Marketing analytics · Automation · AI
I turn complex data into clearer decisions through analytics, automation, and practical software solutions.
My work has evolved from data-quality tools and marketing dashboards to automated pipelines, analytics products, and AI-assisted workflows. Today I combine analytical thinking with AI tools to explore problems, build solutions, and move from insight to execution.
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The journey
I didn’t start out on a technical path. I studied Telecommunication and Informatics Business Management (MBTI) at Telkom University and interned at PT Telkom Indonesia.
Management was my major, but the IT side kept pulling me in. What I loved was how much easier a problem became once the right tool was in place. That curiosity has shaped every role since.
My first automation started with manual work.
Our QC team checked marketplace product data by hand. I introduced the team to data scraping, so we could collect and check listings automatically instead of one at a time.
I saw how one well-placed script could change what a whole team was able to do.
The QC work got noticed, and I moved into marketing technology full-time.
The work was client-based, so the data grew fast: from a single website to brands like BMW, Toyota, Astra Property and many more Astra companies. Each industry measured success differently, and I learned how metrics and workflows change from one business to the next.
This is where I brought Python into the team, which made our marketing reporting faster and more accurate.
Less about single tasks, more about the system.
As I became team lead, I focused more on workflows and automation: scaling what I had built and connecting more systems together, from attribution pipelines and GA4 and GTM measurement to full-funnel reporting.
I started thinking in workflows instead of tasks: how data enters, moves, and reaches the people who need it.
AI stopped being just a script helper.
It started supporting the analysis and the work itself, and I delivered several AI-powered projects in this period. I also moved to the product department, where I explored how AI could bring predictive analytics into the company’s dashboard product.
AI became part of how the work gets done, not only how the code gets written.
A client asked for me personally.
OLX Indonesia needed operational data automation, and Astra arranged my transfer there to support it. Today I work in Marketing Analytics and use agentic AI in my marketing work: agents that plan, execute and check multi-step analysis.
I’m moving from building individual solutions toward systems that carry the work forward.
I still start with the problem, work through the data, and check whether the result helps someone decide better. AI gave me a new way to approach that process. I started out searching Stack Overflow for answers. Today I feel fully enabled to build what I set out to solve.
Selected work
Ordered from most to least AI: an AI assistant for everyday work and AI-powered audience insight, then the data foundations underneath: unified analytics, marketing automation and CRM extraction at scale. Plus one side experiment.
Professional identity
I work at the intersection of data analytics, automation, and product thinking.
My background spans operational data quality, marketing measurement, data pipelines, business intelligence, and analytics products. I enjoy work that goes beyond explaining what happened: understanding why, building the tools to investigate it, and making the result easier to act on.
AI is becoming a more integrated part of how I work. It helps me explore approaches, support implementation, and experiment with agentic workflows. I see it as an extension of analytical judgment, never a substitute for understanding the problem or validating the result.
Turning business questions into measurable metrics, investigating performance, and communicating findings that support decisions.
Connecting data sources, standardising metrics, building repeatable pipelines, and reducing manual reporting.
Translating stakeholder needs into requirements, defining success measures, and building tools around the decisions people need to make.
Using AI tools in the development process and exploring agents that run structured, multi-step tasks with verification and human oversight.
My projects share one principle: removing friction between data, decisions and execution. I want to build systems that do more than collect data, so information is easier to access, insights are easier to generate, and repetitive work is easier to automate.
Contact
My work has moved from fixing data problems to building analytics systems, from reporting performance to thinking about the products around it, and now toward exploring how AI can support more of the analytical workflow.
If you’re working on a data, analytics, product, or AI-enabled business problem, I’d be glad to connect.