, identify coordinated behavior, and assist platforms in policing engagement abuse. The policy and design choices platforms make about AI will determine which future wins out.

What this means for digital behavior scholars and practitioners For researchers, the “Guess” trend is a test case in how platform architecture interacts with cognitive biases to shape large-scale behavior. For designers and product managers, it’s a warning: reward signals determine user norms. For policymakers, it’s a call to act before attention commodification becomes more deeply entrenched and harder to unwind.

Conclusion

The “Guess” trend looks playful, even innocuous—until you step back and see the system it’s embedded in. It leverages deep-rooted cognitive biases—curiosity gaps, the Zeigarnik effect, FOMO—and feeds them into an algorithm that monetizes engagement. The reward structure on TikTok (and platforms like it) makes engagement bait economically rational for creators and brands. The result is a feedback loop where human psychological vulnerabilities are productized into profit.

The stakes go beyond annoying clickbait. This dynamic reshapes digital behavior: it normalizes manipulative attention tactics, encourages impulsive commerce, and incentivizes the automation of psychological exploitation. The numbers are stark—1.59–1.6 billion monthly users, 1.2 billion daily users, average session lengths near an hour, engagement rates around 2.5% per post, 34 million videos uploaded daily, half the content potentially AI-generated, and commerce ecosystems worth tens of billions of dollars. Those metrics are both reason and risk.

But the situation isn’t hopeless. Users can reclaim agency through deliberate friction and digital literacy; creators can choose ethical growth paths and diversify monetization; platforms can redesign incentives and enforce transparency; regulators and researchers can create guardrails and better measurement. The question isn’t whether attention can be monetized—attention always has been—but whether we want an attention economy that profits by exploiting the architecture of human curiosity and anxiety.

Actionable takeaways (quick reference) - For users: Install consumption friction (timeouts, payment blockers), pause before commenting, and research products outside the app before purchasing. - For creators: If you use hooks, deliver quickly and transparently; diversify income streams off-platform. - For platforms: Rebalance algorithmic rewards away from raw comment volume, invest in detection of coordinated engagement and AI-generated manipulation, and publish transparency reports. - For policymakers and researchers: Fund independent studies into engagement-bait prevalence and its behavioral impacts; consider disclosure requirements for content designed to drive commerce.

The “Guess” trend is not just a meme. It’s a mirror showing how social platforms can turn the human impulse to know into a monetizable lever. Understanding that lever is the first step to choosing whether to pull it—or to let it pull you.