Your marketing team generated 5,000 leads last quarter. Sales says only 200 were worth calling. Marketing insists the leads were qualified. Sales claims marketing doesn't understand what "qualified" means. Revenue suffers while both teams argue about whose fault it is.
This conflict destroys companies. When marketing and sales can't agree on lead definitions, quality standards, or hand-off processes, opportunities disappear into the gap between teams.
The SiriusDecisions Demand Waterfall framework solves this by establishing a common language and process for managing leads from first touch through closed deals. It's not just a model—it's a system for alignment.
What Is the Demand Waterfall?
The Demand Waterfall, created by SiriusDecisions (now part of Forrester), is a stage-based framework that tracks prospects through defined milestones from inquiry to customer.
The framework identifies specific stages every lead progresses through, with clear definitions for each stage, agreed-upon handoff criteria between stages, and conversion metrics at each transition.
Unlike simple funnel models that show volume dropping at each stage, the Demand Waterfall focuses on velocity and conversion quality. It answers: How fast do leads move between stages? What percentage advance vs. recycle vs. disqualify? Where are the bottlenecks?
Most importantly, it creates shared accountability. Marketing owns certain stages. Sales owns others. Both teams agree on the definitions and criteria, eliminating the "your leads are trash" / "your reps don't follow up" blame game.
The Core Stages of the Demand Waterfall
The original framework has seven stages. Understanding each is critical for implementation.
Inquiry: Someone raises their hand and expresses interest. They download a whitepaper, attend a webinar, request a demo, or engage with your content. They're in your database but haven't been vetted yet.
Marketing Qualified Lead (MQL): An inquiry that meets marketing's quality criteria based on demographics, firmographics, and behavior. Not every inquiry becomes an MQL—some are students, competitors, or unqualified by company size or industry.
Accepted Lead: Sales accepts the MQL as worth pursuing. Some MQLs get rejected by sales because timing is wrong, contact information is bad, or they don't meet sales qualification criteria marketing missed.
Sales Qualified Lead (SQL): Sales confirms the lead has a real need, budget, authority, and timeline. They've had a conversation. This isn't a maybe—it's a real opportunity.
Closed/Won: The deal closes. The lead becomes a customer.
Closed/Lost: The opportunity didn't convert. They chose a competitor, decided not to buy, or lost budget.
Recycled: Leads that aren't ready now but might be later. They go back to marketing for nurturing. Maybe they have need but no budget this quarter, or they're researching for a future project.
Each stage transition has specific criteria. Marketing can't just declare something an MQL because they hit a lead target. Sales can't reject MQLs without documented reasons. The framework requires discipline.
How to Implement the Demand Waterfall
Implementation requires cross-functional agreement before any technology configuration.
Step 1: Define each stage clearly. What specific criteria must a lead meet to qualify as an MQL? Not "engaged with content" but "visited pricing page, downloaded two assets, works at company with 100+ employees in target industry."
Sales and marketing must agree on these definitions together. If marketing creates definitions unilaterally, sales won't respect them.
Step 2: Establish service level agreements (SLAs). How quickly must sales respond to an MQL? 24 hours? 48 hours? How many attempts must they make before recycling a lead?
How quickly must marketing nurture recycled leads before re-scoring them? These SLAs create accountability.
Step 3: Configure your tech stack. Your CRM and marketing automation platform need to track these stages and enforce workflows. When a lead reaches MQL score, it auto-assigns to sales. When sales hasn't touched it in 48 hours, it triggers alerts.
Step 4: Create feedback loops. Sales must document why they reject MQLs. Marketing reviews this feedback monthly to improve targeting and scoring. This turns complaints into continuous improvement.
Step 5: Measure stage conversion rates and velocity. Track percentage of inquiries that become MQLs, MQLs that become accepted leads, accepted leads that become SQLs, and SQLs that close.
Also track time spent in each stage. If leads sit in "Accepted" status for three weeks on average, you have a sales responsiveness problem.
Key Metrics to Track
The Demand Waterfall enables several critical metrics that reveal go-to-market health.
Inquiry-to-MQL conversion rate: What percentage of inquiries meet your quality threshold? If this is too low (under 20%), your top-of-funnel campaigns attract the wrong audience. If too high (over 80%), your MQL criteria might be too loose.
MQL-to-Accepted conversion rate: How many MQLs does sales accept as worth pursuing? If sales rejects over 40% of MQLs, marketing's qualification criteria don't match sales' needs. Fix the definitions.
