RankWorker
AI SEO tool to grow organic traffic with content on autopilot.
AI & Machine Learning·Productivity·Marketing
1 person waiting for launch day
About
RankWorker is an AI-powered SEO content tool designed to help website owners grow their organic traffic from search engines and AI platforms without turning content creation into a second job. The platform automates the entire SEO workflow, from AI-assisted onboarding and competitor research to keyword prioritization, content planning, and article generation.
Built for busy founders and teams, RankWorker analyzes your website to understand your brand context, target audience, and positioning so that every generated draft aligns with your voice. Users can review monthly publishing plans, check article metadata and Markdown outputs, and maintain full control over their scheduling and custom instructions before publication.
What sets RankWorker apart is its closed-loop workflow combined with robust publishing integrations. You can publish content effortlessly through WordPress, Next.js, a Direct API, secure webhooks, IndexNow for search engine notifications, or an MCP server to operate the tool directly from your favorite AI agent.
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FounderPlaybooks.
What other founders did to grow.
2722 dispatches from hundreds of founders, pulled from the week's best podcasts.
We ask people in onboarding where they came from and we found that to be actually the most reliable way of doing attribution. At the end of the day just asking people where they heard about us — if they say Facebook it's one thing, word of mouth something else.
Simple Where-Did-You-Hear-About-Us Survey Beats Fancy Attribution Software
Opal tried multiple attribution platforms but found a direct onboarding survey question the most actionable signal. At seven people there's no bandwidth to act on granular campaign-level data anyway — knowing that most conversions come from Facebook vs. word of mouth is enough to allocate resources. The dumbest measurement is often the most reliable and the most actionable.
The onboarding is quite long The goal is to kind of make the user feel it's personalized So a couple of questions about sensitive skin wrinkles what makeup look you like what's your skin tone and these are all used to get the actual results and then we do ask to leave a rating a review Usually they leave a fivestar review
Use A Long Personalised Quiz With A Mid-Flow Rating Prompt To Stack Five-Star Reviews
Glow Up intentionally uses a long onboarding quiz (sensitive skin, wrinkles, preferred looks, skin tone) so users feel the result is personalized to them. Mid-onboarding — before showing results — the app prompts for a rating, which consistently lands five stars and pushes App Store ranking up. Effort before reward is the lever.
There's a play for whatever you're stuck on.
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