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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.
How I Built a Model-Agnostic AI Development Setup in 2026
Earlier this year, the economics of AI compute changed. Major providers — Anthropic, OpenAI, Google — started adjusting pricing upward after years of subsidising adoption. The demand-side story is simple: inference capacity is not keeping pace with how fast developers are integrating these tools into their daily workflows. For anyone running a serious amount of AI-assisted work, the cost trajectory is no longer abstract. I run a web development agency, and I was coding against multiple AI providers daily: Claude Code for terminal and config work, GitHub Copilot inside the IDE, Codex CLI for secondary coding runs. When I sat down and calculated what that looked like at scale — input tokens from behavioral rules loaded on every session, MCP tool schemas injected into every context window, 8 servers active simultaneously when I only needed 1 — the waste was significant and entirely fixable. This post documents exactly what I built to address it: a model-agnostic AI setup where every provider operates from the same behavioral rules, token usage is deliberately managed, and switching models costs me thirty minutes rather than a full rewrite.
AI
Developer Tools
Productivity
Shipping a Google Ads Tab: How the Webfluentia Dashboard Brings All Client Data Under One Roof
Every client I work with has the same problem: their performance data lives in five different places. Google Ads is in one tab, GA4 is in another, the lead form submissions are somewhere else entirely, and organic rankings require yet another login. Piecing together a coherent picture of what's working means switching between tools, correlating data manually, and hoping nothing falls through the cracks. The Webfluentia dashboard at <a href="https://dashboard.webfluentia.agency">dashboard.webfluentia.agency</a> was built to fix that — a single multi-tenant platform where each client logs in and sees all their digital marketing data in one place. Last week I shipped the Google Ads tab, and the first client (KindChiro) synced their data on April 28, 2026. This post is about what that tab does, how it works technically, and where the whole system is heading.
Google Ads
Dashboard
Supabase