I once spent $299 on a course I never watched.
Not because I needed it. Not because I researched it. Not because it fit my learning style.
I bought it because I saw “47,329 students enrolled.”
My brain did the math: “47,000 people can’t be wrong. This must be good.”
Spoiler: It wasn’t good. For me, anyway. The content was basic, the pacing was wrong, and I could’ve learned the same material for free.
But in that moment, the number of students was all the proof I needed.
This is social proof: the psychological phenomenon where we copy the actions of others, assuming their behavior reflects correct behavior.
And it’s one of the most powerful forces shaping your decisions every single day.
What is Social Proof?
Social proof was first formally studied by Robert Cialdini in his seminal book “Influence: The Psychology of Persuasion” (1984).
The principle:
When uncertain, people look to the behavior of others to guide their own behavior.
The assumption:
“If everyone else is doing it, it must be the right thing to do.”
Why it evolved:
In evolutionary terms, following the crowd was often smart:
- Everyone’s running? There’s probably a predator. Run.
- Everyone’s eating these berries? They’re probably safe. Eat.
- Everyone’s avoiding this area? There’s probably danger. Avoid.
The problem:
This heuristic made sense in small tribes.
It’s exploitable (and often wrong) in modern markets, social media, and technology choices.
The Classic Social Proof Experiments
The Asch Conformity Experiments (1951)
The setup:
Solomon Asch put participants in groups of 8. Seven were confederates (in on the experiment). One was the real subject.
The task:
Look at a line. Pick which of three comparison lines matches its length.
The catch:
The seven confederates all gave the same WRONG answer out loud before the real subject answered.
Results:
75% of real subjects conformed to the wrong answer at least once.
On average, subjects conformed to incorrect answers 37% of the time.
Translation:
People will literally deny what they see with their own eyes if the group says otherwise.
The Bystander Effect
Classic case: Kitty Genovese (1964)
38 witnesses heard her being attacked. None called police.
Why?
Each person looked to others for cues. “Nobody else is helping, so maybe it’s not that serious.”
The research:
Latané and Darley (1968) showed that the more people present, the LESS likely any individual is to help.
Why?
Diffusion of responsibility + social proof.
“If it were really an emergency, someone else would’ve helped already.”
The Types of Social Proof
Cialdini identified several categories:
1. Expert Social Proof
The principle:
We follow the actions of credible experts.
Examples:
“9 out of 10 dentists recommend…” “As featured in: TechCrunch, WSJ, Forbes” “Recommended by Linus Torvalds”
In tech:
“DHH uses this stack, so it must be good.” “Kent C. Dodds recommends this testing approach.”
Why it works:
Experts have credibility. Their approval transfers to the product/idea.
2. Celebrity Social Proof
The principle:
We mimic the behavior of famous or popular people.
Examples:
Celebrity endorsements Influencer recommendations “Used by Google, Netflix, Uber”
Why it works:
We want to be like people we admire (even if their expertise is irrelevant).
3. User Social Proof
The principle:
We follow the crowd. Numbers create legitimacy.
Examples:
“Join 1 million users” “10,000 GitHub stars” “Most popular choice” “Trending on Twitter”
Why it works:
Large numbers suggest value. “This many people can’t be wrong.”
4. Friend Social Proof
The principle:
We trust recommendations from people like us.
Examples:
“Your friends John and Sarah like this” “3 developers you follow use this tool” “People similar to you also bought…”
Why it works:
We trust people similar to us more than distant celebrities or crowds.
5. Certification Social Proof
The principle:
Official seals and certifications create trust.
Examples:
“SOC 2 Compliant” “GDPR Compliant” “Verified by Visa” “ISO Certified”
Why it works:
Authority figures have verified quality/safety.
Social Proof in Technology and Startups
Let me show you how this plays out in tech:
Example 1: The Framework Bandwagon
The pattern:
React gets popular → Everyone switches to React → More people switch because everyone’s switching.
It’s not because:
- People evaluated all frameworks objectively
- React is universally best for all use cases
- People independently concluded React was right for them
It’s because:
“Everyone’s using React. I should too.”
