I built a platform to your improve efficiency and response times

Hacker News

I am excited to finally be launching PromptlyReply! I built PromptlyReply due to a pain point that I personally experienced. As a former customer service agent, I constantly faced the challenge of managing repetitive responses. As my list of pre-set messages grew, my efficiency and response times began taking a hit. I realized there had to be a better way, and that's how PromptlyReply was born! Key features: Categorise your messages Simply click the required message to copy the text to your clipboard Search through categories and messages to quickly find the correct message Copy history with filters to analyse trends Teams with shared categories and messages to maintain consistency across all employees Chrome extension for more convenient access Shoutout to Shipfast - This allowed me to quickly began working on the most important aspects of PromptlyReply. I would love to hear any feedback you have! https://promptlyreply.com/

Visit product View on Hacker NewsJul 20, 2024

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2points

Did not reach leaderboard

Launch Intel predictions

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

88%88% 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: agent · Missing: mac, agents, macos

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

AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews

58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, io · Missing: https docs, just released, exist

39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

34%34% 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

16%16% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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