If you’re trying to figure out if your Go-To-Market (GTM) efforts are actually working, you need data you can trust—fast. Out-of-the-box dashboards rarely cut it. The good news? Custom dashboards in Crustdata let you track what matters to your team, not what a product manager somewhere thinks you should care about.
This guide is for anyone who’s tired of wrestling with vague metrics, “pretty” charts that don’t mean much, or dashboards that look like a cockpit but tell you nothing useful. Whether you’re in marketing, sales ops, or product, you’ll find plain, actionable advice here for building dashboards that actually help you make decisions.
1. Clarify What You Need to Measure (Don’t Track Everything)
It’s tempting to throw every metric you can think of onto a dashboard. Don’t. More data isn’t always better—it just makes it harder to spot what matters.
Start by asking: - What decisions will this dashboard help us make? - Who is this dashboard actually for? (Sales, marketing, execs, product, etc.) - Which 3-5 metrics are critical for GTM performance? (Think: pipeline velocity, conversion rates, CAC, ARR—real business KPIs.)
Pro tip:
If you can’t explain why a metric is on the dashboard in one sentence, drop it.
What works
- Focusing on a handful of “north star” metrics
- Aligning metrics with real goals (e.g., “Are we generating qualified leads?” vs. “How many people clicked this button?”)
What to ignore
- Vanity metrics (e.g., page views, social shares, form fills without context)
- “Because we can” charts—if you don’t use the info, cut it
2. Map Your Data Sources Upfront
The best dashboard in the world is useless if the data is a mess. Before building anything, figure out where your numbers are coming from.
Typical GTM data sources: - CRM (Salesforce, HubSpot, etc.) - Marketing automation (Marketo, Pardot) - Ad platforms (Google Ads, LinkedIn, Facebook) - Product analytics (Amplitude, Mixpanel) - Spreadsheets (let’s be real, there’s always one)
Questions to ask: - Is the data trustworthy? (If not, fix that first.) - How often is it updated? - Can Crustdata connect to it natively, or will you need to ETL (Extract, Transform, Load) it?
What works - Using as few data sources as possible—less chance for things to break. - Setting up automated data syncs (manual uploads get out of date fast).
What doesn’t - Pulling in “just in case” data. Only integrate what you’ll actually use.
3. Sketch First, Build Second
Before you touch any dashboard tool, sketch out what you want. Seriously—whiteboard, pen and paper, napkin, whatever. It’ll save hours of fiddling later.
Why sketch? - Forces you to focus on the story, not the visuals. - Helps you spot gaps (“Wait, do we even have this data?”) - Makes it easy to get feedback before you spend effort building.
How to do it: 1. List your must-have metrics. 2. Group related metrics together (e.g., funnel, pipeline, retention). 3. Decide what filters or time ranges matter (by region? By segment?). 4. Draw rough boxes for each chart or number.
Pro tip:
Show your sketch to someone who’ll use the dashboard. If they can’t explain it back to you, keep refining.
4. Build in Crustdata: Keep It Simple
Once your sketch is solid, move to Crustdata. The platform’s flexible, but don’t get lost in the options. Focus on clarity and usability.
Best practices: - Use clear, human-readable labels. “Leads Created (Q2)” beats “lead_obj_2024Q2.” - Limit dashboard length. If users have to scroll forever, split into tabs or sections. - Choose the right chart type. Line charts for trends, bar charts for comparisons, single numbers for KPIs. Pie charts? Almost never useful. - Use filters and date ranges, not static numbers. Let users slice the data themselves. - Surface context. Add descriptions or tooltips to explain what “SQL Conversion Rate” actually means (no one will remember).
Pitfalls to avoid: - Over-designing. Flashy visuals can hide bad data or distract from the point. - Relying on default widgets. Tweak them to match your specific needs.
5. Validate Your Data (Trust, But Verify)
Don’t assume the dashboard is right because it “looks good.” Check your numbers—otherwise, you’ll make bad calls.
How to check: - Spot-check key metrics against your source systems (e.g., does “Closed Won” in Crustdata match Salesforce?). - Look for obvious errors—sudden drops, impossible values, missing segments. - Get a second pair of eyes. Someone not involved in the build process is more likely to spot mistakes.
What works: - Scheduling a regular audit (monthly or quarterly) to make sure things haven’t broken. - Documenting where each metric comes from (add a reference sheet if you must).
What doesn’t: - Ignoring oddities because “it’s probably fine.” Gut feelings are not QA.
6. Share, Train, and Get Feedback
A dashboard is only useful if people actually use it—and know how to read it.
To get adoption: - Do a short walk-through with your team (screenshare or video is fine). - Explain what each metric means and how to use the filters. - Ask for feedback: Is anything confusing? Are there metrics nobody looks at?
Iterate, don’t set and forget: - Remove unused charts after a month or two. - Add new views as your GTM strategy evolves. - Keep it relevant—if the dashboard gets cluttered, people will ignore it.
7. Don’t Fall for Dashboard Hype
A few things you’ll hear that you should ignore:
- “More charts = more insight.” Nope. Usually just more noise.
- “AI-powered insights.” These can be useful, but usually just surface the obvious (“Conversions are up 5% this week!”). Don’t let the AI distract from the basics.
- “One dashboard to rule them all.” In reality, each team needs its own view. Executives care about ARR; marketers want channel performance; sales needs pipeline detail.
Focus on what actually helps your team make decisions.
Recap: Keep It Useful, Keep It Simple
The best dashboards don’t try to impress—they help you act. Start with what matters, validate your data, and ask for feedback. Don’t be afraid to cut what isn’t useful. Build, test, trim, repeat.
Most importantly: if you’re spending more time fiddling with your dashboard than making GTM decisions, something’s off. Keep it simple, and let the data do the talking.