Context · Business model
B2C ecommerce
Short consideration cycles, high volume, purchase as the outcome. The easiest place to measure and the easiest place to fool yourself.
What changes here
The same four questions, and what each one runs into in this context.
Attribution
Short windows make last-touch look accurate. Branded search and retargeting absorb credit for demand that already existed.
Incrementality
Geo holdouts are fast and cheap here. Watch for brand search contamination across market borders.
Allocation
Marginal returns bend quickly at scale, and the promotional calendar confounds almost every naive comparison.
Decisioning
Repeat purchase drives value, so optimizing to first purchase understates what a customer is worth.
Written for this context
Attribution
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Attribution Is Not Incrementality
Attribution assigns credit for conversions you observed. Incrementality estimates the ones that would not have happened otherwise. The gap between them is where budgets go wrong.
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Reading Platform Discrepancies Without Losing Your Mind
Two systems report different numbers for the same campaign. Four causes account for nearly all of it, and checking them in the right order turns a week of investigation into an afternoon.
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The Same Click, Different Funnels
One ad click means something different in a self-serve checkout than in a sales-qualified pipeline. The funnel it enters decides the unit, the window, and the outcome you are allowed to attribute it to.
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What Multi-Touch Attribution Actually Computes
Seven credit rules run on the same journeys, from last touch to Markov chains and Shapley values, against the effects that generated them. What changes between rules, what does not, and why the sophisticated ones fail in the same place.
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What Tracking Loss Actually Costs You
Consent refusal, identity resolution, and cross-device loss are not one problem. Separating loss that costs precision from loss that costs validity, and why only one of them is fixable with more data.
Incrementality
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Choosing Between User, Geo, and Cluster Holdouts
The design decision is about what you can withhold cleanly, not about statistical efficiency. A procedure for picking the unit, in which power is the last question rather than the first.
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The Diagnostics That Earn Belief
Balance, overlap, pre-trends, placebo tests, and sensitivity analysis. Which to run, in what order, and the thing they all share: they can falsify a design and never confirm one.
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Triangulating When Your Evidence Disagrees
An experiment, a mix model, and attribution give three different answers for the same channel. A structured way to reconcile them, and why averaging can be worse than picking the best one.
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When Randomization Is Impossible
Difference-in-differences, synthetic control, and interrupted time series. What each one assumes, the diagnostic that would falsify it, and how far wrong the same estimator goes when the assumption fails.
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When the Experiment Leaks
Noncompliance, contamination, and spillover are three different leaks that bias in different directions. Intention to treat survives two of them, and the third is only fixed by the design.
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Where Precision Comes From in a Holdout
Pairing, covariate adjustment, a weighted control, and randomization inference, applied to one geo test in two noise worlds. Most of the levers people reach for buy nothing in a geo test. The design and the inference are what move the interval.
- Worked example
Designing a Credible Geo Holdout
A paid social incrementality test carried end to end: market pairing, power, pre-trend diagnostics, a difference-in-differences estimate with its interval, incremental CAC, and what the design cannot settle.
Allocation
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Adstock, Saturation, and Honest Response Curves
Lagged effects and diminishing returns are where most mix models smuggle in their conclusions. How to tell a fitted curve from an identified one, and what variation would identify it.
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Calibrating an MMM to Experiments
Which experiment to run, how to carry its estimate into the model, and how hard to lean on it. Anchoring a channel's level drags its slope down with it, and the slope is what the media plan runs on.
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Marginal Return, Not Average Return
The channel with the best cost per acquisition is often the worst place to put the next dollar. Averages describe money already spent. Budgets are decisions about money that has not been spent yet.
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Paid Search and SEO Are Not Independent
Pause branded paid search and most of those conversions come back through organic. The paid channel's cost per acquisition describes a transfer between two of your own channels, not a purchase of new demand.
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What a Marketing Mix Model Can and Cannot Do
A mix model is a good allocation tool and a weak causal one. Where its identification would have to come from, why a Bayesian version does not create any, and what makes one worth acting on.
- Worked example
An Experiment-Calibrated Marketing Mix Model
A mix model that fits three years of weekly data almost perfectly and gets the channel contributions badly wrong, and what one geo holdout does about it.
Decisioning
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Choosing the Right Campaign Optimization Event
The deepest event that stays reliable, timely, and frequent enough to train on. Alignment sets a ceiling you cannot buy your way past, precision decides how close you get, and only one of them improves with volume.
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From Segment to Audience to Treatment Policy
Segments, audiences, scores, assignments, and policies are five different objects. A result is only comparable to a previous one if you can say which of the five changed.
