HowsThisGoing – an AI based standup bot for Slack

Hacker News

Hey guys, I left my PM job in December to learn how to code. The plan, - Build something that "I" could build with my background (I haven't studied CS) - Something that already existed and I used so I didn't have to spend time finding PMF Over the past 4 months I've been building howsthisgoing.com (a standup bot for slack with AI summaries). My ex-employed signed up in May & I got another customer through a university batchmate sometime in June (the company he's working at). However, since then it's mostly been 0 new customers, I get roughly 6-10 views on my site daily. The bot and my offering is simple, - you can run standups & check-ins in Slack - cheaper than other alternatives out there - a few solid AI integrations (custom summary prompts etc.) There's also a free tier you could get started with for getting a taste of the software. ---------- Looking for tips on how to better acquire new users. I don't have a sales strategy at the moment but a few things I've been thinking of, - Launching on PH, Reddit, etc. (I feel I'm too early for this, my goal is to get to at least 10-15 paying customers before I do this so I have a simple testimonials section on my website) - Cold outreach on LinkedIn, Email etc.

Visit product View on Hacker NewsJul 13, 2024

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

87%87% 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: slack, user, new · Missing: mac, agents, macos

79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: month, users · Missing: mobile apps, ios, personal

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

51%51% 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: users · Missing: plus, platform, intuitive

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

27%27% 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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