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I made a AI using GPT-4o to do any kind of Marketing.

Hacker News

I made a AI using GPT-4o to do any kind of Marketing.

Hey HN, A few weeks ago I realized that marketing is a very tedious task with being as costly as it can be. But if not done correctly, it will become boring and annoying over some time. So, I decided to merge GPT-4o with some of the marketing sites to create a single site (smstactic.com) that uses AI to do marketing using a total 7 marketing channels that range: SMS, Telemarketing, Email, WhatsApp, SEO, Google or Facebook Ads, Promo through content creators. It saves a lot of time and can get up to 2-3 times more speed, accuracy, and efficiency than Traditional marketing. Akshansh

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Actual performance

2points
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Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
91%91% 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: google, email, single · Missing: mac, agents, macos
73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: google · Missing: mobile apps, ios, personal
56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
27%27% 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
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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