The social proof:
- GitHub stars (user social proof)
- Used by Facebook, Airbnb, Netflix (celebrity social proof)
- Recommended by Kent C. Dodds, Dan Abramov (expert social proof)
Result:
React becomes default choice, often without evaluation.
Sometimes this is fine:
React is good. Following the crowd worked.
Sometimes it’s not:
Your use case might be better served by Vue, Svelte, or even vanilla JS.
But social proof prevented you from finding out.
Example 2: The GitHub Stars Trap
The scenario:
You’re choosing between two libraries:
Library A:
- 50,000 GitHub stars
- Last commit: 6 months ago
- 400 open issues
- Okay documentation
Library B:
- 500 GitHub stars
- Last commit: yesterday
- 10 open issues
- Excellent documentation
Social proof says: Choose A (50k stars!)
Rational analysis says: Maybe B (actively maintained, responsive, good docs)
What most people choose: A
Why?
Social proof. 50k people can’t be wrong.
Reality:
Library A got stars years ago. It’s now abandoned. Those 50k people aren’t necessarily using it anymore.
Library B is better, but social proof blinds you to it.
Example 3: The “Trending on Hacker News” Effect
The pattern:
Article hits Hacker News frontpage → Everyone reads it → Everyone now “knows” the take is correct.
Example:
“Why [X framework] is bad” gets 500 upvotes.
What happens:
People who’ve never used X now believe it’s bad.
Why?
Social proof. “500 developers upvoted this. They must be right.”
The problem:
Maybe the article is biased, wrong, or applies to specific edge cases that don’t apply to you.
But social proof makes you accept it without critical thinking.
Example 4: The “Everyone’s Building With X” Phenomenon
The pattern:
Tech Twitter: “Everyone’s building with Supabase now!”
Reality: A vocal minority is building with Supabase. Most people are still using whatever they were using before.
But social proof creates:
FOMO: “Am I behind if I’m not using Supabase?”
Bandwagon: “I should switch to Supabase because everyone else is.”
Result:
People switch tools not because they have a problem to solve, but because of social proof.
Example 5: The Testimonial Overload
SaaS landing pages in 2024:
“Join 100,000+ teams” “Trusted by Google, Amazon, Microsoft” “4.9 stars from 10,000 reviews” “As seen in: Forbes, TechCrunch, WSJ”
Why it’s everywhere:
Because it works. Social proof dramatically increases conversions.
The problem for users:
You’re making decisions based on what others did, not what’s right for you.
When Social Proof Leads You Astray
Social proof isn’t always reliable:
Case 1: The Crowd Is Wrong
Example:
Everyone’s buying a hyped tech stock.
Social proof says: “Everyone’s buying. I should too!”
Reality: It’s a bubble. The crowd is creating the very thing that will pop.
Historical examples:
- Dot-com bubble (everyone invested in any company with “.com”)
- Crypto hype cycles (everyone buying at peak)
- NFT mania (everyone minting JPEGs)
The lesson:
The crowd can be collectively wrong.
Case 2: The Crowd Isn’t You
Example:
“Most popular choice” on a SaaS pricing page.
Social proof says: Choose the popular one.
Reality:
- Most users might be enterprises. You’re a solo developer.
- Most users might need features you don’t.
- Most users might have different budgets.
What’s popular for “most people” might be wrong for you.
Case 3: Manufactured Social Proof
The dark pattern:
Companies fake social proof.
Examples:
- Fake testimonials
- Inflated user counts (“Join 1 million users” when they have 10k)
- Fake scarcity (“Only 3 spots left!”)
- Fake urgency (“27 people viewing this now”)
- Buying GitHub stars, Twitter followers, reviews
The problem:
You’re making decisions based on fabricated evidence.
Case 4: Outdated Social Proof
Example:
A tool has 100k users.
Hidden context:
- 90k are inactive accounts from years ago
- The tool is now abandoned
- Better alternatives exist
But the “100k users” number creates social proof that’s no longer valid.
