Most marketing teams track the metrics that are easy to pull — website visits, leads, email open rates. The problem is that easy-to-pull metrics do not tell you what is working. They tell you what is happening at the top of the funnel while leaving the bottom, where revenue actually is, completely dark.
Here are the funnel metrics that matter at each stage, what they tell you, and how to connect them into a picture that actually drives decisions.
The funnel stages and what to measure at each one
Awareness: are the right people finding you?
Awareness metrics tell you how much reach your marketing has and whether that reach is hitting your target audience.
- Organic impressions (Google Search Console): How many times your pages appeared in search results. Impressions are a leading indicator — growth here precedes traffic growth by weeks or months.
- Paid impressions and reach: How many unique people your ads reached. For awareness campaigns, reach matters more than clicks.
- Branded search volume: How often people search your company name. Rising branded search is a signal that your awareness campaigns are working — people are looking you up after seeing your content or ads.
- Share of voice: Your brand’s presence relative to competitors in search results or social. If your competitors are gaining ground, you will see it here before it shows up in revenue.
What awareness metrics cannot tell you: whether the people you reached were the right people. High impressions from the wrong audience are a cost with no return.
Interest and consideration: are they engaging with what you show them?
- Click-through rate (CTR): The percentage of people who clicked after seeing your ad or search result. Low CTR on a high-impression term means your title tag, meta description, or ad copy is not compelling enough. The impression volume is there — the message is not landing.
- Engagement rate: On paid social, the percentage of people who interacted with your content (click, like, share, save). Useful for comparing creative performance.
- Pages per session and session duration: From GA4. Visitors who read multiple pages or spend meaningful time are demonstrating actual interest, not just accidental clicks.
- Return visitor rate: The percentage of your traffic that is coming back. First visits are curiosity. Return visits signal consideration.
Conversion: are they taking the action you want?
- Lead conversion rate: The percentage of visitors who submit a form, call, or otherwise identify themselves as a lead. A 1–3% session conversion rate is typical for B2B sites. Below 1% means either the traffic is wrong or the offer is not compelling.
- Cost per lead (CPL): Total ad spend divided by leads generated. Useful for benchmarking channel efficiency — but only tells you about the lead, not about what happens to it.
- Lead-to-SQL conversion rate: What percentage of your leads are actually sales-qualified? High lead volume with low SQL rate means your targeting or messaging is attracting the wrong people. This is where marketing and sales alignment breaks down.
- Form completion rate: The percentage of people who start your form and actually finish it. A high drop-off rate points to a form that is too long, asks for sensitive information too early, or creates friction on mobile.
Close: are leads becoming revenue?
This is the stage most marketing teams have no data on — because it lives in the CRM and sales process, not in Google Analytics.
- SQL-to-close rate: What percentage of sales-qualified leads become customers. If this drops, the problem is either in the sales process or in lead quality (marketing is sending the wrong SQLs).
- Average deal value: What is the average revenue per closed deal? Combined with close rate, this tells you the value of each SQL and — working backward — the value of each lead and each marketing touchpoint.
- Sales cycle length: How many days from first lead to closed deal? For B2B, this can range from a few days to six months or more. The sales cycle length determines the right attribution window for your marketing measurement.
- Revenue by source: Which channels and campaigns are producing the most revenue — not just the most leads? This is the metric that changes budget decisions, and it is only available when you connect marketing data to closed deal data.
The gap most teams have
Marketing teams almost universally measure awareness (impressions, traffic) and conversion (leads). They rarely measure close (revenue by source).
The result: teams optimize toward CPL because that is what they can measure. But CPL optimization does not maximize revenue. A channel with a high CPL but a high close rate and high deal value will always beat a low-CPL channel with weak leads — and you will never know it if you are only looking at lead volume.
This is why revenue attribution matters more than lead attribution. You need to know what each marketing dollar produced in closed revenue, not just which campaign generated the most form fills.
How to connect the funnel
Connecting marketing to revenue requires passing data across systems that typically do not talk to each other:
- Track the original source on every lead. When a form submits, capture the UTM parameters, referral source, and channel that brought that visitor. Store this in your CRM alongside the lead record. Lead source tracking on WordPress covers the mechanics of how to do this without a developer.
- Follow leads through the pipeline. As leads move through deal stages in your CRM, the source data travels with them. A lead that came from a Google Ads click on a non-brand keyword in September becomes an SQL in October and a closed deal in November — and that chain of attribution needs to be preserved.
- Report revenue, not leads, back to your channels. When a deal closes, import that revenue event back to Google Ads and Meta as an offline conversion. This closes the loop — Smart Bidding now knows which clicks actually produced revenue, not just which clicks produced form fills.
Benchmarks by funnel stage
These are general B2B benchmarks. Your numbers will vary significantly by industry, price point, and traffic quality.
| Metric | Typical B2B range | What it signals if low |
|---|---|---|
| Organic CTR (position 1–3) | 15–30% | Title tags or meta descriptions not compelling |
| Paid search CTR | 3–8% | Ad copy or offer needs work |
| Landing page conversion rate | 2–5% | Offer, form, or trust signals need improvement |
| Lead-to-SQL rate | 20–40% | Wrong audience or wrong message |
| SQL-to-close rate | 20–30% | Sales process or lead quality problem |
Attribution across the funnel
One reason B2B funnel measurement is hard is that the touchpoints that create awareness (blog content, social, display) rarely get credit for the revenue they contribute. Last-click attribution — still common — gives all credit to the final ad click before conversion and none to the content that built trust over the prior weeks.
This is the core argument for multi-channel attribution: the funnel has multiple stages, and so should your attribution model. Different models (linear, time decay, position-based, data-driven) distribute credit differently across the path — and choosing the right one for your sales cycle is part of measuring the funnel accurately.
The goal is a measurement system where every stage of the funnel is visible, connected to the stages before and after it, and tied ultimately to revenue rather than to a lead count. Teams that build this report see clearly where they should invest more and where the spend is not producing results — and they move budget accordingly.