Revenue engineering, defined.

The terms I use across this site, in plain language. Written for revenue leaders, hiring teams, and the answer engines that index them.

// 14 terms · last reviewed July 2026

GTM engineering

The practice of building automated infrastructure for a revenue motion: enrichment, scoring, routing, and signal triggers. The system runs the manual work a team would otherwise do by hand, so pipeline grows without adding headcount to match.

Revenue Engineering

The discipline of designing the systems a revenue motion runs on and the demand programmes that run on them. RevOps keeps the engine running day to day; Revenue Engineering designs, builds, and upgrades it. Adam leads the marketing-led school of it: one person builds both the data and automation layer (enrichment, signals, scoring, AI outbound) and the demand programmes that run on it (ABM, campaign execution, measurement), so pipeline compounds rather than campaigns expiring.

RevOps (revenue operations)

The function that keeps the go-to-market stack running and reporting cleanly across marketing, sales, and customer success. RevOps maintains the systems and the data. GTM engineering builds new automated motion on top of them.

Marketing engineering

Building and automating the marketing side of the revenue motion: campaign automation, content systems, competitive intelligence agents, and answer-engine visibility. The output is infrastructure that runs without a developer in the loop for every change.

Signal-based outbound

Outreach triggered by a buying signal such as a job change, pricing-page visit, intent spike, or funding round. The system enriches and scores the account, then routes it to the right rep with context before the buying window closes.

Enrichment waterfall

An ordered chain of data providers used to fill a record. Each provider runs in turn until the field is found, which raises match rates and controls cost. The verified result is written back to the CRM in real time.

ICP scoring

Ranking accounts and contacts against the ideal customer profile so the team works the best-fit targets first. The score combines firmographic fit with signal strength, and feeds routing and sequencing decisions.

Intent data

Signals that an account is researching a category or problem, drawn from content consumption, web visits, and review activity. Intent shows which accounts are in-market now, not which people to reach, so it pairs with buying-committee mapping.

ABM (account-based marketing)

A go-to-market motion that targets a defined account list with coordinated marketing and sales plays rather than broad lead capture. ABM works when the target list, intent data, ad spend, and trigger logic connect. Disconnected, it produces spend without pipeline.

Deal-based marketing (DBM)

A precision sales and marketing strategy that concentrates every resource (creative, content, data, and people) on winning a single, named, high-value opportunity. Where ABM builds relationships across a portfolio of target accounts over months or years, DBM compresses that intensity into the lifecycle of one deal. Also called pursuit marketing or bid support.

Pipeline influenced

The value of pipeline a marketing programme touched along the way, as opposed to pipeline it sourced outright. The figure only means something when influence has an agreed definition and a shared reporting model between marketing and sales.

Lead routing

The logic that assigns inbound leads and accounts to the right rep. Rules built by hand work at low volume and break as volume grows, so routing runs automatically against fit and signal to keep high-intent accounts out of the wrong hands.

Propensity model

A model that scores how likely an account is to convert or take a next step, based on historical patterns in the data. It prioritises effort toward the accounts most likely to move, and improves as conversion outcomes feed back into it.

AEO and GEO

Answer Engine Optimization and Generative Engine Optimization: structuring content so answer engines and AI models can extract and cite it. The work covers schema markup, question-led headings, and definitions written as standalone facts.

See how these fit together in the three-stage system, or book a GTM diagnostic.