Country Performance Analysis (SSF)

Problem

Budget allocation for SSF's Meta campaigns depended on knowing which countries actually generate revenue — hundreds of raw transaction rows, and no way to see it by country, by time period, or by trend. Every time I needed to decide where ad money should go, I was starting from scratch with raw data. There was no single place to answer the one question that drives spend: which countries are worth paying for right now, and which are dropping off?

Old Way

Manually. Pulling the payment data, exporting it, sorting countries by hand in Excel, summing revenue, eyeballing which markets looked strong, and rebuilding the whole thing every time I wanted a fresh view or a different time window. A "last 3 months vs last month" comparison meant redoing the sort entirely. It was slow, repetitive, error-prone, and stale the moment I finished it — by the next day, the numbers were already outdated.

New Method

I built a live, self-updating Country Performance dashboard (a Google Apps Script web app) that reads directly from "Doin Tech Payment (2026)"—combines them into one clean dataset, and presents everything that actually drives budget decisions: 1. Full country ranking by revenue with sale count, average order value, and revenue share — every country, live-ranked, no manual sorting. 2. Single-country revenue trend over time (monthly), with a chart, a table, and month-on-month change — pick any country instantly. 3. Top 5/10 country trends overlaid, with a colour-coded table (green = growth, red = decline) so fading markets are visible at a glance. 4. 4-tier budget allocation model — countries bucketed into tiers by revenue, very-low earners auto-excluded from ad spend, and the monthly budget split across tiers automatically by their earning share. 5. Every view filters by period — all time, 6 / 3 / 2 months, last month, this month — recalculated instantly in the browser, no waiting. 6. Raw country codes are translated to full names, blank rows are dropped, and a Refresh button pulls the latest sales on demand. It's shareable with the whole team via a single link. The key shift: the analysis is no longer something I do — it's something that's simply there, accurate to the latest sale, the moment anyone opens it.

Impact

1. Time saved: Building this country revenue breakdown manually used to take me 2–3 full days each time — pulling the payment data, cleaning it, sorting countries, summing revenue, and rebuilding trend comparisons. And it wasn't once: I had to redo or update it 2–3 times every month, timed around campaign launches, so I was always working off fresh numbers. That's potentially a week or more of work per month gone entirely — the dashboard is now always current, with zero rebuild time. 2. Errors avoided: No more manual sorting mistakes, miscounted countries from blank rows, or stale figures. Budget decisions now rest on live, verified revenue data straight from the payment sheet. 3. Stress reduced: No scramble to rebuild the view before every allocation decision. One link, always ready. 4. Growth accelerated: Budget now flows to genuinely high-performing markets and away from low/declining ones, tier by tier — directly improving return on ad spend. Spotting a country's revenue drop early (via the colour-coded trend) means catching fading markets before they waste spend.