30-second answer: Revenue orchestration is the cross-functional discipline of coordinating marketing, sales, customer success, and operations against a unified account graph and signal layer. The vocabulary covers signal layer, account graph, plays, plays library, instrumentation, and governance. This glossary defines 22 revenue orchestration terms operators use in 2026.
30-second answer: Pipeline orchestration coordinates the cross-channel sequence of touches from intent to opportunity, binding marketing, sales, and post-sales actions to defined triggers and SLAs. The vocabulary covers triggers, plays, routing, handoff, SLA, and attribution. This glossary defines 20 pipeline orchestration terms revenue operators use in 2026.
30-second answer: First-party intent is buyer behaviour observed on properties a vendor owns: website visits, content downloads, ad engagement on owned channels, demo requests, in-product activity. The vocabulary covers signal grain, identification, scoring, decay, and suppression. This glossary defines 20 first-party intent terms used across B2B revenue stacks.
30-second answer: Third-party intent describes account research behaviour observed across external publisher and ad networks, then reported back to vendors under cooperation agreements. The vocabulary covers source types, taxonomy, scoring, suppression, and the cookieless adjustments that have reshaped the category. This glossary defines 20 third-party intent terms.
30-second answer: An intent signal is an observable behaviour or content interaction that suggests an account is researching a category, vendor, or problem. The vocabulary covers source classes, signal grain, scoring, decay, merge, and false-positive control. This glossary defines 22 terms revenue operators encounter in intent-data platforms and orchestration tools.
30-second answer: Account tiering splits a target account list into investment cohorts (1:1, 1:few, 1:many) so revenue teams can match resourcing to expected return. The vocabulary covers tier classes, gate criteria, capacity inputs, and re-tiering operations. This glossary defines 20 tiering terms operators see in ABM platforms and internal docs.
Signal orchestration is the discipline of ingesting every relevant buying signal a B2B revenue team can observe (third-party intent, first-party engagement, CRM events, product usage, conversation analytics, executive and technographic changes), routing each signal to the right team and channel through a defined trigger logic, and tracking what happened so the system gets smarter over time. It is the operational discipline that turns noisy signal feeds into coordinated revenue action; without it, the signal arrives but nothing actually changes in the buyer's experience.
Deal intelligence is the practice of capturing, structuring, and acting on every signal generated during a B2B sales cycle, including conversation analytics from calls and meetings, email engagement, deal-stage data from CRM, intent signals on the buying account, and product or content engagement, then turning that signal into rep coaching, deal-risk alerts, forecast accuracy, and competitive insight. It sits at the intersection of revenue intelligence, conversation intelligence, and pipeline analytics; the value comes from making the data already produced inside the sales motion legible and actionable rather than letting it sit unused in disconnected systems.
Buying committee mapping is the structured discipline of identifying every human stakeholder involved in a B2B purchase decision at a specific account, classifying their role in the decision (champion, economic buyer, technical evaluator, influencer, blocker, executive sponsor, end user), and capturing how they relate to each other so the revenue team can run coordinated motions across the full committee instead of working only with the lead who happened to fill out a form. Mapping is upstream of orchestration; it is the documented committee picture from which sequenced sales and marketing motions are planned.
Cookieless attribution is the practice of measuring which marketing touches contributed to a B2B revenue outcome without relying on third-party cookies, browser fingerprinting, or cross-site tracking. The discipline became operationally urgent as Intelligent Tracking Prevention in Safari, Total Cookie Protection in Firefox, and the evolving Privacy Sandbox proposals in Chrome collapsed the cookie-based attribution model that B2B marketers leaned on for fifteen years. In 2026 the working answer is a layered model combining server-side tracking, first-party identity, deterministic matching where consent allows, modeled attribution, and account-level rather than person-level measurement.
Account tiering is the discipline of segmenting your target account list into priority bands (typically Tier 1, Tier 2, Tier 3) so that resource intensity, motion design, and team coverage scale with revenue potential. In 2026 the discipline has matured beyond static spreadsheets into dynamic tiering, where account assignment to tiers is recomputed continuously from intent signal, firmographic fit, in-pipeline status, and predictive scoring rather than set once at the start of the year and left to drift.
Bombora intent is third-party B2B intent data produced by Bombora, the company that operates the Data Co-Op, a network of business publishers and content sites where buyer behavior is observed across thousands of sources and aggregated into account-level topic surge signals. Bombora measures B2B research patterns at the company level (not the individual level) by tracking content consumption across its co-op, baselining each account's normal research volume, and flagging when an account's volume on a specific topic spikes meaningfully above its baseline. The output is the Bombora Surge Score, a per-account, per-topic signal that signals "this company is researching this topic right now" and is the most widely integrated third-party intent signal in B2B martech.