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Emerging Behaviours

21 min read

On this page

  • How It Works
  • When to Use This Framework
  • When It Misleads
  • Step-by-Step Process
  • Questions to Ask Yourself
  • Company Examples
  • Adjacent Frameworks
  • Analyst's Take
  • Opportunity Checklist
  • Top Resources

Contents

  1. 1. How It Works
  2. 2. When to Use This Framework
  3. 3. When It Misleads
  4. 4. Step-by-Step Process
  5. 5. Questions to Ask Yourself
  6. 6. Company Examples
  7. 7. Adjacent Frameworks
  8. 8. Analyst's Take
  9. 9. Opportunity Checklist
  10. 10. Top Resources
Emerging Behaviours is a market-sensing framework that identifies shifts in how younger generations interact with technology, media, and each other — and treats those shifts as leading indicators of mass-market demand before incumbents recognize them.
Section 1

How It Works

The core insight is deceptively simple: the way 16-year-olds use technology today is the way 36-year-olds will use it in five years. Younger cohorts — unburdened by legacy habits, institutional expectations, or sunk costs in existing platforms — adopt new interaction patterns first. Those patterns don't stay niche. They migrate upward through age demographics with remarkable consistency, and the companies that build for those patterns early capture the market before incumbents even notice the shift.
This works because of a well-documented asymmetry in how behavioral change propagates. Older demographics don't adopt new behaviors because they read about them in trend reports. They adopt them because the infrastructure, social norms, and product ecosystems built by younger users eventually become unavoidable. When teens started communicating through images instead of text in 2011, it wasn't a fad — it was a permanent rewiring of communication preferences that Snapchat and Instagram captured and that eventually reshaped how every age group interacts with their phone. When Gen Z began defaulting to short-form vertical video over horizontal long-form content around 2017, it wasn't a quirk of youth culture — it was a signal that attention economics had fundamentally shifted. TikTok read that signal. YouTube, Netflix, and Instagram spent the next four years scrambling to catch up.
The underlying principle is that technology adoption follows behavior, not the other way around. Most founders build technology and hope behavior changes to match. The Emerging Behaviours framework inverts this: you observe the behavior first, then build the technology that serves it. This dramatically de-risks product development because you're not betting on hypothetical demand — you're betting on demand that already exists in a younger cohort and is migrating toward the mainstream.
The framework also exploits a structural blind spot in incumbent organizations. Large companies optimize for their existing user base, which skews older and more profitable. They systematically underweight signals from younger users who don't yet have purchasing power. This creates a recurring window — typically 3–7 years — where an emerging behavior is clearly visible but commercially underserved.
"I skate to where the puck is going to be, not where it has been."
— Wayne Gretzky, frequently cited by Steve Jobs
Section 2

When to Use This Framework

✓

Best Conditions for the Emerging Behaviours Framework

DimensionIdeal conditions
Founder profileCulturally fluent observers — founders who spend time in online communities, understand platform dynamics, and can distinguish between a fleeting trend and a durable behavioral shift. Age matters less than cultural proximity; a 40-year-old who genuinely understands Discord culture can apply this as well as a 22-year-old.
StageIdeation through Series A. The framework is most powerful when choosing what to build. It becomes less useful once you have a product and are optimizing unit economics — at that point, you're executing against a behavior you've already identified.
Market conditionsBest during platform transitions (mobile → mobile-first video → AI-native), generational inflection points (Gen Z entering workforce, Gen Alpha entering teen years), or when new hardware creates new interaction modalities (AirPods normalizing audio, Vision Pro testing spatial computing).
Competitive environmentIdeal when incumbents are large, profitable, and optimizing for existing demographics. The bigger the incumbent's revenue from older users, the slower they'll pivot to serve emerging behaviors — creating a wider window for new entrants.
Inputs neededEthnographic observation (spending time on TikTok, Discord, BeReal, Roblox), app store analytics (Sensor Tower, data.ai), social listening tools, Pew Research generational studies, and — critically — direct conversations with 15–25 year olds about how they actually spend their time.
The framework is unusually potent right now for two reasons. First, Gen Alpha (born 2010–2024) is the first generation raised entirely on algorithmic feeds, voice interfaces, and AI-generated content — their baseline behaviors are radically different from even Gen Z's. Second, the gap between youth adoption and mainstream adoption is compressing: TikTok went from teen novelty to the most-used social app in the world in roughly three years, compared to the decade it took Facebook to make the same journey. The observation window is shrinking, which means founders who can read emerging behaviors early have an even larger advantage.
Section 3

