https://www.graphed.com/ - AI data analyst to build dashboard and get insights
In this episode, I chat with Jonathan, a rapidly rising expert on Twitter known for building and scaling AI-driven marketing automations using tools like n8n and custom API integrations. We explore the practical realities of "vibe marketing" automation beyond hype, revealing how real-world workflows are being constructed today and why true expertise in marketing is essential for effective automation. Listeners will gain insights into automating audience research, creative production, and ad performance analysis at scale, as well as actionable tips for getting started and leveraging AI tools to 10x their output.
Timestamps
(00:00) – Introduction to Jonathan and Marketing Automation The host introduces Jonathan and sets the stage for a discussion on modern marketing automation tools and why they’re currently so powerful.
(02:45) – Jonathan’s Background and Automation Journey Jonathan shares how he got into marketing automation, his paid ads background, and the evolution from manual work to automation.
(07:30) – Key Tools and Stack for Automation The host and Jonathan discuss their tech stacks, highlighting n8n, railway.com, and custom front-end interfaces to streamline automation.
(12:15) – Top Marketing Automation Workflows Jonathan outlines his most effective workflows: audience research, creative generation, and scaling marketing insights.
(18:00) – Audience Research Automation: Reddit Scraping and Analysis A deep dive into using n8n to scrape Reddit, filter and analyze discussions, and extract actionable marketing insights and customer language.
(25:40) – Twitter Insights Automation How Jonathan automates scraping Twitter for popular posts, identifying top-performing content and structuring it for ongoing content creation.
(31:10) – Creative Production Automation Jonathan explains workflows for bulk generating ad variations using OpenAI’s Image Gen API, including reference image analysis and prompt engineering.
(38:20) – Custom Front-End Interfaces for Workflows The pair discuss integrating user-friendly front-end UIs (using Lovable or Bolt) with n8n backend automations for client and team use.
(44:50) – Automating Ad Performance Analysis Jonathan describes a flow for pulling and analyzing Facebook Ads data, using sub-agents for performance analysis, deep research, and new ad creation.
(51:10) – Video Ad Automation and Future Trends A look at how video ad automation is evolving and the current limitations and opportunities, including upcoming tools like Google Veo 3.
(56:40) – Speeding Up Workflow Creation with Perplexity and Claude The host and Jonathan discuss using AI (Perplexity, Claude 4) to generate n8n workflow JSON, streamlining the automation development process.
Key Points
- Expertise in Marketing is Essential for Automation: To automate marketing workflows effectively, you need a deep understanding of marketing processes themselves. Only then can you define, script, and automate successful campaigns[1].
- Automating Audience Research Drives Results: Bulk scraping and analyzing platforms like Reddit and Twitter allow marketers to extract pain points, trigger events, and customer language at scale, informing ad copy and creative direction.
- Creative Volume is Game-Changing: Automation tools like OpenAI’s Image Gen API enable the generation of hundreds of ad variations, feeding algorithms for higher performance and lower costs.
- Custom Front-Ends Improve Workflow Accessibility: Building user-friendly interfaces (using tools like Lovable or Bolt) for complex n8n automations makes them accessible to non-technical team members and clients.
- AI Accelerates Workflow Development: Using AI tools like Perplexity and Claude to generate n8n workflow JSON reduces the time and technical skill required to build sophisticated automations.
- Human-in-the-Loop Remains Critical: While automation handles the heavy lifting, human oversight is still needed for nuanced analysis, curation, and final ad selection.
Notable Quotes
- Jonathan: “You have to be an expert at that thing to be able to go and actually build out these automations. But when you do that, you can automate 80% of the work that you previously were doing.”
- Jonathan: “I literally just tell Claude what I want to build, and then it maps it out for me. And then you kind of have a canvas that is like 60, 70, 80% there depending on the complexity.”
- Cody: “Your customers are your best advertisers, so taking their exact wording and phrases is for sure going to be an effective marketing strategy a lot of the time.”
Actionable Takeaways for Founders, Marketers, and Podcasters
- Start with a Core Marketing Process: Identify a repeatable marketing workflow you fully understand before attempting to automate it.
- Invest in Audience Research Automation: Use tools to scrape and analyze discussions on Reddit, Twitter, and other platforms to extract customer pain points and language for your messaging[2].
- Bulk Generate and Test Creatives: Leverage AI to produce hundreds of ad variations, enabling rapid testing and optimization of creative assets.
- Automate Performance Analysis: Implement workflows to automatically pull and analyze campaign performance data, allowing you to focus on strategy and execution[8].
- Simplify Tool Accessibility: Build custom UIs for your automation tools to make them accessible for your entire team, not just engineers.
- Accelerate Workflow Development: Use AI-powered tools like Perplexity and Claude to generate automation scripts and reduce development time.
Brought to you by
- TalentFiber – Hire top offshore engineers with US experience at half the cost of US hires. - talentfiber.com
Where to the find Guest:
- https://x.com/vibemarketer_
- https://linktr.ee/vibemarketer
Resources Mentioned
