CrossFolio

TrustMRR

CrossFolio is a lightweight portfolio tracker for investors managing stocks across NYSE, NASDAQ and LSE. You enter your holdings, set a profit target, price target or stop loss per stock, and CrossFolio checks prices every 15 minutes during market hours and emails you when any of them trigger. No broker connection. No spreadsheets. Free to start.

Visit product View on TrustMRRMar 9, 2026SaaS Other B2C

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Actual performance

Did not reach leaderboard

Traction signals

Domain Rating1

Launch Intel predictions

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BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto

53%53% predicted probability of success on BetaList, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

46%46% 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

44%44% 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

42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

34%34% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: profit · Missing: arr, mrr, revenue

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: email · Missing: mac, agents, macos

8%8% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Correct prediction on native model

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