Is media buying …dead?
If you've been in this industry long enough, you've asked yourself that. The version of the job that was just managing ad accounts? Gone years ago. What grows brands now is creative strategy and diversification - knowing exactly who you're talking to, building for every persona who needs the product, and measuring what actually happens. Here's my take, with the numbers to back it.
The ad account was never the job.
Every year something arrives that's supposed to end this industry - a new platform, an algorithm change, AI, audiences with shorter attention spans than ever. And every year the same version of media buying actually does die: the one where the job is just managing an ad account. That stopped being a rare, high-value skill a long time ago. If that's all a media buyer offers, they're right to be worried.
What survives is strategic media buying - producing content and assets that speak to the different personas who actually need the product, one at a time. Not chasing trends. Showing a brand's authenticity by naming a problem buyers already live with every day, and honestly showing them the product solves it. That's how you create demand instead of renting attention.
Take the comfort-footwear brand I ran for three years. Who would have thought a summer thong would become something people collect in every colour? Sixty to seventy percent of its buyers are women 35+, many living with flat feet or plantar fasciitis - and the account grew by speaking to each persona differently: pregnant women, new moms, the pilates crowd, 40+ customers, whitelisting partnerships, even celebrity paparazzi moments. And never on platform metrics alone - every scaling decision was read against real touchpoints and attribution windows, because people don't convert the moment they first see an ad.
Or the shapewear brand that grew +161% in a year on a boutique budget. The strategy wasn't a hack. It was helping women feel seen and accepting of their bodies instead of ashamed of them - bodies change through pregnancy, postpartum and ordinary life, and this brand set out to redefine the category's expectations while fixing everything women hate about shapewear: the rolling down, the digging in, the discomfort. The creative stayed authentic instead of chasing trends. That's why it lasted.
Representation that lasts.
That's what I buy media for. The case studies below are the receipts.
Four accounts. Real numbers.
Every figure on this site comes straight from ad-account and store reports. Pick a case study.
Comfort Footwear Brand
Shapewear Brand
Amazon Ads Program
Event Ticketing
Hi, I'm Achi.
I'll keep this short - if you read my take above, you know I respect your attention span. 🙂 The old me would have said "Media Buyer" or "Paid Social Specialist." The job got bigger than that, and so did I.
Before any of this, I tried to become a flight attendant - eight times. It never happened, and I'm glad. I went remote before remote was normal: cold-calling, customer service, booking events for US clients - until I met paid media and fell in love. Everything I know is self-taught, sharpened on both the agency side and the brand side - and today that means running Meta, TikTok, Pinterest and Amazon in-house for an 8-figure brand.
Why am I looking for a new home? Sometimes you have to leave home to learn what's out there, grow, and keep learning. If what you've seen on this page feels like a fit - I'd love to find out.
Measurement, and the tools I build to protect it.
Two things decide whether a media buyer is worth their budget: whether they can tell what is actually working, and whether they can run a clean operation at scale. Here is how I do both.
Measurement
- Third-party attribution. I work in Northbeam alongside the native platforms, so channel performance is read against an independent source rather than each platform marking its own homework.
- Blended MER before channel ROAS. Total revenue ÷ total spend is the number that survives an attribution change. Channel ROAS tells me where to move budget; MER tells me whether the account is actually healthy.
- New-customer CAC, not just blended. Scaling on blended CAC hides the moment paid stops bringing anyone new.
- Contribution margin, not just revenue. A 3x ROAS on a product that barely clears COGS and shipping is a loss dressed as a win.
- Naming the ceiling. Case Study 01 documents where efficiency broke at record spend. Knowing when to stop scaling is measurement work too.
Automation I've built
- Live client reporting dashboards. Connect your Meta ad account through MCP and I build you a Claude-powered dashboard that reads it directly - spend, ROAS, MER and pacing on demand, instead of screenshots pasted into a weekly slide deck. Ask it a question, get an answer from your own data.
- Order intake → structured records. Web forms feed straight into order records, so nothing is retyped and nothing is lost between a customer paying and a supplier being told.
- Supplier order blocks, auto-generated. One block per attendee, produced in the supplier's own language - English or Chinese depending on who I'm buying from.
- Multi-currency pricing sheets. A supplier list in any of six currencies converts at the live rate and outputs two views: cost and margin for me, clean prices for customers.
- Customer confirmations in one voice. Templated so every buyer gets the same clear message, with no internal cost information ever leaking into a customer-facing note.
- Channel-tuned announcements. One inventory drop becomes a broadcast post, a short-form social post and a story version, each written to the platform rather than copy-pasted across them.
What my reporting actually looks like
A sample from the benchmark system I run for the footwear account - built on Northbeam data, refreshed daily, one view per market. Ad names and the brand are anonymized; the structure and thresholds are the real thing.
Performance vs Benchmark - USA
Footwear Brand · Meta · Northbeam Master TableBad <0.40 · >$174
Fires fast, catches disasters today.
Bad <0.72 · >$99
Where budget moves actually happen.
Bad <0.80 · >$87
The settled truth, once revenue matures.
| Ad (anonymized) | Spend | 1d ROAS | Grade | 7d ROAS | Grade | 30d ROAS | Matured |
|---|---|---|---|---|---|---|---|
| UGC video - restock push | $2,669 | 0.54 | Good | 0.66 | Bad | 0.66 | 98% |
| Whitelisted partnership video | $1,098 | 0.61 | Good | 1.08 | Good | 1.08 | 58% |
| Static - product flatlay | $1,140 | 0.55 | Good | 0.63 | Bad | 0.63 | 61% |
| UGC - creator testimonial | $722 | 0.45 | Medium | 0.75 | Medium | 0.75 | 87% |
| Micro-edit video test | $1,592 | 0.15 | Bad | 0.28 | Bad | 0.28 | 72% |
Every market earns its own thresholds from its own settled history - a "Good" in Canada is a different number from a "Good" in the US, because margins, AOV and shipping differ. One global ROAS target across markets is how budgets get wasted politely.
A media buyer who can build their own tooling ships faster and depends on fewer people. Everything here is work I do myself - the operational automations run my own ticketing venture daily.
- Channel ad revenue = daily spend × daily platform-reported ROAS, summed by month. Attribution is last-click per platform.
- "Total sales" = Shopify total sales + Amazon total sales (Amazon includes organic - Amazon Ads launched Feb 2024).
- Blended ROAS = total sales ÷ total ad spend across the four channels shown. Google/other channels also ran and are excluded from this case study, so blended figures here are conservative views of the channels I managed.
- AUS figures are AUD; USA figures are USD. They are never mixed or converted.
- The brand is anonymized; data is shared in aggregate with permission. Screenshots have identifiers removed.
- Case Study 04 is a personal venture I operate, shown unnamed. Order counts are exact; average order value covers the 113 of 168 orders with a logged amount. No customer information is published.
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createwithachi@gmail.com