Accepted-to-SQL conversion rate: Once sales engages, how many leads qualify as real opportunities? Low conversion here means sales is wasting time on leads that seem qualified but aren't, or sales' qualification is too strict.
SQL-to-Close rate: Your standard win rate. Track separately for different lead sources to understand which channels produce higher-quality pipeline.
Velocity metrics: Average days in each stage. Where do leads get stuck? Long time in "Accepted" means sales isn't following up fast enough. Long time in "SQL" means deals aren't progressing.
Recycle rates: How many leads get recycled back to marketing vs. disqualified entirely? High recycle rates might mean you're capturing leads too early in their buying journey.
How Product Marketing Uses the Demand Waterfall
Product marketers should use this framework to improve campaign effectiveness and messaging.
Lead source analysis: Track which content, campaigns, and channels produce leads that progress through stages fastest and convert at highest rates. Double down on those sources.
Messaging refinement: If leads from a specific campaign become MQLs but sales rejects them, your messaging might attract the wrong audience. Adjust positioning to attract better-fit prospects.
Content strategy: Analyze which content offers convert best at each stage. Early-stage content (blog posts, guides) should drive inquiries. Mid-stage content (case studies, webinars) should convert MQLs to accepted leads. Late-stage content (ROI calculators, demo videos) should accelerate SQL to close.
Sales enablement: Share conversion data with sales. Show them which lead sources have highest SQL-to-close rates. They'll prioritize those leads and understand which marketing programs actually drive revenue.
Campaign ROI: Trace closed/won deals back to original inquiry source. Calculate cost-per-SQL and cost-per-customer by campaign. Kill underperforming campaigns and expand winning ones.
Common Implementation Mistakes
Defining too many stages: Some teams create 15 stages with micro-transitions. This creates confusion and measurement overhead. Stick to the core stages until you're mature enough to need more granularity.
Setting unrealistic conversion expectations: Not every inquiry should become an MQL. Not every MQL should close. Understand realistic conversion benchmarks for your industry and sales cycle. B2B enterprise software might see 15% MQL-to-close. Transactional products might see 40%.
Ignoring recycle stage: Many implementations forget about recycled leads. These leads had interest but wrong timing. Nurture them. They often convert better than net-new inquiries because they've already expressed intent.
No sales accountability: If sales can reject MQLs without documentation or never follows up on accepted leads, the framework fails. Sales needs SLAs just like marketing does.
Tech before agreement: Teams configure their CRM to track waterfall stages before agreeing on stage definitions. This creates garbage data. Agreement first, technology second.
Evolving the Model
The traditional Demand Waterfall is 15+ years old. Many companies have evolved it for modern buying patterns.
Some additions worth considering:
Engagement stage: Between inquiry and MQL, track "engaging" leads who aren't yet qualified but show repeated interest. Nurture them differently than cold inquiries.
Account-based stages: If you do ABM, track account-level progression, not just lead-level. An account with three MQLs from different contacts is more valuable than three unrelated individuals.
Product qualified leads (PQLs): For product-led growth companies, add a PQL stage for users who hit activation milestones in your product. These often convert better than traditional MQLs.
Expansion pipeline: Create a separate waterfall for existing customers. The stages differ (usage milestone → expansion conversation → upsell proposal → expansion closed) but the discipline applies.
When to Use the Demand Waterfall
Use this framework when:
- Marketing and sales disagree about lead quality
- You can't trace revenue back to marketing sources
- Leads disappear between marketing and sales handoff
- You need standardized definitions across teams
- You're scaling demand gen and need process
Don't use it when:
- You have pure product-led growth with no sales involvement
- Your sales cycle is entirely self-service
- You're pre-product-market fit and experimenting wildly
The Demand Waterfall requires process maturity. If your go-to-market motion changes weekly, formalize processes before implementing this framework.
Getting Started
Start with a joint workshop between marketing and sales leadership. Document current lead flow, identify where leads get stuck or lost, and define each stage with specific, measurable criteria.
Build SLAs for each stage transition. Configure your CRM to track these stages and enforce workflows. Start measuring conversion rates and velocity.
Meet monthly to review data, identify bottlenecks, and adjust criteria based on what you learn.
The Demand Waterfall isn't just a reporting model. It's a operating system for revenue generation that creates shared language, shared metrics, and shared accountability between marketing and sales.
When both teams use the same definitions, track the same stages, and optimize for the same outcomes, leads stop falling through cracks and revenue becomes predictable.