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Optiwing – Keyword Grouping and Other PAYG SEO Tools

Hacker News

Optiwing – Keyword Grouping and Other PAYG SEO Tools

What's up Hacker News, I built a keyword grouping tool as a developer managing my own websites' SEO, I found myself frustrated with expensive subscription based SEO tools that had lots of unnecessary features for my needs. So I made a simple tool for myself that grew into it's own product. Optiwing has tools for Keyword discovery, grouping, content briefing, SERP checking and SERP comparison. What I did different: Pay-as-you-go pricing with no subscriptions, Simple integrated workflow from keyword research to grouping, to content briefing, Large scale keyword grouping to identify which keywords can be targeted with a single piece of content using live Google search data for accuracy. I'd love feedback, especially from others managing their own SEO who find existing tools too expensive for their needs. Cheers

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
73%73% 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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
68%68% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: google, new, single · Missing: mac, agents, macos
56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, hacker news · Missing: https docs, excited, just released
28%28% 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 · Strong signals: subscription · Missing: arr, mrr, revenue
16%16% 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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