AI

AI-Powered Client Acquisition for Web Designers

Hacker News

AI-Powered Client Acquisition for Web Designers

Hi HN community, I’m Thijs, a 23-year-old master’s student in Data Science at Utrecht University. I’m excited to share Leadodo, my AI-powered tool designed to help web designers find new clients effortlessly. Leadodo started as my thesis project and has now evolved into a full-fledged startup. What is Leadodo? Leadodo leverages advanced AI technology to analyze over 10,000 websites, identifying businesses that need a website overhaul. Our AI evaluates each site's design, functionality, user experience, and overall online presence, providing web designers with a curated list of high-quality leads. Key Features: • 10,000 Websites Analyzed: Leadodo AI scans and evaluates thousands of websites across various industries. • Detailed Reports: Each potential client comes with a comprehensive report highlighting specific areas for improvement. • Personalized Emails: Tailored email templates for each identified lead, increasing the chances of a positive response. • Proven Results: Test cases have shown an average acquisition of 7-12 new clients. Why Leadodo? Finding quality clients in the web design industry can be as challenging as creating stunning websites. Leadodo aims to change that by automating and optimizing the client acquisition process, allowing designers to focus on what they do best: designing amazing websites. Why I Built This: I’ve been in the web design industry since 2019, running my own small web design business. I found that finding clients was often more difficult and time-consuming than building the websites themselves. Combining my experience with my studies in Data Science, I developed Leadodo to solve this problem for web designers everywhere. I’d love to hear your thoughts and answer any questions you might have! Thanks for your time, Thijs

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Actual performance

3points
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
98%98% 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
76%76% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, new, email · Missing: mac, agents, macos
47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: excited, lua, ide · Missing: https docs, just released, exist
43%43% 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
9%9% 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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