Revenue leaders today are under more pressure than ever to prove marketing and sales impact on business outcomes. Yet, too often, go-to-market (GTM) teams celebrate surface-level success—MQLs, website traffic spikes, or email open rates—while missing the bigger picture: Are these metrics driving revenue?
The reality is that vanity metrics create a false sense of achievement, leading to misalignment between Marketing, Sales, and Customer Success. While Marketing touts high engagement numbers, Sales is focused on closing deals, and Customer Success struggles to retain and expand accounts. Without a clear, data-driven approach to measuring GTM performance, organizations risk stalled pipeline growth and unpredictable revenue outcomes.
Let’s break down how to move beyond vanity metrics and build a GTM dashboard that provides true revenue insights. We’ll cover:
- Why traditional vanity metrics fail to provide real GTM insights (and why we should stop pretending they do).
- The essential metrics every data-driven GTM dashboard should track.
- How to structure a dashboard that aligns marketing, sales, and customer success.
- The tools and frameworks for effective GTM measurement.
- Common mistakes to avoid when building a GTM dashboard (because we’ve all made them).
By the end, you’ll have a clear framework for measuring what truly matters: helping your GTM teams drive more predictable, scalable revenue. Let’s dive in.
Why Traditional Vanity Metrics Fail in GTM Strategy
For years, marketing and sales teams have relied on traditional demand generation metrics like MQLs, website traffic, and email open rates to measure success. In tandem, sales teams have looked at those metrics and thought, Cool, but where’s the pipeline?
Here’s why vanity metrics don’t tell the full story when it comes to GTM success:
MQLs → Individual-Centric vs. Account-Centric
MQLs (Marketing Qualified Leads) were the gold standard of marketing success. That is, until we realized that buying decisions in B2B don’t happen because one person downloaded an eBook.
Why It Fails:
- An MQL may show high engagement, but if the full buying committee isn’t engaged, the deal is going nowhere fast.
- Sales teams often deprioritize MQLs because they don’t reflect an account-based motion.
- Optimizing for MQLs can lead to fragmented marketing efforts.
Better Metric: Account Engagement Score
- Measures total engagement from a target account, ensuring that marketing and sales are moving the entire buying group forward.
Website Traffic → High Volume, Low Buyer Intent
More website traffic sounds great, until you realize most of it is from bots, job seekers, or people just looking for your latest blog post, not your product.
Why It Fails:
- Traffic spikes don’t equal pipeline growth. A surge in traffic sounds great—until you realize most of it is bots and people who bounced after five seconds.
- Channel quality matters. Paid campaigns may bring visitors, but if they’re not converting into target accounts, they’re just expensive window shoppers.
Better Metric: Pipeline Contribution by Target Accounts
- Tracks the percentage of pipeline sourced or influenced by marketing from high-value accounts.
Paid Media Clicks & CTR → Engagement Without Revenue Impact
High click-through rates (CTR) might look great on a report, but if those clicks aren’t coming from decision-makers, they’re just expensive noise.
Why It Fails:
- Optimizing for clicks alone can attract unqualified traffic, leading to wasted budget and an inbox full of demo requests from students writing their thesis.
- CTR doesn’t tell you if the right personas are engaging—just that someone, somewhere, clicked an ad.
Better Metric: Multi-Stakeholder Engagement
- Measures whether key decision-makers within an account are engaging with your marketing and sales content.
Email Open & Click Rates → Visibility Without Actionable Insights
Let’s be real: Open rates can be inflated by spam filters, email previews, and overzealous subject lines.
Why It Fails:
- Email opens ≠ intent to buy. Sometimes people just click by accident while trying to delete.
- Clicking a link doesn’t mean they’re ready to buy. Maybe they were just curious about your CTA button color.
Better Metric: Sales Qualified Account (SQA) Rate
- Instead of tracking individual email clicks, measure when an entire account has engaged across multiple touchpoints and is actually ready for sales outreach.
Tools & Frameworks for GTM Measurement
Even the best GTM strategy falls apart without the right tools and frameworks. You wouldn’t try to build a house with just a hammer, so why try to measure revenue impact with a messy spreadsheet and wishful thinking?
Here’s how to equip your GTM team with the right tech stack and measurement frameworks to turn data into decisions.
The Must-Have Tools for a Data-Driven GTM Dashboard
CRM (Your System of Record)
- Salesforce, HubSpot – The backbone of your GTM data, but only as good as its data hygiene. If it’s full of duplicate accounts, outdated contacts, and deals marked “Closed-Lost (but maybe later?),” you have a problem.
BI & Analytics (Turning Data Into Insights)
- Looker, Tableau, Power BI – For slicing and dicing pipeline, revenue trends, and GTM efficiency. Just make sure your dashboard doesn’t become a graveyard of unread reports.
Revenue Intelligence (Seeing the Real Story in Pipeline & Deals)
- Clari, Gong – Helps forecast revenue based on real buyer engagement, not just sales rep optimism.
