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CombatChurn – Cancellation flow builder for Stripe

Hacker News

CombatChurn – Cancellation flow builder for Stripe

Churn is a big problem for most SaaS, but most of it is easily preventable by offering alternative options. That's were CombatChurn comes in, it easily allows you to create churn reducing cancellations flows using our drag and drop editor. Offer exclusive deals to your customers, allow them to temporarily pause subscriptions or get in touch with you. We can't however stop every customer from churning, but we can help you prevent it from happing in the future. By giving you advanced insights in reasons why customers are churning to give you the possibility to fix those. CombatChurn is far from finished, I am planning to add more features around recapturing churned users and providing insights which customers are at-risk of churning. P.S. We have a special deal for launch day, 50% OFF the first year of Scale! Claim it before it expires.

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
81%81% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, stripe, using · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, 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
37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: exclusive, builder, users · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas, subscription · Missing: arr, mrr, revenue
32%32% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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