Easiest way to send lifecycle emails from your code

Hacker News

Hi HN, Would love some feedback on our service. Nudgespot(www.nudgespot.com/developers) makes it easy to send emails from your code. Instead of writing your email logic in your code, we ask you to send events to us, as you'd do with Mixpanel/GA. You can then configure emails as triggers from our dashboard. Benefits: * Flexibility in adding/modifying your emails without code changes * test out different schedule intervals, email messages * Add drip campaigns based on customer events - an "ordered" event is enough to send a transaction email, a feedback email and perhaps even a reminder email for a repeat purchase. What do you think about the service?

Visit product View on Hacker NewsMay 25, 2014

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, code · Missing: mac, agents, macos

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

55%55% 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 · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

17%17% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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