Glossary
Every term here is one we kept hearing in rooms where it meant something different to each person. The definitions are short on jargon and long on usefulness. Cite them, share them, copy them into a meeting if it helps.
Revenue automation is a single connected system across marketing, sales, and customer success in which strategy, signal, orchestration, and execution all live in one engine. It replaces manual handoffs and disconnected tools with a measurable, self-improving motion.
Not the same as marketing automation (campaigns) or sales automation (sequences). Revenue automation is the engine both plug into. See the full playbook.
Account-Based Marketing is a B2B motion that treats a named list of accounts as the market, then coordinates marketing, sales, and customer success around the buying committee inside each account. Modern ABM runs in three tiers: 1:1 (deep, bespoke for a handful of accounts), 1:few (clustered by segment or use case), and 1:many (programmatic personalisation across a defined list).
ABM in 2026 is less about the channel mix and more about whether the buying committee is mapped and multi-threaded. One champion is a single point of failure. The B2B GTM Engineering guide covers committee coverage and signal-driven account motions.
Agentic revenue is the phase of revenue automation where parts of the engine are run by autonomous AI agents with guardrails. The agent owns research, drafting, surface assembly, and logging, while a human supervises and ships.
Not the same as "a chatbot in the CRM". Agentic is a phase, not a feature. It only works on top of a foundation worth automating. More on what agentic actually means.
Annual Recurring Revenue (ARR) is the normalised yearly value of all active subscriptions. Monthly Recurring Revenue (MRR) is the same number divided by twelve, or the sum of monthly contract values. ARR is the boardroom number used for valuation, planning, and runway. MRR is the operational number used to see month-on-month movement, new logo, expansion, and churn cleanly.
A growing ARR with a flat MRR usually means the team is closing annual deals that mask churn underneath. Look at both, every month, segmented by motion.
The bowtie funnel is a B2B revenue model that treats acquisition, conversion, onboarding, expansion, and advocacy as one continuous loop, not a linear funnel that ends at the close. The left side covers acquisition through close, the right side covers impact, expansion, and advocacy.
Engines that compound work both sides of the bowtie. The right side is where the unit economics get good. Read the long form.
Buyer intent signals are observable behaviours that suggest an account is researching a problem you solve. First-party signals come from your owned surfaces (site visits, pricing page, demo requests). Second-party signals come from review sites and communities (G2, Capterra, Reddit). Third-party signals come from intent providers (Bombora, 6sense) tracking topic surges across the open web.
The trap is reacting to every spike. A useful intent programme defines the topic cluster, the threshold, and the action before the data starts flowing. Otherwise the team chases noise and calls it a pipeline. The phase that handles signal cleanly.
CAC payback is the number of months it takes for the gross margin from a new customer to repay the cost of acquiring them. Healthy B2B SaaS sits at 12 to 18 months. Anything under 24 months is acceptable for most segments. Past 24 months and the engine is paying for growth out of future cash, which only works while funding is cheap.
Payback above 24 months in 2026 is the most common reason a board pulls back on growth spend. Pair it with NRR to read the engine properly. Long payback is survivable if the right side of the bowtie is strong.
The dark funnel is the part of a buyer's research that doesn't appear in attribution data, including peer conversations, Slack groups, podcasts, AI search, and unattributed direct traffic. Increasingly the majority of B2B influence, and the reason last-touch attribution is misleading.
The dark funnel is also why AI search optimisation (AEO/GEO) is a 2026 priority. If the buyer asks ChatGPT and you're not cited, you weren't in the room.
Demand generation is the discipline of creating future buyers, not capturing existing ones. It builds awareness, point of view, and category preference in accounts that are not yet in market. Demand capture is the discipline of converting buyers who are already searching. Most teams over-invest in capture, call it demand gen, and wonder why the pipeline stalls.
The 95-5 rule applies. At any moment, 95% of a B2B audience is out of market and 5% is in. Demand gen earns the future 5%. Demand capture wins today's. Both matter, but only one compounds. Engineered demand vs hope.
A Fractional CMO is a senior marketing leader who runs a B2B company's marketing strategy and execution part-time, typically for early-stage or mid-market businesses that need senior leadership but cannot justify a full-time hire. Strong fractional CMOs embed inside the team, not alongside it.
The fractional model breaks down when the CMO only delivers strategy and the team is left to execute. Agency vs fractional CMO explores the trade-off.
A GTM Engineer is a hybrid role combining RevOps, marketing operations, and AI engineering. They build the systems that connect data, signal, and outreach across the bowtie, often using tools like Clay, n8n, and the major LLM APIs. The role exists because the gap between a B2B strategy and the working pipes that execute it has become too technical for traditional marketing ops alone.
A good GTM Engineer can ship a working data-to-outreach pipe in a week that a traditional stack rebuild would take six months to deliver. The GTM engineering guide covers stack, role, and hiring signals.
A GTM motion is the repeatable way a company takes a product to a segment of the market. Examples include product-led, sales-led, partner-led, community-led, and outbound-led. A motion is not a campaign. A campaign is a time-boxed push inside a motion. Companies that confuse the two end up running a series of campaigns with no compounding engine underneath.
