Nerds and sales = better sales on autopilot

Hacker News

We’re 4 nerds that love to geek out about tech, sales, marketing, growing startups, products and automation. Also, we’re not exactly salespeople (although we do know a bunch and have healthy experience) Long story short. We saw old-school outbound sales playbooks fall apart (at our previous companies). We were advised and coached by a guy who put in place a new engineering-focus automated sales approach at some bigger SaaS brands (you’ve probably heard of). We implemented an automated outbound program that produced better results for less headache (but it was a challenge to get it done due to politics). And thought why don’t we offer this to other startups? That’s how atom8 was born. Feedback welcome.

Visit product View on Hacker NewsJun 29, 2023

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

93%93% 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: new · Missing: mac, agents, macos

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

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

38%38% 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

35%35% 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 · Missing: mobile apps, ios, personal

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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