Marketing Attribution (Tracking What Actually Drives Revenue)
- Usermaven, Dreamdata, Ruler Analytics, HubSpot – Ties marketing activities to revenue outcomes. Because “source: organic” doesn’t tell you if a blog post or a well-timed LinkedIn post actually brought in the deal.
Account Engagement & Intent Data (Prioritizing the Right Accounts)
- 6sense, Demandbase, ZoomInfo Intent – Tells you which accounts are actually in-market so your GTM teams can stop chasing ghosts.
Key Frameworks for Measuring GTM Success
The North Star Metric (NSM) Model
- Focuses on a single metric that best represents long-term business value. (e.g., ARR growth, expansion revenue, or customer retention.)
- Best for aligning GTM teams around one unifying success measure.
The Bowtie Funnel Model
- Moves beyond MQL → SQL → Closed-Won to track post-sale metrics like retention and expansion.
- Best for subscription-based and customer-led growth models.
The AARRR Framework (a.k.a. Pirate Metrics)
- Acquisition → Activation → Retention → Revenue → Referral
- Helps break down full-funnel performance across marketing, sales, and customer success.
The Full-Funnel ABX Model
- Focuses on account engagement, multi-threading, and pipeline contribution from ABM plays.
- Best for B2B teams using account-based go-to-market strategies.
Common Mistakes & Best Practices
Building a GTM dashboard is not just about throwing some charts together and calling it a day. A poorly designed dashboard can cause more confusion than clarity, leading teams to make decisions based on misleading or incomplete data.
Let’s break down the biggest mistakes GTM teams make and how to avoid them.
Mistake #1: Overloading the Dashboard with Too Many Metrics
Just because you can track something doesn’t mean you should. A cluttered dashboard with 20+ metrics becomes noise instead of insight.
The Problem:
- Decision-makers get overwhelmed and stop using the dashboard.
- Teams focus on vanity metrics instead of revenue-driving KPIs.
- It’s impossible to tell what’s actually moving the needle.
Best Practice:
- Stick to 5-7 core KPIs per team (Marketing, Sales, RevOps, Customer Success).
- Prioritize actionable metrics that help GTM teams make decisions.
Mistake #2: Ignoring Data Hygiene (a.k.a. Garbage In, Garbage Out)
Your GTM dashboard is only as good as the data feeding it. If your CRM is a mess, your dashboard will be, too.
The Problem:
- Duplicate, outdated, or incomplete data leads to incorrect insights.
- Reps manually enter data inconsistently, making reporting unreliable.
- Teams distrust the dashboard, leading to constant “Is this data right?” debates.
Best Practice:
- Implement strict data governance to maintain accuracy.
- Use automation and AI-powered tools to reduce manual entry errors.
- Conduct regular data audits (at least quarterly) to clean up the CRM.
Mistake #3: Focusing Only on Lagging Indicators
If your dashboard only tracks closed-won revenue, win rates, and churn, you’re looking in the rearview mirror instead of optimizing in real-time.
The Problem:
- You react to problems too late instead of preventing them.
- It’s hard to diagnose why pipeline isn’t converting.
- Sales and marketing teams can’t adjust until it’s already too late.
Best Practice:
- Balance leading and lagging indicators to predict revenue trends.
- Track account engagement, multi-threading, and sales velocity to catch pipeline risks early.
- Use intent data and buying signals to optimize outreach before deals stall.
Mistake #4: Lack of Alignment Between Marketing, Sales & CS
Your GTM dashboard should be a unifying source of truth—not a battleground where every team fights over which numbers matter.
The Problem:
- Marketing tracks MQLs, Sales tracks opportunities, and Customer Success tracks renewals—none of which align.
- No shared view of pipeline health across the customer journey.
- Different teams report different numbers to leadership, creating confusion.
Best Practice:
- Use an account-centric approach to measure full-funnel performance.
- Align all teams on pipeline contribution, multi-stakeholder engagement, and revenue efficiency.
- Create one shared dashboard with clear ownership and accountability.
Mistake #5: Making the Dashboard Too Hard to Access & Use
A dashboard that requires a PhD in data science (or 15 minutes of digging through reports) will never be widely adopted.
The Problem:
- Teams don’t check the dashboard regularly.
- Leadership only sees the data during QBRs or board meetings.
- Insights aren’t used for real-time decision-making.
Best Practice:
- Keep dashboards simple, visual, and easy to navigate.
- Automate updates so teams always have real-time data.
- Make dashboards accessible in key tools (CRM, Slack, email reports) so they’re used daily.
Stop Tracking Metrics That Don’t Move Revenue
The days of celebrating MQLs, website traffic, and click-through rates as success metrics are over. If your GTM teams are still relying on vanity metrics, it’s time for an upgrade.
A data-driven GTM dashboard should:
- Align marketing, sales, and customer success around revenue impact, not just engagement.
- Prioritize pipeline efficiency and conversion metrics over top-of-funnel vanity numbers.
- Balance leading and lagging indicators to spot revenue risks early.
- Leverage the right tech stack and frameworks to turn data into action.
What’s Next?
The best GTM teams aren’t just tracking metrics—they’re using data to drive predictable revenue.