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The Case for Doing Nothing
Contact fatigue, capacity, and cost mean no-action is a real treatment arm. Why it belongs in every decisioning system by default, and why organizations reliably leave it out.
Systems
- System
Contact Permission and Suppression
Lawful basis, channel permission, jurisdiction, purpose, global opt-outs, and complaint handling as one shared layer rather than a filter each campaign reimplements. Consent is one basis among several; suppression is a decision of your own.
- System
Automated Measurement
A standing readout that runs eligibility, assignment, delivery, exposure, outcome, and guardrails on a schedule instead of as a bespoke analysis each time.
- System
Program Lift and Reconciliation
What the program holdout says the lifecycle policy was worth, reconciled against what the tested actions account for on a common value scale, with the residual reported as a residual. The question a per-campaign readout cannot answer.
- System
Next-Best-Action Policy
Turning scores into decisions under real constraints: capacity, contact fatigue, margin, cooldowns, and the explicit option of doing nothing.
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Treatment Effects and Policy Evaluation
The bridge between a campaign's average effect and a per-customer decision: estimating how the effect differs by customer state, and scoring a candidate policy on randomized or logged data before it is trusted with volume. The component that produces the numbers next best action consumes.
- System
Surfaces and Assignment
Which parts of the product the system covers, how a visitor is assigned to an arm before they have an account, and how that assignment survives the moment they get one. The component where contaminated results start.
- System
The Metric Ladder and Guardrails
One metric that decides, a short list that can veto, and a record of how each proxy earned its place. The component that stops a fast loop from optimizing the top of the funnel at the expense of the bottom.
- System
Test Design and Traffic
Which test may launch now, on whom, alongside what, at what allocation, for how long, and under what ramp and kill rule. The component that turns a stream of individual tests into a portfolio that can be run at once without the tests reading each other.
- System
Sequential Readouts
When a test is allowed to stop, what it reports when it does, and the checks that run before anyone reads a lift. The component that makes a fast loop trustworthy, because reading a test daily and stopping when it looks good inflates a five percent false-positive rate to about a quarter.
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Shipping Rules and the Registry
The rule that turns a readout into a decision, applied the same way to every test, and the registry that records what was asked, what was found, and what was done. The component that makes the tenth quarter cheaper than the first.
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Media Taxonomy and Spend Spine
One vocabulary for channels and tactics, one spend series reconciled to what the business paid, joined to the outcome the budget is meant to move and what it is worth, at a grain that supports the designs you want to run.
- System
Geo Design and Market Matching
Choosing which markets go dark, for how long, and against what, so that the difference afterwards means something. The sample size is the number of markets, not the number of people in them.
- System
The Test Calendar
Experiments as a standing cadence rather than a request, ordered by how much spend rests on a coefficient nobody has validated. The component that makes calibration possible at all.
- System
The Persistent Geo Holdout
A small, rotating share of markets kept dark on the largest channel, so calibration has a recurring anchor without a negotiation. The standing control the calendar cannot provide, when it is worth running, and the price of having one.
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Response Curve Estimation
Adstock, saturation, and priors, plus the harder question underneath them: what in the spend history is doing the identifying, and where does the curve stop being estimated and start being assumed.
- System
Calibration
Folding measured effects into the model as priors, and deciding what happens when the experiment and the model disagree. The step that closes the loop between testing and planning.
- System
Budget Reallocation
Turning a set of curves into a plan somebody will run, under the contracts and minimums that make the unconstrained optimum unreachable, and choosing the moves that generate the next experiment.
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The Budget Decision Log
Every reallocation recorded with the curves that justified it, the effect it predicted, and what happened. The component that lets a quarter score the quarter before it, and the reason the loop closes instead of restarting.
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Content Inventory and Template Map
Every URL mapped to the template that renders it, the intent it serves, and whether it is indexed at all. The unit of change and the unit of randomization are not the same thing, and both have to be known.
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Crawl and Index State
Shipping a change is not delivering it. Treatment begins when a page is re-crawled and re-indexed, which happens over weeks, in an order that is not random and is correlated with the outcome.
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Template Split Design
The only control organic gets is the other half of a template, so the design question is which pages take the change, stratified by the traffic concentration that decides whether it can detect anything.
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Counterfactual Traffic
What to do when the change had to ship everywhere and there is no other half: modeling what the pages would have done, and knowing when a core update has broken the comparison.
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Paid and Organic Together
Some of an organic gain on a term you also buy is your own paid traffic arriving free, and reporting the two channels separately can count the same click twice. How much is measured, not assumed, and who owns the number.
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The Change Roadmap
Which template gets changed next, ranked by traffic at stake rather than by audit severity, and shipped as a split so the change produces evidence instead of consuming it.