What’s the Best Roadmap for Getting Into Marketing Analytics?
That’s a good question—but I think what you’re really asking is...
“What’s the clearest, most realistic way to break in when the path feels overwhelming, the job descriptions are unclear, and I’m not sure where to focus?”
Let’s walk through this together step by step.
Marketing analytics can feel overwhelming. There’s a flood of tools, jargon, and advice—but no clear starting point.
So if you're early in your career and trying to figure out where to start, what to learn, and how to stand out, this guide is for you.
Step 1: Learn to Think Like a Marketer (Not Just an Analyst)
Before the tools, learn the terrain. Marketing analytics is about uncovering insights that drive decisions.
Learn how the funnel works:
Awareness: How people first hear about your product (ads, SEO, word of mouth)
Acquisition: Getting them to visit or engage (clicks, traffic, signups)
Activation: Helping them experience value quickly (first conversion or meaningful event)
Retention: Keeping them engaged and coming back (repeat usage, reduced churn)
Revenue: Turning engagement into sustainable income (subscriptions, LTV, upsells)
Understand these core metrics:
CAC (Customer Acquisition Cost): How much it costs to acquire a customer
LTV (Lifetime Value): How much value a customer brings over time
CTR (Click-Through Rate): % of people clicking a link/ad
CVR (Conversion Rate): % of users who take a desired action
Bounce Rate: % who leave after viewing only one page
Churn Rate: % of users who leave over time
ROAS (Return on Ad Spend): Revenue generated per dollar spent on ads
Revenue per Session: Earnings per website visit
Resources:
HubSpot Academy (Free) – Intro to Digital Marketing
Reforge blog (Advanced, strategic insights)
CXL Blog – In-depth breakdowns of metrics, experimentation, CRO
Step 2: Build Your “Analytics Stack” Skillset
You don’t need to know everything. You need the right tools:
Essential Tools (Minimum Viable Stack):
SQL: Foundational for querying large datasets and joining tables across platforms
Excel/Google Sheets: Still critical for quick data exploration, pivot tables, and modeling
Google Analytics 4 (GA4): To understand website behavior and conversion patterns
Looker Studio / Power BI: For turning insights into shareable, visual dashboards
Optional (for growth or certain roles):
Mixpanel or Amplitude: Powerful for product-led and event-based user flows
Google Tag Manager (GTM): Learn tagging and event tracking implementation basics
Pro Tip: Don’t aim to master everything. Learn each tool through a project—e.g., “Track user drop-offs in signup funnel with GA4 + Looker.”
Step 3: Choose One Domain to Go Deep In
Marketing analytics is a wide ocean. You don’t need to swim across all of it—just dive deep in one bay.
Four Strong Focus Areas:
Acquisition Analytics: Understand channel performance (paid search, SEO, social, etc.) and ROAS
Retention & Lifecycle: Master cohort analysis, user behavior over time, churn prediction
Conversion Optimization & Experimentation: Learn test design, CRO principles, statistical validity, and lift analysis
Attribution Modeling: Evaluate how touchpoints contribute to conversions (first-touch, last-touch, linear, data-driven)
Choose based on curiosity and traction—what problems excite you? What’s in demand in the job market?
Step 4: Learn to Communicate Insights
A dashboard is not a story. A chart is not an answer.
To stand out:
Frame the question: “What decision does this analysis support?”
Simplify the narrative: Focus on “why this matters” to business
Use clear visuals: Avoid clutter, emphasize clarity
Tell a story: What’s happening, why, and what action should be taken
Practice summarizing insights in 2–3 sentences:
“Users from paid search convert 3x higher than organic, but bounce faster. We should explore retargeting or optimizing landing pages for organic.”
This skill alone sets you apart from 90% of other candidates.
Step 5: Build a Portfolio That Shows Business Thinking
Hiring managers don’t just want tech skills. They want applied thinking.
Ideas for portfolio pieces:
Funnel analysis + business recommendations
Real (or simulated) campaign performance breakdown
A/B test strategy doc with results interpretation
Looker Studio dashboard with annotations and insights
Use public datasets (Kaggle, Google Merchandise Store), your own blog/project, or side gigs.
Step 6: Signal Your Knowledge Publicly
Make your learning visible:
Add project links to your LinkedIn and resume
Share bite-sized learnings (“What I learned building my first GA4 funnel report”)
Complete certifications: GA4, SQL, Google Data Analytics (Coursera), HubSpot Analytics
Bonus: Publish one LinkedIn post per week = instant credibility compounding
Step 7: Get Closer to Real People (10x Growth Hack)
Follow practitioners on LinkedIn and ask thoughtful questions
Book ADPList calls with analytics leaders
Attend online meetups, workshops, or community events (many are free)
You’ll grow faster through conversation than consumption.
Final Word
You don’t need a fancy degree or 10 years of experience. You need:
Curiosity
Direction
A repeatable plan
Start where you are. Go deep in one thing. Build, share, refine.
Tools help you get answers. Insight helps you get hired.
If this was helpful, subscribe to Experimentation Career for weekly guides, job-winning frameworks, and honest takes from someone inside the industry.
And remember:
Ask questions in the comments
Reach out if you're stuck
This is all from my lived experience—so it's biased, incomplete, and evolving. I’m still learning, too.
Let’s figure it out—together.
Talk soon,
Atticus