When It Misleads

The framework's greatest strength — pattern-matching from youth behavior — is also its most dangerous failure mode:
⚠

Failure Modes & Blind Spots

Blind spotWhat goes wrong
Confusing fads with shiftsNot every youth behavior migrates upward. Clubhouse captured a real behavior (live audio socializing) but it turned out to be pandemic-specific, not generational. The behavior evaporated when the context changed. You need to distinguish between behaviors driven by durable structural forces (shorter attention spans, mobile-first interaction) and those driven by temporary conditions.
Monetization lagYoung users adopt fast but pay slowly. Snapchat had 100 million daily active users before it had a credible revenue model. Building for emerging behaviors often means building for a demographic with limited purchasing power, then waiting years for monetization to catch up. If your capital runway doesn't match this timeline, you die before the market matures.
Incumbent fast-followLarge platforms have become dramatically faster at copying emerging behaviors. Instagram cloned Stories from Snapchat in 2016 and Reels from TikTok in 2020. If the behavior you've identified can be replicated as a feature inside an existing platform, your window may be months, not years.
Observer biasFounders tend to see what they want to see. If you're already excited about a product idea, you'll find "emerging behaviors" that confirm it. The framework requires genuine ethnographic discipline — observing without a hypothesis, not cherry-picking signals that support a predetermined conclusion.
Cultural non-transferabilityA behavior emerging among American teens may not transfer to Japanese, Nigerian, or Brazilian teens. Youth culture is increasingly global but still deeply local. K-pop fandom behaviors don't map cleanly onto American music consumption patterns, even when the same platforms are involved.
The single most common mistake is building for a behavior that's real but not durable. The test isn't "are young people doing this?" — it's "are young people doing this because of a structural change in how they interact with technology, or because of a temporary social context?" Ephemeral messaging (Snapchat) was structural — it reflected a genuine shift toward privacy-conscious, low-stakes communication. Audio-only social networking (Clubhouse) was contextual — it reflected pandemic isolation, not a permanent preference for voice over video.
Section 4

Step-by-Step Process

Step 1 — Immerse

Embed yourself in youth-native platforms and communities

Spend a minimum of 5 hours per week on platforms where 15–25 year olds are the primary users — not reading about those platforms, but using them. Create accounts, follow creators, join Discord servers, play Roblox games. You're looking for interaction patterns, not content. How do people communicate? What do they share? What do they refuse to do? Keep a running log of behaviors that surprise you or that have no equivalent in older demographics.
Tools: TikTok, Discord, Roblox, Twitch, Reddit (teen-heavy subreddits), BeReal, Sensor Tower app charts
Step 2 — Categorize

Distinguish structural shifts from surface trends

For each behavior you've logged, apply the structural test: Is this behavior enabled by a technology change (e.g., better phone cameras → visual communication)? Is it driven by a generational value shift (e.g., privacy consciousness → ephemeral content)? Or is it driven by a temporary context (e.g., pandemic boredom → Clubhouse)? Only structural and value-driven behaviors are worth building for. Cross-reference with quantitative data — if a behavior is growing 30%+ year-over-year across multiple markets, it's likely structural.
Tools: Pew Research Center generational data, eMarketer, Comscore, academic papers on media consumption
Step 3 — Map

Identify the commercial gap between behavior and product

The behavior exists. Now ask: what product would perfectly serve this behavior, and does it exist yet? If teens are spending 3 hours a day on short-form video but the only monetization tool for creators is brand deals, there's a gap. If young professionals are using AI tools for work but no enterprise product is designed for their workflow, there's a gap. The gap between observed behavior and available product is your opportunity space.
Deliverable: Behavior-to-product gap analysis — a one-page document mapping the behavior, the current (inadequate) solutions, and the product opportunity
Step 4 — Validate

Test with the cohort that exhibits the behavior

Build a lightweight prototype or landing page and put it in front of 50–100 users from the target demographic. Don't ask "would you use this?" — observe whether they actually engage. Run a 2-week test in a Discord server or a TikTok comment section. The validation signal you're looking for isn't enthusiasm — it's repeated, unprompted usage. If users come back without being asked, the behavior-product fit is real.
Tools: Figma prototypes, Maze usability testing, Instagram/TikTok polls, micro-communities on Discord, landing page tests
Step 5 — Time

