Lifecycle stage conversion benchmarks describe the typical rate at which leads move from one stage to the next in a B2B SaaS funnel — lead to MQL, MQL to SQL, SQL to opportunity, opportunity to closed won. They’re useful as rough orientation and dangerous as targets, because the numbers depend entir
Every B2B attribution model is wrong; some are useful. How to tell whether yours is lying, and how to use attribution for decisions without pretending it’s accounting.
Attribution doesn’t fail loudly. It just keeps confidently crediting the wrong channels until budget quietly flows to the ones that look good rather than the ones that work. Here are six signs yours is misleading you — and every one of them costs real money, because attribution decides where spend g
CRM cleanup has a hidden risk: fix the data carelessly and you break the reports built on it. Merge records, purge deals, or backfill fields without thinking, and last quarter’s trend suddenly reads differently — and now nobody trusts the numbers even more than before. Here’s how to clean up without
A 90-minute, do-it-yourself CRM data hygiene check — seven measurements that reveal whether your data can support the decisions being made on it.
Marketing attribution is the practice of assigning credit for a closed deal to the marketing touchpoints that influenced it — the channels, campaigns, and content a buyer engaged with on the way to purchase. In B2B, where deals involve many people over many months and dozens of touches, attribution
Ask how much pipeline a typical B2B SaaS company loses to broken process rather than genuine rejection, and the honest answer is: more than anyone measures, because most of it is invisible. The leaks that get counted are the ones that error out. The expensive ones fall silently between systems and n
A win/loss review only earns its place if it changes what you do next. Most don’t — they collect a dropdown reason at close, aggregate it into a chart, and change nothing. Here’s how to run one that actually improves pipeline, step by step, with the trap in each stage.
Reporting trust dies in a predictable order — and has to be rebuilt in reverse. A field guide to getting leadership to believe the pipeline numbers again.
Here’s a real one, anonymised. A leadership team had a headline revenue dashboard — pipeline, forecast, conversion, the lot — and in meetings they’d glance at it, then argue from their own spreadsheets instead. The dashboard existed; nobody trusted it. Let’s take apart why, because untrusted reporti