Case 5: The Loudest Voice Isn’t the Majority
Social media distortion:
10 people tweeting passionately about something creates the illusion of consensus.
Reality:
10 people ≠ everyone
But social proof makes it FEEL like everyone agrees.
Example:
“Everyone’s leaving X for Y!”
Reality: 20 vocal people are leaving. 10,000 quiet people are staying.
The Cost of Following the Crowd
Cost 1: Suboptimal Decisions
Following the crowd means:
You choose what’s popular, not what’s optimal for your specific needs.
Example:
Everyone uses microservices → You use microservices → Your small team drowns in complexity.
Better choice: Monolith (for your team size and context).
But social proof prevented you from considering it.
Cost 2: Wasted Resources
Following trends costs money and time.
Example:
- Rewriting in the “hot new language”
- Migrating to the “everyone’s using” platform
- Adopting the “future of development” tool
Result:
Months of migration. Minimal value gained. Could’ve spent that time on features.
Cost 3: Loss of Critical Thinking
The habit:
If you always follow the crowd, you stop thinking for yourself.
The consequence:
You become dependent on others’ validation for decisions.
Career impact:
You never develop the skill of independent technical judgment.
Cost 4: Herd Behavior Crashes
What happens:
Everyone piles into the same thing → It becomes overvalued/overcrowded → Crash.
Tech examples:
- Every startup pivoting to crypto (2021)
- Every company adding “AI” to their product (2023)
- Everyone building the same type of SaaS
Individual example:
Everyone learns React → React developer market is saturated → Harder to get jobs.
Maybe learning something less popular would’ve been better.
How to Resist Social Proof
You can’t eliminate the bias, but you can make better decisions:
Strategy 1: Ask “Why?” Not “Who?”
Instead of: “How many people use this?”
Ask: “Why would this be good for MY specific situation?”
Example:
Social proof thinking: “50k stars on GitHub. I’ll use it.”
Critical thinking: “Does this library solve my specific problem? Does it have the features I need? Is it well-maintained?”
Strategy 2: Seek Disconfirming Evidence
The practice:
When everyone’s saying X is great, actively search for “Why X is bad.”
Example:
Everyone’s praising Tailwind.
Search for: “Tailwind criticisms,” “Tailwind cons,” “Why I stopped using Tailwind”
Goal:
Understand the full picture, not just the social proof.
Strategy 3: Test It Yourself
Don’t trust social proof. Trust your own experience.
Example:
“Everyone says Neovim is better than VS Code.”
Instead of accepting that: Use both for a week. Decide based on YOUR experience.
Your needs might be different from the crowd.
Strategy 4: Consider the Source
Not all social proof is equal.
Questions to ask:
- Who are these people? Are they similar to me?
- What’s their context? Enterprise vs. startup? Team vs. solo?
- When did they decide? Is this social proof current or outdated?
- Why did they choose it? Marketing, genuine value, or bandwagon?
Strategy 5: Use Social Proof as a Starting Point, Not a Decision
The reframe:
Social proof tells you what to INVESTIGATE, not what to CHOOSE.
Example:
“This has 10k stars. Worth investigating.”
Then: Actually investigate. Don’t just follow the crowd.
Strategy 6: Create Decision Criteria Before Exposure
The practice:
List your requirements BEFORE looking at options.
Example:
What I need in a database:
- Supports transactions
- Good Node.js library
- Scales to 100k users
- Easy local development
Then: Evaluate options against YOUR criteria, not popularity.
Strategy 7: The Contrarian Scan
The exercise:
When everyone’s doing X, ask: “What would happen if I did the opposite?”
Example:
Everyone’s learning React.
Contrarian: “What if I specialized in Vue or Svelte? Less competition, still valuable.”
Sometimes the contrarian play is better.
Strategy 8: Track Your Social Proof Decisions
The practice:
Write down decisions you made based on social proof.
Review later:
Were they good decisions?
Example log:
“Chose X because it had 50k stars. Result: Abandoned in 6 months, switched to Y.”
