Booking Dentist
Connected Meta and Google spend to actual booked revenue for a dental booking platform.
I build the systems that turn traffic into revenue.
Thirty minutes. I go through your tracking, your funnel, and your attribution, and show you exactly where revenue is leaking.
Go-to-Market Engineer
I build the systems that turn traffic into revenue.
Most growth problems are not creative problems. They are engineering problems wearing a marketing costume: broken attribution, funnels nobody instrumented, manual work that should have been automated a year ago. I find them and I build the fix.
Free · 30 minutes · no pitch deck
3.9x
Return on tracked ad spend (€34K in, €135K out)
+255%
Revenue growth for a DTC storefront
126K
Organic clicks driven from 14M impressions
Software Engineer @ Microsoft
Azure, distributed systems
Marketers can't ship it. Engineers don't own the number.
Growth stalls in the gap between the people who know what to build and the people who can actually build it. Agencies hand you a strategy deck and no implementation. Dev shops ship a ticket and never ask whether it moved revenue. I sit in the middle, and I own the outcome.
The usual setup
- A strategy deck with no one to implement it
- Tracking that was 'set up once' and silently broke months ago
- Reports that show traffic, never revenue
- The team doing by hand what a script should do nightly
Working with me
- Systems that ship, not slides
- Attribution you can audit, from first click to closed revenue
- Every experiment instrumented before it launches
- The repetitive work automated and out of your team's hands
If you're spending on acquisition and can't trace it to revenue, that's the problem I solve, whether revenue means a closed-won deal or a repeat purchase.
What I build
Four systems. They compound: the data layer makes the experiments honest, and the automation makes the wins repeatable.
Revenue Attribution & Data Pipelines
Server-side tracking, clean event schemas, and warehouse pipelines that survive ad blockers and iOS. GA4, GTM, BigQuery, Looker.
- B2B: ad click → lead → closed-won, stitched through the CRM
- Ecommerce: campaign → first purchase → repeat LTV in one model
AI Agents & Internal GTM Tools
Custom tooling for the work your team does by hand: lead research and scoring, enrichment, routing, and internal dashboards that answer questions without a data request.
- B2B: agents that research and score inbound leads before a rep opens them
- Ecommerce: automated product and creative reporting pushed to the team daily
Landing Pages, Funnels & CRO
Fast, instrumented pages built to be tested. Real experiment infrastructure, so a result means something instead of starting an argument.
- B2B: demo and trial flows rebuilt around qualification, not just volume
- Ecommerce: PDP and checkout paths tested against revenue per visitor
Paid + Organic Acquisition
Meta and Google campaigns, SEO, and content, all run against the revenue data rather than platform-reported conversions.
- B2B: spend steered by pipeline quality instead of raw lead count
- Ecommerce: scaling decisions made on contribution margin, not ROAS alone
The GTM engineering loop
The same loop I use on production systems, pointed at revenue. Nothing gets optimized before it gets measured.
- 01
Instrument
Get the data layer honest first. If the numbers are wrong, every decision after this one is a guess.
- 02
Diagnose
Find where revenue actually leaks. It is rarely where the dashboard says it is.
- 03
Build
Ship the fix: a pipeline, a page, an agent, a campaign. Whatever the constraint turns out to be.
- 04
Test
Validate against revenue, not proxies. Kill what loses without negotiating with it.
- 05
Scale
Automate what worked so the gain holds without anyone babysitting it.
The stack
A working knowledge of all of it is what makes the systems fit together instead of merely coexisting.
Data & Attribution
GA4Google Tag ManagerServer-side trackingBigQueryLooker StudioMeta CAPISQL
Acquisition
Meta AdsGoogle AdsSEOGoogle Search ConsoleContent strategyA/B testing
Build
TypeScriptNext.jsReactNode.jsGoPostgreSQLVercel
AI & Automation
LLM agentsWorkflow automationWebhooks & integrationsPythonScheduled pipelines
Selected work
Different businesses, same pattern: instrument the money, then build against what the data actually says.
Passionista.rs
3.9x return on tracked ad spend and 255% revenue growth for a multi-market Shopify brand.
eskuter.rs
Lead-generation site and booking flow for a premium electric moped brand.
Who you'd be working with
I'm Jovan. I'm a software engineer at Microsoft working on Azure's distributed systems, and I've spent the last several years building growth systems for startups, ecommerce brands, and my own products.
The engineering came first. Distributed systems, data pipelines, monitoring, the work of making complicated things observable and reliable. Then I started launching my own products and ran straight into the part nobody warns engineers about: building the thing is maybe a third of the job. Distribution is the rest.
So I learned that half properly: paid acquisition, SEO, attribution, conversion, offer design. Most of my own products failed. That turned out to be the useful part, because failing at distribution with your own money teaches you what an agency retainer never will.
What I do now is the combination. I can instrument the funnel, read the data honestly, build the fix, and ship it to production myself. No handoff between the person who spots the problem and the person who can solve it.
Most people selling growth can't build. Most people who can build don't own the revenue number. The overlap is where the leverage is.
GTM Teardown · Free · 30 minutes
Find out where your revenue is leaking
Thirty minutes. I go through your tracking, your funnel, and your attribution, and show you exactly where revenue is leaking.
- Where your tracking lies to you: the attribution gaps and broken events hiding your real numbers
- Where revenue leaks in the funnel: the steps quietly costing you conversions
- What I'd build first: the single highest-leverage system, and the lift to expect from it