Lead Marketing Analyst · Crypto · Cape Town
Every growth number is an estimate. My job is knowing how good it is.
I have spent eight years in crypto. I came in as a data analyst, found a paid media operation that nobody was running, and ended up owning both analytics and marketing operations at an exchange serving customers across Africa, Europe and Southeast Asia. My work sits where measurement, markets and growth overlap.
How I see the industry. These are the views I work from. Each one comes with how confident I am and the evidence that would make me drop it. A view you cannot lose is not worth much.
A crypto customer sees an ad on her phone, signs up a week later on a laptop, clears KYC three days after that and funds from her banking app. No click path survives that journey, and since the mobile privacy changes most of it is invisible anyway. I treat channel credit as a range: MMP data, holdout tests and media-mix models triangulated, with the uncertainty reported next to the number.
Clicks are cheap in Lagos, Nairobi and Lusaka. Funded, retained accounts are not. Whoever already owns the customer relationship and the payment rail (mobile money operators, banks, merchant networks) carries trust that paid media cannot buy. The best growth plan in these markets often looks more like a partnership strategy than a media plan.
Signups, deposits and volume move with the market far more than with any campaign. Bitcoin still trades as a macro asset alongside real yields, the dollar and ETF flows. I plan spend against that backdrop: lean in as liquidity improves, protect retention when it tightens, and never read a bull-market CPA as a channel win.
Most of the "this channel stopped working" debates I have investigated ended in the event pipeline: a redirect that fires a second page view, an SDK that double-counts installs, a consent setting that quietly drops a market. Audit the instrumentation before you judge the channel. It is slower and less fun, and it is usually where the answer is.
A single forecast in crypto gets anchored on, then embarrassed. I work in conditional branches instead: two to four scenarios, each with its assumptions written down and a set of observable tells that show which branch we are actually in. When a tell fires, the plan changes. More on how this works.
Exchange brands get cloned, impersonated in ads and buried under spam SEO. Users cannot tell the difference, so every scam spends the real brand's trust. Competitive intelligence in crypto has to watch bad actors as closely as competitors, and the response is part marketing, part security work.
Probabilistic attribution, incrementality testing, event taxonomy design and the plumbing between mobile measurement, CDP and warehouse.
Growth strategy across African, European and Southeast Asian markets, built around how payment rails, regulation and trust shape what actually works locally.
Tracking competitors, market structure and bad actors with passive methods: ad libraries, search footprints, product and pricing changes.
Paid media governance, budget pacing, campaign taxonomy, lifecycle messaging and the reporting that ties spend to funded accounts.
Personal project · Python
A market insights generator that pulls from FRED, yfinance, Farside ETF flows, DeFiLlama and exchange APIs. It produces a stance, an attention signal (QUIET, WATCH or BREAK) and the falsifiable tells behind each call. It runs on a written epistemics framework: scenarios over forecasts, assumptions stated, every claim checkable.
Analytics forensics
A newsroom article was reporting far more views than it could plausibly have had. Live, instrumented browser traces showed a CDN geo-detection redirect to a localised URL that fired a second page view inside the same session. The article was fine. The redirect was the problem.
Marketing operations
Joined as a data analyst and found paid media spending with no clear owner. Took it on and rebuilt it around measurement, so spend could be judged on funded accounts rather than clicks. That is how an analyst ended up running marketing operations.
Competitive intelligence
Traced a coordinated operation in Cape Town that combined spamdexed pages with what appeared to be a farm of Facebook community groups. Passive methods only, nothing that touched the operation's own systems.
Macro research
A daily briefing cadence through the 2026 US, Israel and Iran conflict, tracking Brent crude, Bitcoin, gold and real yields. Alongside it, a framework for South Africa's structural position on the Cape shipping route.
Joined crypto as an analyst: SQL, Python, dashboards and the questions nobody else had time to answer.
Found a neglected paid media operation and absorbed it. Learned growth from the spend side, with a measurement habit already in place.
Own analytics and marketing operations for an exchange across African, European and Southeast Asian markets.
Outside work I build things: a console-style strategy game in Python, audio tools in C++ and JUCE, and small utilities for tabletop games.
Happy to talk measurement, growth in emerging markets, or where crypto is heading.
The best way to reach me is on LinkedIn.
