Waterbongo ✓
@waterbongo · California · joined 25 Nov 2025
Founder @tradeonpear
34 648Followers
28Following
3 882Posts total
75.6KViews on collected posts
Postingan terbaru
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Crypto volume is dying.
If you haven’t noticed it yet, you’re not paying enough attention.
A lot of that volume is moving toward betting platforms, prediction markets, and fantasy platforms.
Web3 loves speculation.
that’s one of the reasons you love memecoins so much.
But
5.9K views · 163 likes
· 6 reposts · 67 replies
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@waterbongo Prediction markets nailed the trading part. Making it fun to trade with other people feels like the missing piece
6 views · 1 likes
· 0 reposts · 0 replies
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@waterbongo social makes prediction markets way more sticky
21 views · 2 likes
· 0 reposts · 1 replies
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@waterbongo Prediction markets attract people who want to be publicly right, which is a different and often less sticky social dynamic. We love what you’re doing on Pear’s platform.
19 views · 1 likes
· 0 reposts · 1 replies
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prediction markets have a product problem.
nobody plays fantasy football because they love statistical modeling.
they play because their friends are in the league.
social layer is the product.
When I first used prediction market, i loved it because of the infinite markets
10.6K views · 172 likes
· 5 reposts · 68 replies
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a year ago you could say "prediction markets" in a room and get funded.
that time is long gone.
every investor conversation now ends the same way: launch, show us the data, then we'll talk.
honestly it's a good filter.
sorts people building a company from people
7.5K views · 178 likes
· 6 reposts · 72 replies
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I worked on the robotics team at NVIDIA.
left because i wanted to work for my own company instead of someone else's.
now i work 24/7 and answer to investors.
what an upgrade
7K views · 192 likes
· 24 reposts · 70 replies
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Join the waitlist → https://t.co/VReXThoCyk
Early access + cashback on every trade for life (only for pre-launchers).
See you inside.
1.6K views · 11 likes
· 2 reposts · 0 replies
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This isn't a "coming soon" promise.
It's live and tested:
→ $5,000+ in volume already
→ 10,000+ on the waitlist
→ 60,000+ tasks completed
Everyone who joins before launch gets first access + cashback from day one.
First come, better served 🍐
7/8 https://t.co/2WNdsFoyOs
1.7K views · 18 likes
· 0 reposts · 1 replies
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Oh, and Pear pays you to trade.
Every trade = cashback.
couple of taps and you're in... trading on best prediction markets platform.
6/8 https://t.co/J1eiCBdYPQ
1K views · 9 likes
· 1 reposts · 1 replies
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Every other tool for prediction markets is a desktop terminal built for whales.
Pear is built for your phone.
Polymarket + Kalshi + everything, all in one place.
One app to access every market.
Finally, entire portfolio on one screen.
4/8 https://t.co/GcJsdtJoAn
1.6K views · 10 likes
· 0 reposts · 1 replies
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And here's my favorite part:
you can actually see who's winning.
Real profiles with real leaderboards and real track records, all public.
When a top trader makes a move, you can copy it in one tap.
No more guessing and you stop being exit liquidity.
5/8 https://t.co/ModNADve
1.2K views · 10 likes
· 1 reposts · 1 replies
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I've put thousands of dollars through these platforms before I wrote a single line of code.
you can't fix a frustration you haven't lived.
I'm a builder at heart.
When something annoys me, I take it apart and rebuild it the way I want it.
Did it with my EV.
3/8 https://t.co
1.6K views · 12 likes
· 0 reposts · 1 replies
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0:25
It's 2026. Buying a token takes 10 seconds.
To place a prediction trade, I need my laptop, click through 7 screens, and patience of a monk.
Smartest idea in crypto is stuck inside cluckiest product on earth.
So, I built my own.
Meet @tradeonpear 🍐
1/8 https://t.co/PN5tE9Mb5
34.4K views · 472 likes
· 169 reposts · 56 replies
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that clunky experience actually costs money.
A WSJ analysis found 70% of people on prediction markets lose money.
Not because they're bad at prediction.
they're trading blindly.
Whether you've made 500 trades or quit after one confusing afternoon, you've felt it
2/8 https://
1.4K views · 16 likes
· 1 reposts · 1 replies
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Dibandingkan akun berukuran sama
8 postingan dari 90 hari terakhir, dibandingkan dengan rentang 10K–100K pengikut. tampil jauh melampaui audiensnya sendiri, dan audiens itu merespons.
Median tayangan2 971akun ini1 041median untuk 10K–100K
Jangkauan, %8.57%akun ini3.78%median untuk 10K–100K
Interaksi, %4.99%akun ini1.69%median untuk 10K–100K
| Metrik | Akun ini | Median untuk 10K–100K | Rasio |
|---|---|---|---|
| Median tayangan per postingan | 2 971 | 1 041 | 2.85× |
| Jangkauan (tayangan ÷ pengikut) | 8.57% | 3.78% | 2.27× |
| Tingkat interaksi | 4.99% | 1.69% | 2.96× |
Akun lain pada rentang ini → Bandingkan dengan akun lain → Bagaimana tolok ukur ini disusun →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
1.6K16 Jun
1.2K
1.6K
1K
1.7K
1.6K
1721 Jul
7K27 Aug
7.5K1 Sep
10.6K2 Sep
19
21
6
5.9K7 Sep
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.79%16 Jun
1.03%
0.67%
1.08%
1.12%
0.81%
5.88%21 Jul
4.09%27 Aug
3.42%1 Sep
2.31%2 Sep
10.53%
14.29%
16.67%
3.99%7 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.69%.
What the audience does
Likes68.4%1 268 in total
Reposts11.6%215 in total
Replies18.4%341 in total
Bookmarks1.6%30 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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