2025 B2B SaaS Funnel Benchmarks & Pipeline Audit Framework

Marketing and sales teams each have their role to play in this process. The role of sales and marketing teams is to gently guide the lead, using specific tools and strategies for each stage. That’s how conversion rates improve durably — not through a single tactic, but through a continuous diagnostic loop applied to the right metrics.

To improve the handoff, start by creating a shared Ideal Customer Profile (ICP). While better scoring and follow-up can improve results, flaws in the handoff process continue to hurt overall performance. Use score decay – lowering points after 30 days of inactivity – to keep your team focused on warm leads.

When the marketing and sales teams work together, leads can move smoothly from being nurtured by marketing to being engaged by sales. Also, both the marketing and sales teams may have trouble because they can't see their leads’ activity and engagement. Marketing teams might put lead volume and engagement metrics at the top of their list while sales teams focus on things like budget availability and buyer mql vs sql intent. One of the biggest problems is that marketing and sales teams don't always talk to each other.

How Does a Lead Move from MQL to SQL?

Treating the funnel as ending at closed-won leaves the most leveraged growth motion unmapped. TOFU, MOFU, and BOFU are the practitioner shorthand for the first three stages. Answer Engine Optimization (AEO) is becoming a parallel investment alongside traditional SEO for awareness-stage content.

At a glance: Here’s how MQLs and SQLs differ

Many leads can be categorized under an MQL (marketing qualified lead) or an SQL (sales qualified lead). Instead of banging the gavel one way or another, we hope this invites you to think deeper about the metrics you’re accountable for and how they drive real business outcomes. For some software companies, this could mean a combination of different metrics that are all tracked and measured via multi-touch attribution modeling. When you hold marketers and salespeople accountable to different metrics, even though both teams are technically responsible for the same goal of generating revenue, it creates a rift. The next few days are spent following up and trying to get a hold of these people to schedule a qualifying intro call. Once a lead becomes a MQL, the next step is to have it carefully vetted by a member of the sales team.

MQLs and SQLs occupy different stages of the buyer journey, which affects ownership, goals, and the type of outreach that makes sense. They consume content independently, attend webinars without requiring personal interaction, and explore resources at their own pace. SQLs drive predictable revenue because both marketing and sales have vetted them. These factors separate SQLs from MQLs who might be interested but can’t actually buy yet. Sales and marketing teams often struggle not because leads are scarce, but because qualification is unclear.

• Start by analyzing historical data to identify which behaviors and characteristics correlate with closed-won deals and inform how you generate sales leads.
• These factors carry higher weights because they directly correlate with purchase probability.
• These factors separate SQLs from MQLs who might be interested but can’t actually buy yet.
• Features like Milestones visually map the journey from MQL to SQL, showing exactly which actions or content drive progression between stages.

Win Rate Benchmarks Across Segments

Then, your sales and marketing teams need to determine what lead score threshold will automatically move someone to the next stage of the sales funnel. Proper lead scoring requires sales and marketing teams to work together. Prior to the implementation of lead scoring systems, sales teams determined whether someone was interested in purchasing simply by a gut feeling or paying attention to certain positive indicators.

Start by analyzing historical data to identify which behaviors and characteristics correlate with closed-won deals and inform how you generate sales leads. Downloading one awareness-stage blog post shows minimal interest. Effective marketing qualified lead identification requires analyzing patterns across multiple data points to spot prospects demonstrating genuine interest. If 100 MQLs typically produce 30 SQLs and 10 closed deals, future pipeline can be projected with confidence based on current volume. When marketing tracks qualification consistently, campaigns can be evaluated based on the quality of pipeline they generate, not just surface-level engagement. Clear qualification creates a single revenue system instead of separate sales and marketing motions.