Over time, you’ll calibrate your trust in social proof.
Using Social Proof Ethically
If you’re building products, you can use social proof without manipulation:
Ethical Use 1: Real Numbers
Don’t: Inflate user counts, fake testimonials, buy stars.
Do: Share real numbers. If you have 1,000 users, say 1,000.
Why:
Authenticity builds trust. Getting caught lying destroys it.
Ethical Use 2: Context Matters
Don’t: “Used by thousands of companies!” (when they’re all using the free tier)
Do: “Used by 500 paying customers across 20 industries”
Why:
Gives real social proof with context.
Ethical Use 3: Specific Over Generic
Don’t: “Everyone loves us!”
Do: “Tesla, Airbnb, and 500 startups use our API”
Why:
Specific is credible. Generic is marketing fluff.
Ethical Use 4: User Stories Over Numbers
Better than: “10,000 users”
Try: “Here’s how Sarah used our tool to ship 3x faster”
Why:
Stories are more persuasive and provide actual information.
Ethical Use 5: Negative Social Proof Honesty
What not to hide:
If your tool isn’t good for certain use cases, say so.
Example:
“We’re great for small teams (50 of our 100 customers). If you’re an enterprise, you might need more features.”
Why:
Helps users make good decisions. Builds trust.
Real-World Social Proof Examples
The Good: Wikipedia
How they use it:
Citations provide expert social proof.
More editors reviewing an article = more trusted.
Why it works:
Transparent. Verifiable. Crowd-sourced validation.
The Bad: Fake Reviews
The problem:
Amazon, Yelp, Google Reviews flooded with fake reviews.
Why it’s bad:
Manufactured social proof. Users make bad decisions.
How to spot:
- Generic language
- Too many reviews in short time
- All 5-star or all 1-star
- Overly promotional
The Ugly: Bandwagon Crypto Scams
The pattern:
“Everyone’s buying this coin!”
Reality:
Early investors pump the price → Social proof kicks in → New buyers pile in → Early investors dump → Crash.
Social proof was weaponized for fraud.
The Wisdom vs. Madness of Crowds
Here’s the paradox:
Crowds can be wise (averaging estimates, Wikipedia, open source).
Crowds can be mad (bubbles, panics, fads).
When crowds are wise:
- Diverse, independent opinions aggregated
- No herding behavior
- Information is decentralized
When crowds are mad:
- People copying each other
- Herding behavior
- Information cascades (everyone follows early movers)
Your job:
Distinguish between the two.
Final Thoughts: Think for Yourself
Social proof is powerful because it’s usually right.
In evolutionary environments, following the crowd kept you alive.
But modern markets are different.
They’re filled with:
- Marketing
- Manipulation
- Manufactured trends
- Herd behavior
- Bubbles
The developers I respect most don’t ask “What’s everyone using?”
They ask:
- “What’s the right tool for THIS problem?”
- “What are the tradeoffs?”
- “Have I tested this myself?”
- “What do I actually need?”
They use social proof as one input, not the decision.
Some of my best decisions were contrarian:
- Using Postgres when everyone said “NoSQL is the future”
- Sticking with monoliths when everyone said “microservices”
- Using boring tech when everyone chased shiny tools
Some of my worst decisions were following the crowd:
- Building with MongoDB because “everyone uses it” (should’ve used Postgres)
- Learning Ruby because “everyone’s using Rails” (then demand crashed)
- Buying courses because of high enrollment numbers (never watched them)
The difference:
Good decisions came from independent thinking.
Bad decisions came from social proof.
So here’s my challenge:
Next time you see “1 million users,” “10k GitHub stars,” or “everyone’s using this,” pause.
Ask:
“Am I making this decision because it’s right for me, or because other people did it?”
If it’s the latter, think harder.
Because the crowd isn’t always wrong.
But they’re not always right either.
And your job is to figure out which is which.
What decisions have you made because of social proof? Were they good or bad? What would you have chosen if you’d ignored the crowd? Let me know.