If you’re in marketing, sales ops, or revenue leadership, you know the pain: dashboards everywhere, but answers are hard to find. You want clarity about which activities move the needle and which are just noise. This guide is for anyone who needs to analyze go-to-market (GTM) performance—without getting lost in vanity metrics or endless reports. Whether you’re new to Matchkraft or just looking to get more out of it, you’ll find practical, no-nonsense ways to use its analytics to actually improve results.
Step 1: Get Clear on What Matters (and Ignore the Rest)
Before you even touch Matchkraft or any analytics tool, stop and ask: What are you really trying to improve? GTM metrics can spiral out of control fast—there’s always something else to measure, but not everything is useful.
The only metrics that matter: - Pipeline: Are you generating enough real opportunities? - Conversion Rates: Are those opportunities moving forward? - Sales Velocity: How fast are deals moving? - Customer Acquisition Cost (CAC): Are you spending efficiently? - Retention and Expansion: Are customers sticking around and growing?
Unless you’re running a massive team, don’t bother tracking “engagement” or “brand awareness” as primary metrics. Those are nice-to-haves, not must-haves.
Pro tip: Pick 3-5 core metrics—track them consistently, and ignore the noise.
Step 2: Connect Your Data Sources
Matchkraft is only as good as the data you feed it. If your CRM is a mess or you’re missing key marketing data, you’ll get garbage out.
What you need: - CRM (Salesforce, HubSpot, etc.): For opportunity and pipeline data - Marketing automation (Marketo, HubSpot, Pardot, etc.): For campaign and lead data - Ad platforms (Google, LinkedIn, Facebook): For spend and performance details - Product or usage data (if available): For expansion and retention analysis
How to do it in Matchkraft: - Use the built-in integrations to connect your accounts. Don’t cut corners—map fields carefully so you’re not mixing apples and oranges (e.g., “lead source” means the same thing everywhere). - Double-check for duplicate records, missing values, or weird naming conventions. This is the most boring part, but if you skip it, your numbers will never add up.
What to ignore: Fancy connectors and “AI enrichment” that promises to fix your data for you. If your CRM is a disaster, no tool will magically clean it up.
Step 3: Set Up Your Dashboards (But Keep Them Simple)
The first time you log into Matchkraft’s analytics, you’ll see a lot of shiny dashboards. Resist the urge to turn everything on. More charts won’t help you focus.
Start with just a few views: - Funnel Overview: Visualize the flow from leads to closed-won deals. If there’s a leak, you’ll see it. - Pipeline by Source: See which channels are delivering real opportunities, not just form fills. - Win Rate by Segment: Break down by industry, company size, or region—whatever matters to your business. - Sales Velocity: Average time from first touch to deal closed. - CAC and ROI: Tie spend back to revenue, not just “leads generated.”
In Matchkraft: - Use their “Quick Start” dashboard templates, but customize them. You don’t need a 15-stage funnel if your process is simpler. - Avoid “vanity dashboards” (e.g., total website visitors, email open rates) unless you have a very specific reason.
Pro tip: If you wouldn’t present a metric to your CEO, don’t put it on your dashboard.
Step 4: Drill Down to Find What’s Working (and What’s Not)
Now comes the real work: interpreting the data. Matchkraft gives you filtering and segmentation tools—use them to slice the data, not just look at topline numbers.
How to dig deeper: - Compare sources: Are Google Ads driving pipeline, or is it all coming from webinars? - Segment by sales rep or team: Is someone consistently outperforming? Why? - Look at stage conversions: Where are deals getting stuck or lost? - Analyze campaign ROI: Did that expensive LinkedIn campaign actually result in revenue, or just “leads”?
What to watch out for: - False positives: A spike in leads might look good, but if quality drops, revenue won’t follow. - Attribution games: Don’t get too hung up on “multi-touch attribution models.” They’re always a bit fuzzy. Focus on clear trends, not mathematical perfection.
Pro tip: Pick one metric to improve each quarter. If you try to fix everything at once, you’ll fix nothing.
Step 5: Set Up Alerts and Regular Reviews
Metrics are useless unless you act on them. Matchkraft lets you set up automatic alerts—use them to flag real issues, not just to create more noise.
How to use alerts well: - Set thresholds for your key metrics (e.g., pipeline below $X, win rate drops below Y%). - Have alerts go to the person who can actually fix the issue, not just a shared Slack channel. - Schedule a regular (weekly or bi-weekly) review meeting to look at what’s changed. Don’t let the dashboard become wallpaper.
What to skip: Don’t create alerts for every minor fluctuation. You’ll start ignoring them.
Step 6: Tie Analysis Back to Actual Actions
This is where most teams fail. It’s easy to review numbers; it’s hard to change behavior. Matchkraft can’t do this part for you.
How to drive action: - For every metric that’s off, assign an owner and a next step. (“Leads from webinars down 30% — Sally to review event strategy by Friday.”) - Track whether actions actually move the metric in the next review. If not, try something else. - Stop measuring things that never lead to action.
Pro tip: Your analytics setup should get simpler over time, not more complex. If you’re constantly adding new dashboards, you’re probably not acting on the old ones.
Step 7: Iterate—But Don’t Chase Every Shiny Object
Analytics is never “done.” But that doesn’t mean you should constantly rebuild your dashboards or chase every new feature Matchkraft releases.
How to stay focused: - Review your metrics quarterly—are they still the right ones? - Only add new views or reports if you hit a real business question you can’t answer today. - Ignore most “AI insights” unless they clearly help you spot something you’d miss.
A note about AI features: Matchkraft, like every analytics platform, will try to sell you on their latest AI-powered insights. Sometimes they’re useful, but often they’re just statistical noise dressed up as wisdom. Trust your own eyes and experience first.
Analytics aren’t magic. They’re just tools to help you ask better questions and make better decisions. If you keep your Matchkraft setup focused and honest, you’ll spend less time arguing over numbers—and more time improving them. Start simple, make one meaningful change at a time, and remember: dashboards don’t close deals, people do.