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Media Buying
Your ads, placed where your customers actually look. I manage campaigns across Google, Meta, and display networks — turning ad spend into measurable revenue, not just impressions.
I'm Chris de Gruijter, a Data-Driven Digital Marketing Specialist
I turn data into decisions and campaigns into revenue. With 22 years in digital marketing — from managing MYR 150K+ monthly ad budgets for insurance giants to raising MYR 7 million for social causes — I've learned that great marketing lives at the intersection of analytical rigor and creative instinct. I build strategies grounded in real numbers, not hunches.
222222
Years of experience
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Conversion Optimization
More conversions from the traffic you already have. I analyze your funnel, test what works, and fix what doesn't — because driving traffic to a leaky bucket is just expensive water play.
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Lead Generation
Qualified leads that actually pick up the phone. Using AI-powered targeting and proven nurture sequences, I build pipelines that fill your CRM with prospects ready to buy — not just browse.
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Business Development
New markets, strategic partnerships, and revenue channels you haven't tapped yet. I help you identify growth opportunities and build the relationships that turn them into real business.
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Data Analytics
Dashboards that tell you what to do, not just what happened. I turn your raw data into clear, actionable insights — so every marketing decision is backed by evidence, not guesswork.
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Development & Scripting
Custom tools that save hours, not create headaches. From marketing automation scripts to full web applications, I build solutions that make your processes faster and your team more productive.
SEO at Scale: My Keyword Research Methodology and the Systems That Run It
SEO at scale is not about one keyword. It's about discovering thousands of them, figuring out which ones actually matter, and turning that pile of search demand into a content pipeline without drowning in spreadsheets. The hard part was never finding keywords — any tool spits out tens of thousands. The hard part is classification: knowing which 200 of those 15,000 terms translate into revenue, which 75 topic groups deserve a page, and which 8,000 are retailer noise you should never look at again. This is the methodology I use to do exactly that — both for agency clients through Webfluentia and on freelance engagements outside the agency — and the engineering that makes it repeatable. I'll walk through how raw discovery becomes a classified, scored dataset, how that dataset feeds both content generation and the optimisation of existing pages across whole clusters, and the technology layer underneath it all: MCP servers, AI agents, multi-tenant dashboards with client-scoped auth, and the regression contracts that stop an SEO change from quietly breaking a site.
SEO
Keyword Research
AI Agents
Building a Content Powerhouse: How I Turned One Client Project Into a Cross-Workspace Production System
The first time I batched social posts for a client I treated it like a one-off. Sixteen posts for a healthcare client, mostly ImageMagick scripts and Higgsfield prompts wired together with bash. It worked well enough to roughly double a small monthly Google Ads engagement into a larger growth package, which got my attention. If a duct-taped Friday afternoon could do that, what would a proper system do? This post is the build log for what that proper system turned into. I called it the Content Powerhouse — partly tongue-in-cheek, partly because that's genuinely what it has become. It sits at <code>/Projects/Content</code> on my machine, it serves every agency client, my personal projects and my freelance clients from the same toolchain, and it has reshaped how I think about content production more than any single piece of AI tooling I've adopted in the last two years.
Content Systems
AI Automation
Workflow