Estimate the migration window and build your capital plan accordingly

The hardest question: how long until this behavior goes mainstream? Study analogous adoption curves. Short-form video went from teen niche to mass market in roughly 3 years. Ephemeral messaging took about 4 years. Mobile payments in the U.S. took nearly a decade. Your capital plan must match the migration timeline — if you'll need 5 years of runway before the mainstream arrives, your fundraising strategy needs to reflect that from day one.
Tools: Historical adoption curves (smartphone, social media, streaming), cohort aging models, investor pitch frameworks
Section 5

Questions to Ask Yourself

Discovery
What are 15–22 year olds doing on their phones that 35-year-olds find confusing or pointless?
Which apps are growing fastest among users under 25 that have no equivalent for older demographics?
What communication norms have shifted in the last 2 years (e.g., voice notes replacing texts, memes replacing words)?
What do young users actively refuse to do that older users take for granted (e.g., phone calls, email, long-form reading)?
Validation
Is this behavior growing because of a structural technology shift, a generational value change, or a temporary context?
Can I find quantitative evidence (app downloads, time-spent data, survey data) that this behavior is accelerating, not plateauing?
Have I observed this behavior across at least two distinct cultural or geographic contexts, suggesting it's not locally specific?
Is there a clear product gap — something users are doing despite inadequate tools, not because of great tools?
Execution
Can an incumbent replicate this as a feature within their existing platform in under 6 months?
Does my product require network effects to work, and if so, can I achieve critical mass in the target demographic before the behavior goes mainstream?
What's my monetization timeline — and do I have enough capital to survive until the behavior migrates to demographics with purchasing power?
Am I building a product that grows with the cohort as they age, or one that only works for a narrow age window?
Risk
What would cause this behavior to reverse or plateau — and how would I detect that early?
If TikTok, Instagram, or YouTube added this as a feature tomorrow, would my product still have a reason to exist?
Am I projecting my own excitement onto a behavior that might be less durable than I think?
Section 6

Company Examples

T
TikTok
Built for the shift from curated feeds to algorithmically-served short-form video
ByteDance's Musical.ly acquisition in 2017 (reportedly $800 million–$1 billion) and subsequent relaunch as TikTok was a masterclass in reading emerging behaviors. The behavior was clear by 2016: teens were creating and consuming video in sub-60-second bursts, preferring algorithmic discovery over social-graph-based feeds, and gravitating toward raw, unpolished content over the curated aesthetic that dominated Instagram. TikTok didn't invent short-form video — Vine had proven the format years earlier. What TikTok did was build the infrastructure (the For You Page algorithm, the creation tools, the sound library) that perfectly matched the behavior at scale. By 2023, TikTok had surpassed 1.5 billion monthly active users globally, and its core interaction pattern — swipe-to-discover vertical video — had been copied by every major social platform.
S
Snapchat
Identified the shift toward ephemeral, low-stakes digital communication
Evan Spiegel and Bobby Murphy observed something in 2011 that most adults dismissed: young people were anxious about the permanence of their digital footprint. Every photo on Facebook, every tweet, became a permanent record. The emerging behavior was a retreat from permanence — teens wanted to communicate in ways that felt more like real conversation, where messages disappeared after being seen. Snapchat launched Stories in 2013, pioneered AR lenses, and by 2014 was processing more photos per day than Facebook. The company went public in 2017 at a $24 billion valuation. The behavior Snapchat identified — ephemeral, visual, playful communication — proved so durable that Instagram copied Stories wholesale in 2016, and the feature now drives a significant portion of Instagram's engagement.
I
Instagram
Captured the mobile photography behavior before it became mainstream
When Kevin Systrom and Mike Krieger launched Instagram in October 2010, the iPhone 4 had just shipped with a dramatically improved camera. The emerging behavior was unmistakable if you were paying attention: young smartphone users were taking more photos than ever, but the photos looked terrible and there was no native social layer for sharing them. Instagram's filters solved the quality problem; its feed solved the distribution problem. The app hit 1 million users in two months and 10 million within a year. Facebook acquired it for $1 billion in April 2012 — a price that seemed absurd at the time and now looks like one of the greatest acquisitions in tech history, given Instagram reportedly generates over $50 billion in annual ad revenue.
Amazon logo
Amazon
Recognized that watching other people play games was becoming a mainstream entertainment behavior
Justin.tv pivoted to Twitch in 2011 after noticing that its gaming category was growing far faster than any other content vertical. The emerging behavior: teens and young adults were spending hours watching other people play video games — a behavior that older demographics found baffling. By 2013, Twitch was the fourth-largest source of peak internet traffic in the U.S., behind only Netflix, Google, and Apple. Amazon acquired Twitch in 2014 for $970 million, outbidding Google. The behavior Twitch identified — live, interactive entertainment built around gaming — has since expanded into music, cooking, "just chatting," and IRL streaming, validating that the core shift was about participatory live content, not just gaming.
D
Discord
Built for the shift from public social media to private, interest-based communities
By 2015, a counter-behavior was emerging among younger users: fatigue with public, performative social media and a preference for smaller, private, interest-based groups. Discord launched as a voice chat tool for gamers but quickly became the default platform for any community that wanted real-time, semi-private interaction — study groups, crypto communities, fan clubs, creator audiences. The product matched the behavior perfectly: always-on voice channels, text channels organized by topic, and no algorithmic feed. Discord reached 150 million monthly active users by 2023 and was reportedly valued at $15 billion after turning down a $12 billion acquisition offer from Microsoft in 2021. The behavior it captured — private community over public broadcast — continues to accelerate.
Section 7

