Your demand gen dashboard shows 10,000 impressions, 500 clicks, and 50 leads. Your CEO asks: "Did we make money?"
You don't have an answer.
Most demand gen measurement tracks activity metrics (clicks, opens, downloads) instead of business outcomes (pipeline, revenue, ROI). Activity metrics are easy to track but don't prove value.
Here's how to measure campaigns in ways that actually drive accountability and improve decision-making.
Why Most Campaign Measurement Fails
Common failure patterns:
Vanity metric obsession. You report on email open rates, social media engagement, and website traffic. None of these directly correlate with revenue. They're activity indicators, not business outcomes.
No clear goals. You launch a campaign without defining what success looks like. Then you cherry-pick metrics that make the campaign look good. That's not measurement—that's rationalization.
Attribution theater. You claim credit for every deal that touched your campaign, even if the campaign had minimal influence. Sales closed a deal with an account that once attended your webinar six months ago? You count it as campaign-sourced. That's not accurate attribution.
Point-in-time measurement. You measure campaign performance one week after launch and declare success or failure. But B2B buying cycles are months-long. Early metrics don't predict final outcomes.
No comparative analysis. You report that Campaign A generated 100 leads. Is that good? You don't know because you're not comparing to past campaigns, other channels, or industry benchmarks.
The teams that measure well do something fundamentally different: they define clear goals, track business outcomes, use rigorous attribution, and optimize based on data.
The Campaign Measurement Framework
Every campaign needs three levels of metrics:
Level 1: Activity metrics (leading indicators). These show if the campaign is reaching people: impressions, clicks, opens, visits. Useful for troubleshooting execution issues but don't prove business value.
Level 2: Engagement metrics (progress indicators). These show if people are interested: content downloads, form fills, webinar attendance, demo requests. Better than activity metrics but still don't prove revenue impact.
Level 3: Business outcome metrics (lagging indicators). These show if the campaign drives business results: pipeline created, opportunities won, revenue generated, ROI. This is what executives care about.
Most teams stop at Level 1 or 2. Winners measure all three levels but optimize for Level 3.
Defining Campaign Goals
Before you launch any campaign, define success criteria.
Framework: Goal → Target → Timeframe.
Example 1 (Brand awareness campaign):
- Goal: Increase awareness among enterprise CMOs
- Target: 5,000 qualified impressions, 10% engagement rate
- Timeframe: 30 days
- Secondary goal: 20 new accounts added to nurture
Example 2 (Pipeline generation campaign):
- Goal: Generate qualified pipeline
- Target: $500K in new pipeline, 20 opportunities created
- Timeframe: 90 days post-launch
- Secondary goal: 15% MQL-to-SQL conversion rate
Example 3 (Account acceleration campaign):
- Goal: Move stalled opportunities forward
- Target: 30% of targeted accounts take next action (demo, pricing review)
- Timeframe: 45 days
- Secondary goal: Reduce average sales cycle by 20%
Notice how goals are specific, measurable, and tied to business outcomes—not just activity.
Set targets based on historical performance, industry benchmarks, or minimum ROI thresholds. If you have no baseline, estimate conservatively and refine as you gather data.
The Metrics That Actually Matter
Here are the metrics worth tracking for different campaign types:
Content marketing campaigns:
- Downloads (engagement)
- Download-to-MQL conversion rate (business outcome)
- Content-influenced pipeline (business outcome)
- Cost per MQL (efficiency)
- Pipeline velocity for content-engaged leads (business outcome)
Email campaigns:
- Open and click rates (activity)
- Click-to-conversion rate (engagement)
- Email-sourced opportunities (business outcome)
- Revenue influenced by email touches (business outcome)
- Unsubscribe rate (health metric)
Paid media campaigns:
- Impressions and clicks (activity)
- CTR and CPC (efficiency)
- Conversion rate (engagement)
- Cost per MQL and cost per SQL (efficiency)
- ROI and ROAS (business outcome)
Event campaigns:
- Registrations and attendance (engagement)
- Qualified conversations (engagement)
- Meetings scheduled (engagement)
- Pipeline created (business outcome)
- Cost per opportunity (efficiency)
ABM campaigns:
- Account engagement score (engagement)
- Coverage % (reach)
- Accounts creating pipeline (business outcome)
- Win rate for engaged accounts (business outcome)
- Account LTV (business outcome)
The common thread: always track both efficiency metrics (cost per X) and outcome metrics (pipeline, revenue).
Attribution Models That Actually Work
Attribution is hard in B2B because buying journeys are complex. Here's how to approach it:
First-touch attribution: Credits the first campaign that brought a lead into your system. Useful for understanding what drives awareness but ignores everything that happens after.
Last-touch attribution: Credits the last campaign before conversion. Useful for understanding what closes deals but ignores the nurture journey.
Multi-touch attribution: Credits all campaigns that touched a deal based on weighted contribution. More accurate but requires sophisticated tooling and clean data.
