B2B SaaS

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.

Defining Events That Survive Contact With Operations

A lead, an activation, and a qualified opportunity are organizational agreements before they are data. What happens to a time series when the agreement changes and nobody writes it down.

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.

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.

Leads Versus Incremental Qualified Pipeline

A B2B lead program that hit every MQL target, measured by a staged rollout across territories. Leads went up by half. Opportunities and pipeline did not detectably move, the leads converted at two thirds the rate, and the design could never have seen the pipeline effect it was asked about.

Counterfactuals, Estimands, and Saying What You Mean

Before choosing a method, state what you are trying to estimate: which units, which treatment, which outcome, over what horizon. One campaign produces six different numbers, and only one of them is wrong.

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.

Prediction Is Not Persuasion

A model that knows who will convert does not know who you can convince. The two questions have different answers, and only one of them can be checked against data you already have.

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.

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.

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.

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.

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.

Uplift Modeling in Practice

Where to cut the ranking, how much to withhold, and why the offline number is larger than the money. Estimating heterogeneous treatment effects when you have a randomized holdout, and validating the policy prospectively.

Broad Nurture, Propensity, or Uplift?

One trial-to-paid nurture sequence, four targeting policies, and a randomized holdout. Compared on incremental conversions rather than model accuracy, which is the only comparison that changes the answer.

Customer State Model

One row per person or account carrying consent, lifecycle stage, eligibility flags, and contact history. The foundation every audience, experiment, and policy reads from.

Audience Builder and Capacity Planning

Audience definitions as versioned, reusable objects instead of one-off SQL, and the capacity check that decides whether a test was ever going to work.

Assignment and Experiment Registry

Deterministic hash-based assignment, a program holdout with a scope contract, overlap rules, an outcome contract per experiment, and a registry that stops two campaigns from colliding on the same people.

Exposure and Decision Logging

Logging what was decided and what was delivered, not just what was sent. The component that makes everything downstream measurable at all.

Evidence Review

The standing forum where estimates get ranked by what they assumed, a number is promoted to the one the plan uses, and a result is allowed to be inconclusive.

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.

Units Above the Visitor

When the visitor is the wrong thing to randomize: teams that must see one price, marketplaces with two sides, referral loops, and shared devices. The component that decides how much sample a clean comparison costs.

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.

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.

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.

The Long-Run Holdback

A small standing share of visitors who never see any shipped change, so that once a quarter the sum of the program's wins can be checked against what the program added. The component that keeps a fast loop pointed at the outcome.

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.

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.

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.

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.

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.

The Account Graph

One canonical buying unit, the contacts that resolve to it, the buying episodes in which it can buy, and the state it was in when treated. Two grains at once, and every measurement downstream depends on which one a number is counted at.

Designs When Randomization Is Refused

No sales leader will accept a do-not-touch list on named accounts. What can be assigned is the marketing program itself, with sales left alone in both arms, and after that the territory, the partner, and the order of a staged rollout.

Lag-Aware Readouts

Deals close over quarters and decks are due in weeks, so the readout has to choose an outcome it can observe and say what it gave up by choosing it.

Sourced, Influenced, and What Replaces Them

Two reporting conventions that divide pipeline without a counterfactual, why both are attribution wearing a B2B accent, and the evidence ledger that should sit above them.

Rep Capacity and Account Prioritization

Which accounts get a rep's hour, which is the scarcest allocation on the list. Scoring is easy, and the constraint that decides whether it changes anything is how many hours exist.

The Prioritization Log

Which accounts were ranked, which were assigned work and at what probability, and what was actually done, with a two-sided exploration band around the cutoff so that both working and not working have support near the line. The record that lets the next ranking be evaluated before it ships.