Adjacent Frameworks

Emerging Behaviours rarely operates alone. It's a sensing framework that feeds into execution frameworks:
Pairs well with
Spot the fringes — what are nerds doing on weekends
The natural complement. Emerging Behaviours looks at youth demographics; Spot the Fringes looks at enthusiast communities. Together, they create a two-lens system for detecting demand before it becomes obvious — one generational, one subcultural.
Pairs well with
Category creation
Once you've identified an emerging behavior, Category Creation gives you the playbook for building a new market around it rather than competing in an existing one. TikTok didn't enter "social media" — it created "short-form entertainment."
In tension with
Focus on what won't change
Jeff Bezos's framework asks you to build on permanent human needs (low prices, fast delivery, wide selection). Emerging Behaviours asks you to build on changing human behaviors. The tension is productive: the best companies do both — serve a permanent need through a new behavioral channel.
In tension with
Build a Copycat
Copycat says replicate what's proven. Emerging Behaviours says build for what's forming. If you copy a product built for yesterday's behavior, you may arrive just as the behavior shifts. The frameworks pull in opposite directions on the risk spectrum.
Apply next
Sell an Identity
Once you've built a product around an emerging behavior, the next move is to make that product synonymous with the identity of the cohort that adopted it. Snapchat wasn't just a messaging app — it was what cool teens used. Identity lock-in is the moat that follows behavioral lock-in.
Apply next
Be a closer follower of a new category
If you've identified the behavior but someone else has already built the first product, the Close Follower framework helps you enter with better execution, a different demographic slice, or a superior business model — while the behavior is still migrating mainstream.
Section 8

Analyst's Take

Faster Than Normal — Editorial View
My honest read: this is the most powerful and most misused framework in the entire library.
It's powerful because every major consumer technology company of the last 15 years was built on an emerging behavior that incumbents dismissed. Facebook was built on the behavior of college students wanting to see each other's photos and relationship statuses. Instagram was built on the behavior of smartphone users wanting to share visual moments. TikTok was built on the behavior of teens preferring algorithmic entertainment over social feeds. Twitch was built on the behavior of young people watching other people play games. In every case, the behavior was visible years before the winning product was built — and in every case, older observers dismissed it as trivial, juvenile, or temporary.
It's misused because most founders confuse observing a behavior with understanding it. They see teens using a new app and conclude "I should build something like that." But the app is the surface. The behavior underneath is what matters. Vine proved that short-form video was a real behavior. But Vine failed because it didn't understand the behavior deeply enough — it thought the behavior was "watching 6-second loops" when the actual behavior was "discovering entertaining content from strangers through an algorithmic feed." TikTok understood the deeper behavior. That's why TikTok won.
The founders who apply this framework best share a specific trait: they're participant-observers, not analysts. They don't read reports about Gen Z. They're in the Discord servers. They're on the TikTok For You Page at 11pm. They're watching what their younger siblings or employees actually do, not what surveys say they do. The data is in the behavior, not the self-report.
The biggest risk right now is that the migration window is compressing. It used to take 5–7 years for a youth behavior to go mainstream. Now it takes 2–3. TikTok went from "that weird Chinese app teens use" to the most-downloaded app in the world in about 30 months. This means the opportunity window for founders is shorter, the capital requirements are higher (you need to scale faster), and the incumbent fast-follow threat is more severe. Instagram launched Reels within 18 months of TikTok's U.S. breakout. YouTube Shorts followed shortly after. If you're building for an emerging behavior in 2025, you need to assume you have 18–24 months before a platform with a billion users copies your core mechanic.
One more thing worth saying plainly: this framework has a built-in age bias that founders should be honest about. If you're over 35, your ability to naturally observe emerging behaviors degrades. Not because you're less intelligent, but because you're no longer embedded in the communities where behaviors emerge. The fix isn't to pretend you're still 22. The fix is to build a systematic observation practice — hire young researchers, embed in youth-native platforms, and treat your own instincts about "what young people want" with deep skepticism.
Section 9