The pragmatic approach: Use different models for different questions.
- First-touch for lead source analysis: "Which campaigns generate new names?"
- Last-touch for conversion analysis: "Which campaigns drive final conversions?"
- Multi-touch for campaign ROI: "Which campaigns contribute most to closed revenue?"
Don't obsess over perfect attribution. Approximate attribution that informs decisions beats perfect attribution that's too complex to use.
Tracking Pipeline and Revenue
This is where demand gen proves its value.
Pipeline created: Opportunities created within 90 days of campaign engagement. Track by campaign, channel, and segment.
Pipeline influenced: Opportunities that engaged with the campaign at any point in their journey, even if the campaign didn't source them. Influenced pipeline is typically 3-5x sourced pipeline.
Win rate: What percentage of campaign-sourced opportunities close? If your campaign generates 100 opps but wins zero, lead quality is broken.
Average deal size: Are campaign-sourced deals larger or smaller than average? Smaller deals might indicate lower-quality leads or wrong targeting.
Sales cycle length: Do campaign-sourced deals close faster or slower? Faster = campaign educated prospects effectively. Slower = prospects weren't ready.
Revenue generated: Closed-won revenue attributed to the campaign. This is the ultimate metric. Everything else is directional.
Set up dashboards that track these metrics by campaign over time. You want trend lines, not point-in-time snapshots.
Cost and ROI Calculation
Track full campaign costs, not just media spend.
Total campaign cost includes:
- Media spend (ads, syndication, sponsorships)
- Content creation (writers, designers, agencies)
- Tool costs (platforms, data, analytics)
- Team time (FTE cost allocated to campaign)
- Event costs (venue, travel, swag)
Most teams underestimate campaign costs by 30-50% because they forget team time and tool costs.
ROI calculation:
Marketing ROI: (Revenue - Campaign Cost) / Campaign Cost
Example: Campaign cost $50K, generated $200K in revenue → ($200K - $50K) / $50K = 3:1 ROI.
Target 3:1 minimum for mature campaigns. Early campaigns or brand campaigns might be lower.
Payback period: How long until revenue generated exceeds campaign cost? Track this over time (30 days, 60 days, 90 days). Target 90-180 days for most B2B campaigns.
Dashboard and Reporting Structure
Build dashboards that serve different audiences:
Executive dashboard (monthly):
- Total pipeline generated
- Total revenue influenced
- Marketing ROI
- Trend lines (are we improving?)
Keep it simple. One page, five metrics max.
Campaign manager dashboard (weekly):
- Campaign-by-campaign performance
- Funnel conversion rates
- Cost efficiency metrics
- Comparison to targets
This informs tactical decisions: pause underperforming campaigns, double down on winners.
Channel dashboard (monthly):
- Performance by channel (email, paid, events, content)
- Comparative ROI
- Allocation recommendations
This informs strategic decisions: budget allocation, channel mix.
Use tools like Looker, Tableau, or built-in dashboards in Salesforce/HubSpot. Don't build complex custom dashboards that nobody maintains.
Testing and Optimization Cadence
Measure continuously, optimize systematically.
Real-time monitoring: Check activity metrics (clicks, opens) daily in the first week. Catch execution issues early (broken links, wrong targeting).
Weekly optimization: Review engagement metrics (conversion rates, cost per lead). Pause underperforming ads, adjust targeting, tweak copy.
Monthly performance reviews: Review business outcome metrics (pipeline, opportunities). Decide: continue, optimize, or kill campaigns.
Quarterly strategic reviews: Compare channel performance, ROI trends, and pipeline contribution. Adjust annual budget allocation based on what's working.
Don't optimize too fast (you need statistical significance) or too slow (you waste budget on underperformers).
Common Measurement Mistakes
Mistake 1: Measuring too early. B2B campaigns need 60-90 days to show pipeline impact. Don't judge a campaign after two weeks.
Mistake 2: Not segmenting results. "The campaign generated 100 leads" tells you nothing. Segment by: company size, industry, job title, geography. You'll find that campaigns work for some segments and fail for others.
Mistake 3: Ignoring qualitative feedback. Numbers don't tell the whole story. Talk to sales: "Are campaign leads any good?" Talk to customers: "How did you find us?"
Mistake 4: Analysis paralysis. You have 47 metrics in your dashboard. Nobody can make decisions from that. Focus on the 5-7 that matter most.
Mistake 5: No action from insights. You measure everything, identify underperformers, then... do nothing. Measurement only creates value when it drives decisions.
The Reality
Perfect measurement doesn't exist in B2B demand gen. Attribution is messy, buyer journeys are complex, and some value is impossible to quantify.
But teams that define clear goals, track business outcomes, use reasonable attribution, and optimize based on data dramatically outperform teams that track vanity metrics and guess at what's working.
Measure what matters. Optimize continuously. Kill what doesn't work. Scale what does.
That's how demand gen becomes accountable and earns its seat at the executive table.