Sam Nouri
Founder, ADSRUNNER
Sam Nouri is the founder of ADSRUNNER and a growth operator working at the intersection of paid media, customer behavior, measurement, and business economics.
Across more than 12 years in paid growth, Sam has worked in over 50 industries and managed more than $200 million in ad spend. That experience taught him that stronger platform metrics do not necessarily mean a stronger business. The useful question is what paid media contributes after attribution assumptions, customer value, margins, and payback are taken into account.
Sam founded ADSRUNNER in 2021 to bring strategy and execution closer together. He remains close to the work while building an agency where experienced judgment is supported by better systems, proprietary technology, and AI-assisted analysis. The aim is to make growth decisions clearer and more accountable, without turning them into a black box.
His work focuses on the choices that determine whether paid media creates durable value: who to reach, what makes an offer relevant, where the customer journey breaks down, how performance should be measured, and when additional spend has earned the right to scale.
Sam writes about paid growth, attribution, customer acquisition economics, and the role of human judgment in an increasingly automated industry.
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.