Stamperly

Stamperly

TrustMRR

Digital loyalty cards that live in Apple Wallet and Google Wallet. Cafes, salons and barbershops launch a branded stamp card in minutes — no app to build, nothing for customers to download. Scan a QR

Digital loyalty cards that live in Apple Wallet and Google Wallet. Cafes, salons and barbershops launch a branded stamp card in minutes — no app to build, nothing for customers to download. Scan a QR code to give stamps. Bring people back with push notifications, broadcasts and automations, and see who your regulars actually are. Free up to 20 customers, from $12/month after.

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Actual performance

2customers
$23MRR/mo
Did not reach leaderboard

Traction signals

Domain Rating1
MRR growth 30d+93.0%

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: month, google · Missing: mobile apps, ios, personal
57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: apple, google, code · Missing: mac, agents, macos
37%37% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
26%26% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
18%18% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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