The Ultimate Guide to Cohort Tables: Turn Your Data Into Decisions

"Was the marketing campaign worth it?"

“Do customers like the new features?”

Except... your CEO wants to know why. Your investors want to know if it's sustainable. And honestly, you're not even sure yourself. Was it the new marketing campaign? Existing customers expanding? Pure luck?

Sound familiar?

In a data centric world, the hardest part isn't getting the data - it's understanding what the it means.

You have transaction records. You have customer lists. You have dates and dollar amounts and enough CSV files to fill a small library. But when someone asks "Why did revenue change?" or "Which customers are our best?" 

This is the moment where most people either:

1. Spend three days building pivot tables that break the moment new data arrives
2. Shrug and say "revenue went up" and hope nobody asks follow-up questions
3. Make educated guesses that may or may not be true

The problem is you're looking at your data wrong. There's a better way.

The secret weapon of elite finance teams, RevOps analysts, and growth-obsessed founders isn't fancier tools or bigger datasets. It's knowing how to organize their data into cohort tables—and actually understanding what they're looking at.

Cohort Analysis helps you visualize your business in a different way. That 15% growth? You'll know exactly which customer groups drove it, whether it's repeatable, and where to invest next quarter.

Let me show you how.

What Is a Cohort Table?

A cohort table groups customers (or revenue - anything really) by a common characteristic—usually when they made their first purchase or signed up—and tracks their behavior over time.

Think of it like this: Instead of lumping all your customers into one blob, you're organizing them into graduating classes. Your "January 2024 cohort" is everyone who became a customer that month. Your "February 2024 cohort" is the next class. And so on.

The “ah-ha” moment happens when you can see patterns across these groups - often predictable.

The Two Flavors: Left vs Right (And Why It Matters)

Here's where most people get confused. There are two completely different ways to arrange a cohort table, and they answer fundamentally different questions.

Left-Aligned: "Which Groups Are Best?"

In a left-aligned table, each row is a cohort, and columns represent their journey from Month 0 forward.

What you see:

• Row 1: Jan 2024 customers → Month 0, Month 1, Month 2...
• Row 2: Feb 2024 customers → Month 0, Month 1, Month 2...

What you learn:

• Do Q1 customers retain better than Q4 customers?
• Did customers from our big marketing push actually stick around?
• Do customers typically upsell in Month 3?
• Which acquisition channel produces the best long-term value?

When to use it: You're comparing groups to find your winners and optimize where you invest.

Right-Aligned: "What Changed and Why?"

In a right-aligned table, columns are actual calendar periods, and you see ALL cohort activity in each period and can view the build-up.

What you see:

• Column: January 2024 → All cohorts' activity that happened in Jan 2024
• Column: February 2024 → All cohorts' activity that happened in Feb 2024

What you learn:

• Why did revenue drop from $1M to $900K in March?
• What drove that growth spike last quarter?
• How much of this month's revenue is from new customers vs existing?
• Where exactly did we lose money?

When to use it: You're building a revenue story—a waterfall that shows how you got from Point A to Point B.

How to Actually Read These Things

Reading Left-Aligned (Cohort Lifecycle)

Look for patterns down the columns:

• Does Month 3 show a retention drop across all cohorts? → You have a ~90 day problem
• Do recent cohorts start higher in Month 0? → Your recent customers are better quality
• Do some rows stay flatter than others? → Those cohorts are stickier

Reading Right-Aligned (Calendar Periods)

Look for patterns down the columns AND across rows:

• Big number in one period? → Check which cohorts contributed
• Revenue drop? → See if it's from churn (older cohorts disappearing) or lack of upsells
• Growth spike? → Identify if it's from new customers or expansion

The Insights You'll Actually Get

From Left-Aligned:

• "Our enterprise customers have 3x better Year 1 retention than SMB customers" → Shift sales focus
• "Customers acquired through Partner Channel X have 2x LTV" → Double down on that partnership
• "Every cohort churns heavily in Month 4" → Fix your Month 4 experience

From Right-Aligned:

• "We lost $200K in Q3 because our 2023 cohorts churned" → We have an aging customer problem
• "50% of this quarter's growth came from upsells, not new customers" → Our expansion motion is working
• "The revenue dip in March was entirely from one large customer churn" → Not a systemic issue

Common Mistakes People Make

1. Using the wrong view for the question - Trying to build a revenue waterfall from left-aligned data is painful
2. Not standardizing periods - Mixing monthly and quarterly cohorts creates chaos
3. Ignoring small cohorts - That tiny cohort from your product launch might have the best retention
4. Manual calculations - By the time you've built it in Excel, the data is outdated

Where Jetti Comes In

Here's the reality: Building cohort tables manually is a nightmare. You're wrestling with VLOOKUPs, pivot tables, and formulas that break when you add new data. And you definitely don't have time to maintain both left and right-aligned views - especially across different cuts

Jetti automates all of it:

• One click, both views: Toggle between "Which groups are best?" and "What changed?" instantly
• Automatic revenue categorization: See New, Upsell, Downsell, Lost, and Reactivation without formulas
• Live updates: Your cohort tables refresh as your data changes
• Drill-down: Get transparency behind the numbers and build trust behind the numbers

Whether you're a finance team trying to explain the quarter to leadership, a RevOps analyst optimizing customer acquisition, or a founder trying to understand what's actually working—Jetti democratises the insights and turns your data into actionable insights in minutes, not days.

Navigate Your Growth. Start with the right map.