Sam Nouri
Founder, ADSRUNNER
Sam Nouri is a Google Ads and Meta ads specialist and the London-based founder of ADSRUNNER, a performance marketing agency that manages ad spend for ecommerce, SaaS, lead generation, and education brands across the UK and the US. He founded the agency in 2021 after more than a decade operating paid media accounts directly.
His work sits at the intersection of two jobs that are usually kept apart: running accounts and building the systems that run accounts. Rather than renting a stack of third-party tools, he led the build of ADSRUNNER’s own infrastructure — first-party tracking, a unified cross-platform data layer, multi-touch attribution, and AI agents that monitor every account continuously and propose changes for a human to approve.
He writes about the decisions that actually move accounts — measurement and attribution, account architecture, budget allocation, and the economics of scaling paid media profitably — and about where AI genuinely helps versus where it is marketing copy.
How to scale an ecommerce business.
Most scaling advice is a list of tactics with no diagnosis attached, which is why it so often fails: the tactic was fine, the constraint was somewhere else. This guide works the other way round: five constraints that cap ecommerce growth, how to tell which one is binding on your business right now, and what actually moves each.
Freelancer, expert, or agency: who should actually run your ads?
"Google Ads expert" and "Google Ads agency" are usually typed by the same person on the same afternoon, and they lead to very different places. Here is what each option is genuinely good at, the spend range where each stops making sense, and the failure mode specific to each.
Performance dropped: a systematic method for finding out why.
Performance drops trigger a predictable panic: bids get changed, campaigns get restructured, budgets get shuffled, all before anyone has established what actually happened. We work a fixed diagnostic order instead: measurement, market, platform mechanics, then the account. In that order, for a reason.
Server-side tracking and the Conversions API: a practical 2026 setup.
Server-side tracking is no longer optional. The browser pixel misses too much, and the gap is widening every year. This is a practical look at how Conversions API and Enhanced Conversions work, what a trustworthy setup looks like, and where implementations go wrong.
The first 90 days: how we approach a foundation rebuild.
The interesting work in paid media, the bid strategy and creative testing and audience expansion, only compounds once the foundations are right. So our first 90 days on any account are deliberately spent on the unglamorous work first. Here is the sequence.
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.
Why most Google Ads audits miss the real issue.
Most accounts we audit have great-looking dashboards and broken foundations. The interesting issues are never bidding strategy or keyword choice. They are upstream of those: in measurement, attribution, and architecture decisions made years ago and never revisited.
Attribution after iOS 14: what actually works.
Pixel attribution is not coming back, and the difficulty has moved on from missing data to something subtler: platforms now fill the gaps with modeled estimates displayed alongside observed conversions. Platform claim, observed correlation, modeled contribution, measured incrementality. Four numbers, four meanings, and most budget mistakes come from confusing them. Here is the stack that separates them.
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.
The paid-media account standard, v1.0.
Every "healthy account checklist" is a list of things no competent operator would dispute, which is exactly why accounts fail them: agreement is free and thresholds are not. This is the same discipline rebuilt as a real standard: 22 numbered criteria each with a pass condition you can fail, weighted scoring that gates on the layers which corrupt everything downstream, an explicit list of what we left out and why, and a version number so an account scored today stays comparable next year.
Want this applied to your account?
Run a free AI audit of your Google or Meta account, or talk to the team about what scaling profitably would take.