FeedIQ – Create and schedule content on Twitter and Mastodon

Hacker News

Hello, I have created a social content scheduler for Twitter and Mastodon that allows you to manage multiple social accounts from a single place. Here's what it offers: - An intuitive platform for creating content - The ability to create weekly time slots for posting your content. For example, if you regularly post on Monday mornings at 10 am and 4 pm, you can create these slots and simply add content to your queue. - Tools to assist you in writing your content, including AI assistance, polls, symbols, and a gradient background generator. - The option to connect multiple Mastodon accounts into a single queue. - 7-day analytics to track the performance of your accounts. - Auto-Retweet/Boosts feature that automatically retweet your posts 12 hours after posting and un-retweet them 12 hours later. This helps increase post visibility, especially when targeting multiple time zones. I would greatly appreciate your feedback to understand if you find value in this tool and your thoughts on the product/features. Thank you HN!

Visit product View on Hacker NewsMay 30, 2023

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1points

Did not reach leaderboard

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

85%85% 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: single · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, intuitive · Missing: plus, reviews, host

47%47% 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, including · Missing: https docs, excited, just released

26%26% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

18%18% 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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