Most B2B companies eventually run two or three motions in parallel by segment. The mistake is launching a second motion before the first one has been honestly measured. The GTM Engineering guide covers fit and sequencing.
An Ideal Customer Profile (ICP) is the documented description of the kind of company most likely to become a successful, expanding customer. A useful ICP names firmographic, technographic, behavioural, and outcome traits, and is precise enough to disqualify accounts, not just qualify them.
If your ICP doesn't help the team say no to a meeting, it isn't tight enough. ICP also lives downstream of the bowtie's right side: who actually expands?
Lifecycle marketing is the discipline of orchestrating the right message to the right customer at the right stage, from onboarding through expansion and advocacy. It is not email marketing. Email is one channel inside it. Lifecycle marketing is the right-side-of-the-bowtie counterpart to demand generation, and the function most B2B teams under-resource until churn forces the conversation.
Strong lifecycle programmes do three things well: they instrument the in-product moments that matter, they coordinate across channels (in-app, email, CSM outreach, community), and they measure outcomes in retention and expansion, not opens and clicks.
MEDDIC is a B2B sales qualification framework: Metrics, Economic buyer, Decision criteria, Decision process, Identify pain, Champion. Used to assess whether an opportunity is real and forecastable, not just open.
Variants include MEDDPICC (adds Paper process and Competition) and MEDDICC. The framework is useful when the team enforces it in the CRM, not just on slides.
A Marketing Qualified Lead (MQL) is a contact whose engagement signals readiness to talk to sales. A Sales Qualified Lead (SQL) is a contact sales has accepted as worth pursuing. The MQL-to-SQL ratio is the most honest test of marketing-sales alignment in a B2B engine.
Healthy ratios depend on segment. Low MQL-to-SQL conversion usually means the MQL definition is generous, not that sales is failing.
Net Revenue Retention measures the revenue an existing customer base produces in a period compared to the same base in the prior period, including expansion and contraction. NRR above 110% signals a healthy expansion motion; below 100% signals churn is outpacing growth.
NRR is the right-side-of-the-bowtie number. A company with weak NRR is running half a revenue engine no matter how good its acquisition is.
Outbound is sales-initiated contact with accounts that have shown no prior interest. Inbound is buyer-initiated contact triggered by content, search, or referral. The 2026 truth is that the distinction has collapsed. The best engines blend the two, using intent signal and content gravity to make outbound feel warm and inbound feel intentional. Treating them as separate teams is a budget structure, not a strategy.
The blended motion looks like this: content and PR create the gravity, intent data picks up the accounts already leaning in, and outbound opens the conversation with context the rep didn't have to invent. The label on the lead matters less than the quality of the next touch.
Pipeline coverage is the ratio of open pipeline value to the period's revenue target. The standard B2B benchmark is 3x to 4x coverage on the quarter, though the right number depends on win rate, sales cycle length, and forecast accuracy.
Coverage is only honest if the records in the pipeline are honest. Coverage on a CRM nobody trusts is a comforting number that means nothing. The forecast you can defend.
A Product Qualified Lead (PQL) is a user who has reached a defined activation event inside the product itself, typically inside a free trial or freemium plan. PQLs are the PLG counterpart to MQL (behaviour in marketing) and SQL (acceptance by sales). The signal is stronger because the user has experienced the product, not just clicked an ad or downloaded a guide.
A good PQL definition names the action (created project, invited teammate, hit usage threshold), the timing (within first session, within seven days), and the response (sales outreach, in-product nudge, both). Without that specificity, PQL becomes another vanity tier.
RevOps is the function responsible for the system that connects marketing, sales, and customer success. A strong RevOps team owns the system of record, the signal layer, and the orchestration logic. A weak one buys tools and hopes.
RevOps is the function. Revenue automation is the engine RevOps owns. Conflating the two is one of the most common diagnostic errors we see.
Sales velocity is the cleanest single measure of a B2B engine's pace. The formula is the number of open opportunities, times win rate, times average deal size, divided by sales cycle length in days. The output is revenue per day. Improving any one of the four inputs lifts the number, and the metric makes it obvious which lever has the most room.
Most teams stare at pipeline coverage when sales velocity is the more useful number. Coverage tells you if there is enough volume. Velocity tells you if the engine moves. Track it weekly, segmented by motion and segment.
A system of record is the single trusted source for a class of data. In B2B revenue, the CRM is the system of record for accounts, contacts, opportunities, and revenue activity, meaning every other tool defers to it for those entities, not the other way round.
When the CRM is not the system of record, the team manages two truths and trusts neither. Making NetSuite the system of record is the long-form version.
Win rate is the percentage of qualified opportunities that close as won. Read at the company level it is a vanity number. Segmented by source, by stage entered, by competitor faced, and by deal size, it becomes a diagnostic. An honest win rate counts every opportunity that entered the pipeline, including the ones quietly closed-lost as no-decision.
The most common win-rate lie is filtering out no-decision losses. They are losses. They are also the most fixable category, because the buyer was interested enough to enter the pipeline and the engine still failed to land. Track them, name them, learn from them.
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