Long-form thinking,
written by operators.
We write because we have to think, and we publish because we think it might be useful. Essays as record of how we approach the work — not blog posts as content marketing. No 400-word listicles, no SEO filler. Things you might actually want to read.
Showing Measurement. Topic hubs above are the curated reading lists.
Recent essays.
Meta reporting beyond Ads Manager.
Meta’s in-platform ROAS is generous by design — attribution windows, view-through conversions, and blended prospecting all flatter it. How to build a reporting layer on a blended metric that reconciles against real revenue instead of taking Ads Manager at its word.
The measurement stack for high-spend advertisers.
At scale, measurement is not a dashboard — it is a layered system: clean signal into the platforms, a blended metric anchoring reality, and incrementality tests settling the questions attribution cannot. What the stack contains and why each layer earns its place.
Facebook Ads cost benchmarks in 2026 — and why they mislead.
Realistic 2026 ranges for Meta CPM, CPC, and CPA — presented with the caveats that make them usable. The real lesson is methodological: a benchmark is a distribution, not a target, and your own economics decide whether your cost is good.
SaaS marketing metrics that matter.
Median B2B SaaS CAC payback now sits around 15-16 months — a different world from the 12-month rule of thumb. The metrics that matter, current benchmark ranges, and how to derive paid media targets from them.
Incrementality testing: work out what your test can detect first.
Every attribution model is an allocation of credit among ads; none can tell you what would have happened without the ad. Only a controlled test can, but an underpowered test is worse than no test, because its nulls all point the same direction: toward "nothing is incremental". Here are the three designs a marketing team can run, and the arithmetic that tells you in advance which questions your data is capable of answering.
Profit on ad spend: bidding to margin, not revenue.
A 4x ROAS on a 15% margin product loses money. A 2.5x ROAS on a 70% margin product prints it. Revenue-based bidding cannot tell the difference, which means most accounts are systematically over-buying their worst economics. The fix is to bid to margin.
MER vs ROAS: the argument is a decoy.
Every version of this article tells you to stop trusting ROAS and start trusting MER. That advice is not wrong so much as beside the point: MER and blended ROAS are the same economics inverted, and neither is safer than the revenue figure you feed it. Here is the ladder that ranks your revenue sources by trustworthiness, the arithmetic that turns one week of data into three contradictory decisions, and how to set the floor from your own P&L.
Brand vs non-brand: the error that grows as you succeed.
Counting branded search as paid acquisition is the most common measurement error in paid search, and the usual account of it (that it inflates ROAS) understates the problem twice over. It makes every other figure in the account uninterpretable, and it is self-concealing: the error grows precisely as your non-paid marketing succeeds. Here is the full decomposition, why separation always leaks, and the cases where the split is honestly ambiguous.
Ecommerce unit economics: four numbers, one quantity.
Most scaling mistakes are made in the spreadsheet long before they reach the ad account. The reason is structural: CAC, LTV, payback window and MER are treated as four independent KPIs when they are four views of one quantity — the contribution margin a customer produces. Here is the full waterfall, the denominator error that makes CAC look half its real size, and why a business with textbook ratios can still run out of cash while scaling.
Google Ads metrics that lie to you.
CTR rewards clickbait, conversion rate punishes growth, impression share hides its own denominator, and platform ROAS grades its own homework. What each metric really measures and what to read instead.
Written by operators, not content teams.
One essay when we find something worth your time, from people running real accounts. How we research and correct this writing is set out in our editorial policy.
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