Reading Amazon in three dimensions.
The free notes let you see the shape. This course gives you the method to find it on your own account: the decomposition, the queries, the controls and the checklists, unit by unit.
Operators with data
Sellers with real volume, in-house ad leads and agency operators who already know the console and want to know why the numbers move.
A method, not a verdict
Ways to decompose a metric, test whether ads are incremental and catch a reading trap before it costs you a decision.
Setup and promises
No account setup walkthroughs, no compliance advice, no tool recommendations and no promised results.
Six modules. One skeleton in every unit.
Each unit opens with a popular claim or something a seller actually said, then walks the same eight steps: how the crowd reads it, the premises, how we take it apart, the evidence, what would prove it wrong, how you run it yourself, and where it stands in the ledger.
The Shadow Problem
- Every report is a shadowACOS, AMC and SQP each see one face of the account.
- Dashboard vs. mapLagging indicators versus structure; what matters is whether the account grows.
- Why one operator can do it nowBringing AI into your analysis: it joins the reports, you keep the judgment.
- How to read this courseExperience vs. hypothesis, the verdicts, three rules that run through everything, and the public ledger.
- Time is the third axisNumbers alone are flat. Where shoppers are in their journey changes every number, which is why customer mix comes first.
- Survive, don't gambleGo all in on getting to the bar fast, and aim at the weak spots, not the leader.
The Mountain: Ticket, Auction, Reaction
- The mountainShoppers are already on the mountain; your bid only decides how hard you reach for them. Why ads cost so much, especially at the start.
- Not a second-price auctionThe bid is close to the price you actually pay.
- One seller, one entryWhen several of your campaigns chase the same term, only one enters the auction.
- When bids stop bindingRead the margin, not the average; when the budget caps out, ratios are the signal.
- Premium is a bidA rest-of-search placement premium acts like a higher bid.
- Reaction comes lastFix three axes before reading conversion: customer mix, placement and targeting type.
- The suggested bid is your scoreNot the market price for a keyword. Judge how hard you bid by what you get.
- Match type shapes your poolExact, phrase and broad change how many shoppers you can reach, and where. With an interactive simulator.
- One metric per stageA new listing in four stages, one number to watch at each, and when to shift or stop.
- Variations: inherit the shelf, not the ticketWhat joining a variation family really brings, and why to check the parent before any test.
- Open question: more ticketsHow more shoppers become eligible to see you. Unsolved, and tracked in the open.
Five Reports, Five Calibers
- What each report countsFour labels on every number: how it is counted, its scope, its time, and its causal level.
- Time trapsAccount time zones, order timestamps, and comparing against the same weekday.
- Reports that keep changingBusiness Report figures still revise weeks later.
- Aggregation trapsDeduplication, and why shares must be summed before they are divided.
- Attribution breaksA change in attribution rules that looks like a collapse.
- Profit that adds upThe finance caliber, and why the deposit is a fraction of what you sold.
- Intent groups, not wordsRead SQP by groups of searches with the same buying motive, and rank them against each other.
- A blank is not a zeroNot spent, not loaded, masked, or missing: four blanks that look like zero.
The Customer Cycle
- Who counts as newNew, recent and settled customers, and a lookback window you measure instead of assume.
- The fake 100% newAn illusion created by privacy thresholds.
- Repurchase curves and the refill windowEach product has its own cut-off, and the fight to keep a new customer is early.
- Entry vs. terminal productsWhich products bring people in and which are the last stop.
- Acquisition vs. harvestWhere acquisition and harvesting spend actually flow, and what the flywheel can and cannot claim.
- Did we reach new people?Compare warm-to-cold ratios, not the share of returning customers.
- New and returning, by placement and positionMost shoppers who see the top slot are new; returning shoppers just buy there far more.
- How much can the first order lose?Work back from repurchase to the most you can pay for a new customer.
Decompose, Then Prove
- Why ACOS risesSplit the change into parts that add up exactly.
- Three reasons exposure fallsWith opposite fixes, plus a fourth: the denominator grew.
- Is it incremental?Five rulers, including whether your ads just claimed buyers you already had.
- Controls that tell the truthSame-product controls, untouched placements, and A-B-A tests.
- Free experimentsDeliberate switch-offs and zero-spend windows, and the gates they must pass.
- When did it really break?Missing files first, then stock and the buy box, then the breakpoint.
- The residual is a ceilingTotal minus ads is an upper bound, not organic truth.
- Where the funnel leaksYour share at each step against the market, and what to fix at each break.
- Break-even: when to cutThe break-even line, marginal returns, and why a guardrail must be tested first.
- Price is a lever tooMeasure price response product by product; it confounds every ad test.
Watch, Then Act
- State the goal firstThe same data means opposite things under growth and profit. Name who takes over any volume you cut.
- Direction firstDecide up, flat or down in absolute numbers before looking for causes.
- Drill to the keywordFrom total to placement to intent group to word, and pruning without killing.
- Freshness tiersWhat each data source can tell you, and how fresh it has to be.
- Right pair, right roleAcquisition is judged by cost per new customer; harvest by cost per order.
- The weekly inspectionA fixed route from direction to cause to action, with a guardrail on every move.
- Good news needs a drill-down tooStrip out the spikes before you call it growth.
- Top-10 concentrationHow much of a keyword group the top ten hold, and which rivals are buying exposure, holding a stable base, or winning clicks.
- Write the prediction firstWrite what should happen before you change anything, then score it.
Free lets you see it. The course lets you do it.
The free notes are meant to be true enough to trust on their own. That is where the trust is earned.
| Part of each unit | Free note | Course |
|---|---|---|
| ①–③ The claim, the crowd's reading, the premises | Full | Full |
| ④ How we take it apart | The conclusion and one key screen | The complete decomposition, including how AI joins the reports |
| ⑤ Evidence | One example | All the evidence, several cases, the failures too |
| ⑥ What would prove this wrong | One sentence | The full set of disproof conditions |
| ⑦ How you run it | — | Step-by-step operations, query templates, checklists, the research-method handbook |
| ⑧ Ledger status | Public | Public, plus updates when a verdict changes |
Trust built from premises, not from screenshots of revenue.
I can't show you who I am, which accounts these are or what they sell. So the course is built to be checked instead of believed.
Every claim carries its own disproof condition
Each unit states the result that would overturn it. If you see that result on your account, the claim is wrong for you, and I want to hear about it.
Premises first
Before any conclusion, the premises are laid out and marked ✅ ⚠️ or 🔶. You can reject a premise and see exactly which conclusions fall with it.
Reproducible on your account
Part ⑦ gives you the steps, queries and checklists to run the same test on your own data.
Reversals are published
When a verdict flips, the reversal stays in the public ledger with the premise that broke.
Experience and hypothesis, labelled
You always know whether a claim was measured on my own accounts or is a framework still under test.
No conflicts of interest
No tools for sale, no affiliate links, no testimonials. Scale is stated once, in ranges, and never shown off.
Bringing AI into your analysis
AI assists; the judgment stays yours. Each lesson shows how to bring AI into your own operating analysis: which reports to hand it, how to line up their definitions and time windows, how to cross-check a claim from several angles, and how to catch it when it gets something wrong. The questions, the verdicts and the disproof conditions remain human work.
Screens shown in the course use de-identified or demonstration data. No client, product or absolute revenue figures appear anywhere.
The full series
Price to be announced
- All 6 modules, 52 units, video and text
- Part ⑦ in every unit: steps, queries, checklists
- Downloadable attachments and the research-method handbook
- Ledger updates when a verdict changes
Personal use only. See terms.