Model your complete marketing and sales funnel from first visitor to closed customer. See conversion rates, drop-off at each stage, cost per stage and which stages offer the greatest improvement opportunity.
| Stage | Volume | Conv. Rate | Drop-Off | Cost per Stage |
|---|
Every marketing funnel has a biggest leak — one stage where a disproportionate number of prospects are lost. Fixing the biggest drop-off point is almost always more valuable than increasing top-of-funnel traffic. A funnel converting 3% of visitors to leads but only 25% of leads to MQLs might get far more value from improving lead qualification than from increasing traffic spend.
| Stage | Strong | Average | Weak |
|---|---|---|---|
| Visitor to Lead | 4%+ | 2–4% | <2% |
| Lead to MQL | 50%+ | 30–50% | <30% |
| MQL to SQL | 60%+ | 40–60% | <40% |
| SQL to Won | 30%+ | 15–30% | <15% |
| Overall (visitor to customer) | 0.1%+ | 0.05–0.1% | <0.05% |
A funnel tracks the journey of a potential customer from first awareness to purchase. Typical B2B stages: Visitor (website arrival) → Lead (provides contact details) → MQL (meets qualification criteria) → SQL (sales-accepted, ready for direct outreach) → Won (closed customer). Each stage has a conversion rate; the product of all rates equals the overall funnel conversion. Optimising the weakest stage delivers the highest ROI.
MQL (Marketing Qualified Lead): a lead that meets marketing-defined criteria suggesting readiness for sales contact — typically based on demographic fit (ICP match) and behavioural signals (content downloads, page visits, webinar attendance). SQL (Sales Qualified Lead): a lead that sales has reviewed and confirmed as a genuine active opportunity — typically with confirmed budget, authority, need and timeline (BANT criteria).
Compare your stage-by-stage conversion rates against benchmarks. The stage furthest below benchmark is typically your biggest opportunity. Also track which lead sources produce the highest MQL-to-SQL conversion rates — some sources may produce high lead volumes but low quality (low MQL rate). CRM data is essential: track every lead through all stages to identify systematic patterns in where and why prospects drop out.