Hi, my name is Maciej
I work on boosting growth for B2B and startup teams. I do practical AI automation for enhancing and streamline campaign and reporting workflows. Got extensive experience working with multiple ad platforms and marketing tools - worked with SaaS products and hype brands.
.my_work
Selected Case Studies
Request full breakdown →Marketing
Google Ads growth for NordPass
Built B2B search and landing workflows optimized for pipeline quality and customer value, not just headline volume.
View Project →Side Quests
Paid + ecommerce operating model improvements
Connected channel execution, store operations, and automation loops to shorten feedback cycles and improve decision speed.
View Project →AI Projects
Internal AI assistant for repetitive production tasks
Automated repetitive content and ops tasks with a lightweight workflow, cutting turnaround time significantly.
View Project →My process is straightforward: audit performance data, define clear goals, execute with structure, automate repeatable work, and scale only where results support it.
I work across different business types - from startups to more established teams. The focus is always the same: practical marketing that improves results, avoiding unnecessary complexity, overhead and overspend. I bring 8 years of digital marketing experience across agencies, startups, and in-house teams.
The day-to-day work includes campaign setup, channel execution, content planning, and AI workflows for optimization, research, and reporting.
View Approach →Review full performance data, define clear goals, and agree what marketing should achieve before deciding next steps. Every decision starts from actual numbers.
Build campaigns end to end and run channel execution. Plan landing pages and requirements, then brief design/content teams on what needs to be included. If needed, I can also create the content myself. Copy, landing pages, graphic design.
Add automation for campaign optimization support, ongoing market research, and data gathering/analysis so adjustments happen faster and with less manual overhead.
Scale only where the data proves it makes sense. Double down on winners, stop what underperforms, and keep iterating.