Every B2B company has a sales funnel, whether or not it is written down. Buyers move from first contact to a conversation, an evaluation, a proposal and a decision. Writing the funnel down, with clear definitions and a conversion formula for each stage, turns it from a diagram into a management tool: you can see where buyers drop out, compare channels and forecast how much activity you need to hit a revenue target. This article defines the common stages of a B2B sales funnel, gives a formula for each conversion, explains how to measure by cohort and shows how the funnel differs for inbound, outbound and product-led motions.
The common stages
Names vary, but most B2B funnels include these stages. Visitor or prospect: someone who visits the website or is identified as a potential buyer. Lead: someone who has shared contact details, for example by filling in a form, booking a demo or replying to outreach. Marketing qualified lead (MQL): a lead that meets agreed criteria for fit and interest. Sales qualified lead (SQL) or meeting: a lead sales has accepted and spoken to, confirming a potential need. Opportunity: a qualified deal with a real problem, a buying process and an expected value. Proposal: a deal where a formal proposal or quote has been shared and discussed. Closed won or lost: the outcome. Some companies skip the MQL stage, particularly when every inbound demo request goes straight to sales.
Write a definition for every stage
Conversion rates only mean something if each stage is defined precisely. Write down, for each stage, what must be true for a record to enter it and who decides. For example: an MQL is a lead from a company within the target size range and industry that has requested a demo or engaged with pricing content; an SQL is an MQL that a salesperson has spoken to and confirmed has a relevant problem and the authority or influence to buy. Agree the definitions between marketing and sales, record them in the CRM as stage or status values, and apply them consistently. The article on pipeline stage exit criteria covers the opportunity stages in more detail.
Conversion formulas
Each conversion rate is the share of records that enter one stage and go on to reach the next. Measure them by cohort, as described below.
| Conversion | Formula | What it tells you |
|---|---|---|
| Visitor to lead | Leads ÷ unique visitors (or target accounts reached) | How well the website or outreach converts attention |
| Lead to MQL | MQLs ÷ leads, same cohort | Share of leads that fit and show interest |
| MQL to SQL | SQLs ÷ MQLs, same cohort | Lead quality and sales follow-up |
| SQL to opportunity | Opportunities ÷ SQLs, same cohort | Qualification accuracy |
| Opportunity to proposal | Proposals ÷ opportunities, same cohort | Progress through evaluation |
| Proposal to won | Won ÷ proposals, same cohort | Closing effectiveness and pricing fit |
| Opportunity win rate | Won ÷ (won + lost) for opportunities created in the period | Overall sales effectiveness |
Measure by cohort, not by period
A common mistake is to divide the number of SQLs in a month by the number of MQLs in the same month. If MQLs take several weeks to become SQLs, the two figures refer to different groups of people, and the rate swings with lead volume rather than quality. Cohort measurement fixes this: take all leads created in a given month and measure what share of them reached each later stage, allowing enough time for them to progress. Cohort rates take longer to settle, but they are far more reliable for decisions. For quick weekly monitoring, period-based rates are acceptable as long as everyone knows their limits.
Add time between stages
Conversion rates tell you how many buyers progress; time between stages tells you how fast. Track the median number of days from lead to SQL, SQL to opportunity, and opportunity to close. Long gaps at a particular stage often reveal a bottleneck: slow follow-up after a form fill, a delay between demo and proposal, or procurement steps that take longer than planned. Time also matters for forecasting, because a funnel with good conversion rates but long stage durations produces revenue later than expected.
Inbound, outbound and product-led funnels
The stages differ by sales motion. Inbound funnels start with website visitors and forms, and the MQL stage is useful for filtering. Outbound funnels start with target accounts and contacts; the early stages are contacted, replied and meeting booked, and the conversion that matters most is from meeting to opportunity. Product-led funnels start with sign-ups and add product stages such as activated, meaning the user reached a key action, and product-qualified, meaning usage suggests a likely buyer, before sales gets involved. Track each motion as a separate funnel, because their conversion rates and costs differ widely, and averaging them hides problems in each.
Using the funnel to plan
Once you have reliable rates, work the funnel backwards from the revenue target. Divide the revenue target by the average deal size to get the number of deals needed, then divide by each conversion rate in turn to find how many opportunities, SQLs, MQLs and leads you need. Compare the result with your current volumes and capacity. The gap tells you whether to focus on more leads, better conversion at a particular stage or larger deals. The conversion funnel calculator and the marketing pipeline targets article on this site walk through the method.
Common mistakes
Undefined stages, so each rep or marketer counts differently. Mixing inbound, outbound and partner deals in one funnel. Measuring by period rather than cohort. Counting stages that the CRM cannot record reliably. Treating conversion rates from benchmarks as targets without checking your own history. And reviewing the funnel only quarterly, which leaves problems undetected for months. A monthly review of cohort conversion and stage timing with marketing and sales catches most issues early.
Setting up the funnel in your CRM
The funnel only works if the CRM records each stage reliably. For leads, use a lifecycle stage or lead status field with values matching your definitions, and record the date each stage was reached, because cohort analysis depends on those dates. HubSpot records the date a contact enters each lifecycle stage automatically; in Zoho CRM and other systems you may need workflow rules to stamp a date field when a status changes. For opportunities, use deal stages with exit criteria and stage dates. Make sure every record carries an original source that cannot be overwritten casually, so funnels can be split by inbound, outbound and partner. Build a single report that shows each cohort's progression through the stages, and use it in the monthly review rather than rebuilding the analysis in spreadsheets each time.
Building a funnel report the team will use
A funnel report is most useful when it answers the same few questions every month: how many records entered each stage, what share moved on, how long they took, and how this compares with the previous period and plan. Show cohorts by month of lead creation in rows and stages in columns, with conversion rates between them and median days in stage. Split by source and by motion, such as inbound, outbound and partner. Add a short commentary on the biggest change and its likely cause. Share the same report with marketing and sales, so that both teams discuss one set of numbers. Over time, the history in this report becomes the basis for setting realistic targets and for spotting problems early, because a fall in one stage's conversion shows up within weeks rather than at the end of a quarter.
FAQ
Commonly visitor, lead, marketing qualified lead, sales qualified lead or meeting, opportunity, proposal and closed won or lost. Names vary by company and motion.
Divide the number of records reaching the next stage by the number entering the current stage, for the same cohort, such as leads created in one month.
Because stages take time. Dividing this month's SQLs by this month's MQLs compares different groups and swings with volume rather than quality.
It can be for inbound funnels with many leads of varying fit. Where every inbound request goes straight to sales, some companies drop it.
Yes. Their stages, conversion rates and costs differ, and combining them hides problems in each.
Long enough for most of the cohort to have progressed, usually at least your typical time between those stages. Mark recent cohorts as incomplete in the report.