B2B growth wiki

B2B growth can feel like a foreign language when every slide deck shouts LTV:CAC, ABM, PLG, ICP, and a dozen other acronyms before you have even brewed the coffee. After fifteen years translating that jargon into actionable plans for sales, marketing, and product teams, I decided to publish the plain-English explanations I wished I had on day one.

This wiki is the result: a living glossary that strips each term back to its job-to-be-done, adds practical examples, and links out to tools or frameworks that help you apply it. Articles are grouped by topic—demand generation, revenue operations, product-led growth, and so on—so you can dive straight into the area you are mastering without wading through unrelated theory.

My aim is simple. Whether you are an intern drafting your first campaign brief or a specialist moving sideways into growth, you should be able to land here, decode a term in thirty seconds, and return to work wiser and faster. No buzzword bingo, no filler, just the essentials and the context you need to use them confidently.

B2B growth wiki: the complete plain-English glossary

The B2B Growth Wiki exists to cut through the noise that clutters modern marketing conversations. Every definition is written from the vantage point of a growth leader who has spent over a decade turning strategy into pipeline for service firms, SaaS vendors, and professional-services consultancies. That means you get more than a textbook label—you receive the back-story that explains why a term matters, when it enters the conversation, and where it fits inside a revenue engine.

The structure of each article follows a deliberate pattern. First comes a concise description in everyday language, free of marketing-speak. Next you will find the metric or outcome that validates whether the concept is doing its job; for example, lead-to-opportunity conversion for MQL versus SQL, or net expansion revenue for account-based marketing. Then I lay out common pitfalls observed across dozens of implementations, so you avoid recycled mistakes. Finally, there is a short list of recommended reading and, where relevant, links to tool guides in the companion Toolstack section.

Grouping the articles by theme serves two purposes. It mirrors the way organisations build functions—demand generation, lifecycle nurture, data operations—and it surfaces hidden dependencies, such as how your intent-data strategy should shape scoring rules inside a CRM. This thematic approach also aligns with how search intent clusters, which improves the wiki’s visibility for queries like “what is a growth loop” or “difference between CAC and CPA”. By interlinking related entries I create clear topic clusters that help search engines map authority while giving readers intuitive navigation paths.

Because language evolves, so does the wiki. I review new jargon quarterly, add emerging terms from analyst reports and community forums, and retire buzzwords that have lost practical relevance. Each update cycle checks for overlaps and synonym drift to keep the glossary tight and coherent. If you come across a phrase in the wild that is missing here, drop me a note via the contact form; crowd-sourced reality checks ensure the content stays grounded.

For learners, the greatest obstacle is often context switching: one moment you are deciphering T-shaped funnel models, the next you are debugging UTM taxonomy. The wiki’s internal search and anchor links minimise that friction. You can move from a high-level concept like product-market fit to a tactical element such as North Star metrics in two clicks, preserving focus and speeding up comprehension.