Opportunity Checklist

Use this scorecard to evaluate whether a specific emerging behavior represents a viable product opportunity. Score each item as yes (1 point) or no (0 points).

Emerging Behaviours Opportunity Scorecard

The behavior is observable across at least two distinct platforms or communities, not confined to a single app.
The behavior has been growing for at least 12 months, suggesting durability rather than a momentary spike.
The behavior is driven by a structural force (technology change, generational value shift) rather than a temporary context (pandemic, viral moment).
No existing product perfectly serves this behavior — users are cobbling together workarounds or tolerating poor experiences.
Incumbents are either ignoring the behavior or serving it as a secondary feature rather than a core product.
The behavior is migrating upward in age demographics — early signs of adoption among 25–35 year olds, not just teens.
I can articulate the behavior in one sentence without referencing a specific app or platform (proving it's a behavior, not a product preference).
The behavior has a plausible monetization path within 3 years — either through the users themselves or through adjacent revenue (ads, commerce, subscriptions).
I have direct, first-hand observation of this behavior — not just secondhand reports or trend articles.
A product built for this behavior would be difficult for an incumbent to replicate as a feature, because it requires a fundamentally different product architecture or business model.
I can identify at least one historical analogue — a previous emerging behavior that followed a similar adoption curve and produced a large company.
Section 10

Top Resources

01
The Cold Start Problem — Andrew Chen (2022)
Book
Chen's framework for how network-effect products launch and scale is essential reading for anyone building on emerging behaviors. The early chapters on how products find their first atomic network — often a young, tight-knit community — map directly onto the Emerging Behaviours framework. The Tinder and Slack case studies are particularly relevant.
02
Hooked — Nir Eyal (2014)
Book
Once you've identified an emerging behavior, you need to build a product that captures it through habit formation. Eyal's Hook Model (trigger → action → variable reward → investment) explains why some products successfully harness new behaviors while others fail to retain users. The framework is especially useful for understanding why TikTok's infinite scroll works and why Quibi's scheduled content didn't.
03
Seeing What's Next — Clayton Christensen, Scott Anthony & Erik Roth (2004)
Book
Christensen's most underrated book applies disruption theory to prediction — specifically, how to identify which emerging signals will become mainstream disruptions and which will fizzle. The framework for analyzing "nonconsumption" (people who want to do something but can't with existing products) maps perfectly onto emerging behaviors that lack adequate product solutions.
04
Crossing the Chasm — Geoffrey Moore (1991)
Book
Moore's classic explains the gap between early adopters and the mainstream — the exact transition that the Emerging Behaviours framework depends on. Understanding why some products cross the chasm (Instagram, TikTok) while others stall in the early-adopter phase (Vine, Clubhouse) is critical for timing your build and your fundraising.
05
Aggregation Theory — Ben Thompson
Essay
Thompson's foundational essay explains how the internet enables companies to aggregate demand by owning the user relationship rather than the supply. This is the structural mechanism that makes emerging behaviors so valuable: the company that captures a new behavior first aggregates the demand, and aggregators tend to win permanently. Essential for understanding why being early to an emerging behavior creates durable competitive advantage.

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On this page

  • How It Works
  • When to Use This Framework
  • When It Misleads
  • Step-by-Step Process
  • Questions to Ask Yourself
  • Company Examples
  • Adjacent Frameworks
  • Analyst's Take
  • Opportunity Checklist
  • Top Resources