Be 10x more efficient prospecting leads

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Hi HN! We’re Esteban and Juan, co-founders of MegaBoost. Check us out at https://megaboost.io/ We have built MegaBoost because we identified that the most painful part of a B2B sales process is the very first step: Obtaining high-quality leads. When we had our previous startup, I was taking at least 8 hours to build a high-quality 100 contact email list. That’s why we decided to automate this. We’re now being used by YC companies. Our previous startup was in enterprise cybersecurity, and actually won a Pioneer tournament thanks to that. We are different from Hunter, Clearbit Connect, etc. because: 1. We give you all the data needed to send customized messages at scale, which is what increases your campaign’s response rate. Unlike our competition we don’t just give you their email, company, and name; we also give you the person’s position and even a customized ice breaker. 2. We only include verified emails on our campaigns, and can verify them with a 98% accuracy. You won’t be sending emails to a catch-all address. 3. We do the entire job for you. We source companies according to the description you give us of your customer segmentation, and then give you the champion you’re looking for at those companies. Please register and give us your feedback.

Visit product View on Hacker NewsDec 23, 2019

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

95%95% 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: email · Missing: mac, agents, macos

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, 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.

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 · Missing: arr, mrr, revenue

19%19% 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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