Cliently – Find new leads. Close more deals. Automatically

Hacker News

Hey guys, Wanted to share the complete overhaul of the app we've been developing for the last several months. http://www.cliently.com After the initial launch targeted towards freelancers, we decided to go broader and add Automated Flows -- basically a relentless sales manager that will reach out to potential customers on your behalf via different channels. Right now we support twitter and email and you can add timed delays to your flow. We will be adding new channels for follow-up in the coming weeks. We've also added Instant Twitter Search -- search twitter like you would search google, the results pop-up instantly. It's great for trying different search queries to find more leads. Let us know what you think guys!

Visit product View on Hacker NewsApr 12, 2016

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

78%78% 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

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

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

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.

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.

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

35%35% 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

15%15% 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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