What a Real Amazon Marketing Strategy Case Study Should Show
A real case study states total spend, blended cost per click and CPM across every placement (not just the cheapest one), portfolio-wide ROAS, CPA, new-to-brand share, and how the result was verified — ideally a holdout test, not last-click attribution alone.
What this looks like in a real account
What separates a real case study from a brand story
Most pages ranking for this term are not case studies. They're brand history — Bezos in a garage, the four P's, Prime membership counts. Useful reading, but they answer 'why is Amazon successful' not 'did this advertising campaign work.' Those are different questions.
A real Amazon marketing strategy case study is narrower and more mechanical. It names a defined period, a defined spend, a defined set of advertisers or campaigns, and a result measured across all of them — not the one campaign that hit. It also says how the result was checked. If a case study can't tell you the timeframe, the sample size, and the verification method, it's marketing copy wearing a case study's clothes.
The other tell: cherry-picked line items. A single ASIN doing 12x ROAS inside a portfolio averaging 3x is a real number, but reporting only the 12x is misleading. Ask whether the figure covers the whole book or the best slice of it.
A worked example, with the whole book shown
Here's what a full-book case study looks like in practice. Across 30 advertisers we manage, one month (July 2026) produced 6.04x return on ad spend — measured across the whole portfolio, not the best line item inside it. That's the number to trust more than a single hero campaign, because it can't hide underperformers.
Underneath that headline sit the mechanics: 78.4 million impressions at a $4.00 CPM, and a blended $1.42 cost-per-click. That $1.42 matters because a $0.41 CPC gets quoted constantly in this category — and it's real, but it's an online-video-only number, not a blended one across search and display placements. A case study that quotes the low number without saying which placement it came from is doing the cherry-picking problem again, just with a cost metric instead of a ROAS metric.
Below CPC sits acquisition cost: $5.49 blended CPA across 57,137 attributed purchases. And below that, the number that tells you whether the spend grew the brand or just harvested existing demand: 20.1% of those purchases came from a shopper new to the brand. One in five. That's the figure that separates media that's building an audience from media that's just collecting existing customers at a markup.
Read in that order — scale, cost, return, acquisition, new-to-brand — a case study tells you not just whether something worked, but what kind of working it did.
When the numbers are bad news
A case study is only honest if it also says what happens when the number is wrong. Three situations come up constantly, and each has a specific fix — not a rewrite of the narrative.
- ROAS looks worse than last month. Check whether spend moved into a different placement mix before assuming performance dropped. A shift toward upper-funnel video will lower ROAS by design; that's not failure, it's a different job being done.
- CPA is trending up. Before cutting budget, check whether sponsored ads and DSP are being credited for the same purchase. Double-counted conversions inflate apparent efficiency, and when you fix the double-count, CPA looks worse even though nothing changed operationally.
- The lift can't be confirmed. This is the most common bad news, and the least often reported. Last-click attribution will happily tell you display drove a sale it had nothing to do with, or fail to credit a sale it caused. The only way to know is a holdout or matched-control test — some accounts see the ad, some don't, and you compare. If a case study never mentions a holdout, it hasn't actually proven incrementality, no matter how good the ROAS number looks.
The right move when a number disappoints is to isolate the cause before touching the budget. Cutting spend on a campaign that's actually incremental, because a flawed attribution model said it wasn't working, is a more expensive mistake than the bad number itself.
The mistake almost every case study makes (including ones we've published)
The most common error is blending cost metrics across placement types without saying so. A CPC that mixes cheap video inventory with expensive search placements produces a headline number nobody could actually plan a budget around, because it doesn't correspond to any single decision you can make.
We've done this. Earlier reporting on our own book quoted a blended CPC without breaking out what was driving it down. It wasn't wrong, exactly — it was incomplete in a way that flattered the number. Reconciling everything through Amazon Marketing Cloud, where DSP and sponsored ads stop double-counting each other, is what forced us to stop doing that. Once you can see line by line what's inside a blended figure, you can't unsee it, and reporting the flattering-but-vague version starts to feel dishonest even when it's technically accurate.
The second common mistake is treating last-click attribution as proof of incrementality. It was never built for that job. Last-click tells you which touchpoint happened closest to a purchase — it can't tell you whether the purchase would have happened anyway. Holdouts and matched controls can. That distinction sounds academic until a budget decision hinges on it.
A checklist for reading any Amazon case study
Before trusting a number in someone else's case study — or your own — run it against the table below. Each row is a place where the honest version and the flattering version diverge.
| Component | What an honest case study shows | Shortcut that hides the truth |
|---|---|---|
| Spend & scale | Total spend, impressions, exact timeframe, number of advertisers or campaigns | One standout campaign presented as if representative |
| Cost metrics | Blended CPM/CPC across all placements, with placement mix disclosed | Lowest-cost placement (often online video) quoted as the average |
| Return metric | ROAS or ROI measured across the whole portfolio | Best single SKU or line item |
| Acquisition | CPA alongside purchase volume | Revenue reported without cost or count of purchases behind it |
| New-to-brand share | % of purchases from shoppers new to the brand | Total sales presented without saying who was already buying |
| Verification method | Holdout test or matched control confirming incrementality | Last-click attribution presented as proof |
Which one you should actually pick
If you're building an internal case study to defend budget, the checklist and worked example above are the whole job — go build it. If you're evaluating an agency's claims, ask for the whole-portfolio number and the verification method before the headline stat. reMKTR runs Amazon DSP as a managed service and reconciles results in Amazon Marketing Cloud specifically so display and sponsored ads stop double-counting each other; that's one way to get an honest number, not the only way, and it won't suit a team that wants to run DSP self-serve.
Shortlist on the job, not the feature grid. Pull your search-term report for the last 90 days and total the spend against terms that produced no orders — 33.6% on the account above. Then ask each vendor on your list what they would do about it in week one, and see who answers with a process rather than a screenshot.
Common questions
What's the difference between an Amazon brand story and a real marketing case study?
A brand story explains why a company succeeded in general terms — customer focus, long-term thinking, diversification. A case study is narrower: it reports what a specific campaign or media spend did over a defined period, with numbers you could audit. Most pages that rank for this search are brand stories, not case studies.
How do I know if a ROAS number in a case study is legitimate?
Check whether it's measured across a whole portfolio or account, or drawn from a single best-performing campaign. Also check the attribution method behind it — a ROAS number built entirely on last-click attribution can overstate or understate the real effect, because last-click can't distinguish a sale the ad caused from one that would have happened anyway.
What should I do if my own campaign's case study shows bad numbers?
Isolate the cause before cutting spend. Check for double-counted conversions across DSP and sponsored ads, check whether the mix shifted toward a different funnel stage, and if possible run a holdout to see whether the underlying campaign is still incremental. Bad-looking numbers and a genuinely underperforming campaign are not always the same thing.
Does last-click attribution work for proving an Amazon ad strategy worked?
No. Last-click can tell you which ad touched a purchase last, but it cannot tell you whether that purchase would have happened without the ad. Proving that requires a holdout group or matched control — comparing exposed and unexposed audiences directly, rather than crediting whoever was closest to the sale.
Is there a normal ROAS or CPA for Amazon advertising?
There's no single benchmark that applies across categories, price points, and funnel stages — anyone quoting one flat number is oversimplifying. What's useful is seeing a real, whole-portfolio result: across a 30-advertiser book we manage, one month produced 6.04x ROAS and a $5.49 blended CPA, which gives you a data point, not a promise about your own account.
We show the method before the number.
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