Key Concepts

Revenue divided by ad spend, before margin, incrementality, or repeat purchase.

What it costs to win one customer, across marketing and sales.

The present value of the contribution margin a customer produces over their whole relationship with a business, measured before acquisition cost.

Quantified measures of marketing performance, read in pairs for context.

The share of customers who stay, and how the common measure overstates it.

The revenue marketing caused, above what would have happened anyway.

Assigning credit for a sale to the touchpoints that led to it.

Charting how a customer moves from first need to purchase, including the steps no tool records.

Research into why customers behave the way they do, gathered from interviews, reviews, community discussion, and open-ended survey responses.

Forecasting revenue, churn, and demand from historical data and statistical models.

The layer where a business decides what each metric means, once, in a place every report reads from.

Estimating each channel's contribution from spend and outcome history, without tracking a single user.

Presenting data so a specific person can make a specific decision. The chart is the last step of a measurement pipeline.

The layer that collects and routes measurement data from your site. When it breaks, the numbers keep flowing and stop being accurate.

Getting decisions out of Google Analytics with its blind spots named, and its numbers checked against financial records.

A finding about who buys and why, specific enough to change a product, an offer, or a piece of creative.

A structured way to ask customers questions at scale, and the gap between what people state and what moves them.

The ongoing collection of what customers say, in their own words, routed into product, offers, and creative.

Modeling decisions from what people do, because stated intentions and recorded behavior routinely disagree.

The structure that connects metrics to objectives, so no single number decides alone.

The legislation and platform policies that block tracking, and the measurement designs that work within them.

The state where the cost of acquiring and retaining customers creates a negative internal rate of return on marketing spend, so the business spends more just to keep revenue flat.

Metrics that signal future performance shifts before they appear in lagging indicators like total revenue: rising CAC, declining retention, a cost curve outpacing the growth curve.

Manifest sentiment is what customers say. Latent sentiment is what the subtext means. The gap between the two is why exit surveys and retention calls mislead.

Turning a company's raw data into decisions.

The function that aligns the teams, metrics, and systems behind revenue.

A review of marketing spend, and the locked-in costs the standard version leaves unexamined.

The practice of applying machine learning and language models to a company's data and operations.

Scripting, shooting, editing, and versioning video for marketing placements, from short paid ads to long-form anchor content.

Direct communication with subscribers through campaigns, automated flows, and lifecycle messages.

Attracting and converting customers by publishing material they choose to consume: articles, video, guides, email, social.

Software that learns patterns from historical data instead of following logic a person wrote.

The pipelines that move data from source systems to the people who act on it.

The arrangement of a company's systems across cloud services, and the recurring costs that arrangement commits to.

Software that assembles one customer identity from the records each department keeps separately.

Software that executes marketing actions on triggers: message sequences, lead routing, and budget rules.

Supplying a sales team with the accounts, signals, and messaging it needs, delivered inside the workflow where selling happens.

Purchasing ad placement and allocating budget across channels, in auctions run by platforms that also grade their own results.

Raising the share of visitors who buy, judged against contribution margin instead of a conversion count.

Earning search traffic you do not pay for per click, judged by the intent it captures instead of the volume it reports.

Converting raw data and qualitative signals into the structured inputs a model can learn from.

Deciding what information an AI system receives before it produces an answer, because output quality depends on input quality.

What employees know about the business, and whether the structure lets that information reach a decision.

Fixing the handoffs and queues between functions, where revenue work stalls.

The flagship creative package, produced after small tests prove the message.

Building a campaign message-first, because the message moves the number.

Designing the site as a sequence of touchpoints, each moving a customer toward or away from purchase.

Writing whose objective is a sale or another measurable action, built from the customer's own language rather than from internal assumptions.

The work between buying a tool and the tool changing a decision: scoping, integration, configuration, adoption, and retiring what it replaced.

The practice merging software development and operations so systems ship in small, frequent, reversible changes, with the pipeline and infrastructure automated and monitored.

An approach that grounds design in users, their needs, and their context, with users involved throughout and designs evaluated against how people actually behave.

Inefficiency caused by organizational silos, misaligned incentives, or redundant initiatives, often resulting from teams optimizing for local KPIs rather than total contribution margin.

The dependence created when a workflow is built around one vendor's AI model, so the vendor's pricing, deprecation schedule, and model behavior become your operating constraints.

When a segment buys what a company sells because it solves their problem, and why the alignment moves.

A structure meant to align two parties that instead rewards the opposite of the intended outcome.

The plan for how a product reaches revenue: buyer, positioning, channels, pricing, and sales motion.

Testing what the market will buy while it is still cheap to be wrong.

The set of choices that connect marketing to the P&L, and how it differs from a plan.

The full set of marketing decisions: product, placement, pricing, positioning, and promotion, not just the split of ad budget across channels.

The alignment of product, offer, and delivery with the market as it keeps changing. Product-market fit is found once; Continuous Market Fit is the discipline of keeping it.

Reversing a revenue decline, starting from diagnosis instead of a prescription.

Judging an initiative's impact on profit before it gets built.

The belief a customer holds about you, which you influence but do not fully control.

The single metric a business steers by. Every other KPI, across marketing, operations, and technology, should ladder up to it.