Business Analytics
The analytics they teach in a top MBA — free, and from scratch. Turn raw numbers into decisions: read a P&L, work out unit economics (CAC, LTV), segment customers, debug the funnel, weigh choices with expected value and decision trees, forecast demand, and tell the story that changes the room. Every business term is defined the first time it appears — no finance background assumed, beginner to advanced.
- Chapter 01
Foundations
3 lessons - 01 What Business Analytics Is Dashboards don't make decisions — people do. Business analytics is the craft of turning numbers into a decision someone can act on, and it's mostly not machine learning.
- 02 Descriptive → Prescriptive Four questions, four kinds of analytics: what happened, why, what's next, and what to do. A ladder of rising value — and rising difficulty.
- 03 Metrics vs KPIs Every number is a metric; only a few are KPIs. The skill is picking the handful that actually steer the business — and ignoring the vanity numbers that only ever go up.
- Chapter 02
Business & Financial Literacy
4 lessons - 04 Revenue, Cost & Profit Revenue is not profit. Walk one month of a coffee shop from money-in to the bottom line, defining every word — COGS, gross margin, opex, operating profit — as it appears.
- 05 Reading a P&L The income statement is one page that every business speaks. Read it top to bottom — revenue down through COGS, opex, interest and tax to net income — and you can judge a company in 60 seconds.
- 06 Break-Even & Contribution Margin How many units must you sell each month just to stop losing money? Break-even analysis gives every new product, shop, or subscription the answer — and shows exactly what moves it.
- 07 Unit Economics: CAC & LTV We pay $280 to acquire a customer who pays $40 a month — are we making money or lighting it on fire? Unit economics answers whether ONE customer is profitable, which decides whether growth helps or kills you.
- Chapter 03
Descriptive & Customer Analytics
5 lessons - 08 Averages That Lie Your dashboard says average revenue per customer is $590 — but almost no real customer spends that. Here is why the mean misleads on skewed business data, and what to use instead.
- 09 Segmentation & RFM You have 50,000 customers and a budget to reach 5,000 — which 5,000, and what do you say? RFM turns three cheap numbers into laser-targeted segments that change what you do.
- 10 Funnel Analysis 10,000 people visited; 360 paid. Where did the other 9,640 go — and which leak should you fix first? Funnel analysis answers both.
- 11 Cohorts, Retention & Churn 50,000 active users and the count looks flat — are you healthy, or quietly dying? Cohort retention is the only way to know.
- 12 Customer Lifetime Value A customer pays $40 a month — but a dollar five years from now isn't worth a dollar today. What are they REALLY worth, in today's money? CLV shows you the ceiling on what you can spend to acquire each customer.
- Chapter 04
Decision Analysis
4 lessons - 13 Expected Value Should you spend $50,000 on a campaign that will probably flop — but might be huge? Expected value gives you a single number to make that call, and teaches you exactly when to trust it.
- 14 Decision Trees Launch nationally, run a pilot, or skip it entirely? Decision trees give you a structured way to compare options when the future is uncertain — and fold-back arithmetic tells you which branch wins.
- 15 Sensitivity & What-If Your spreadsheet says profit is $800,000 — but it rests on five guesses. Sensitivity analysis tells you which guess, if wrong, would hurt the most.
- 16 Monte Carlo Simulation Our model says $800,000 profit — but every input is a guess. Monte Carlo simulation draws thousands of possible futures and tells you the probability of each, including the chance you actually lose money.
- Chapter 05
Forecasting
2 lessons - 17 Trend & Seasonality December sales jumped 40% over November. Before you celebrate, learn to separate a real growth trend from the Christmas spike — and see how every forecast is just trend plus seasonality, projected forward.
- 18 Smoothing & Forecast Error Demand bounces around every month. Smoothing averages out the noise so you can plan next month's inventory — and forecast error tells you how well you did.
- Chapter 06
Prescriptive, Experiments & Communication
3 lessons - 19 Optimization & Constraints A workshop can make two products that share the same limited machine-hours and material. What mix makes the most money? Optimization finds the best decision — not just a good guess.
- 20 A/B Testing for Decisions The new checkout button converted 13% of visitors versus the old one's 10%. Did the new button really win, or did we just get lucky with 1,000 visitors each? A/B testing gives a rigorous answer.
- 21 Storytelling with Data An insight nobody acts on is worth nothing. Learn to lead with the recommendation, cut chartjunk, and match every chart to a single message — so executives decide in the room, not after you leave.
- End of section 0 / 21 complete
Make it stick — pass every quiz.
Each lesson has a short quiz at the bottom. Passing the quiz is what marks the lesson complete and counts toward your certificate.
Business Analytics — frequently asked questions
Straight answers to the questions people ask most about business analytics.
What's the difference between revenue, profit, and margin?
Revenue is total money from sales; profit is what's left after costs; margin is profit as a percentage of revenue. A business can have high revenue and still lose money if costs exceed it — which is why margin, not revenue, tells you whether the model actually works.
What are CAC and LTV, and why do they matter together?
CAC (Customer Acquisition Cost) is what you spend to win a customer; LTV (Lifetime Value) is the total profit that customer brings. The business is healthy when LTV comfortably exceeds CAC — a common benchmark is roughly 3:1 — otherwise you lose money on every customer you acquire.
Read the lessonWhat is a break-even analysis?
Break-even is the point where total revenue equals total cost, so profit is zero. It tells you how many units you must sell, or what price you must charge, to cover fixed and variable costs before you start making money — essential for pricing and go/no-go decisions.
Read the lessonWhat is RFM segmentation?
RFM scores customers on Recency (how recently they bought), Frequency (how often), and Monetary value (how much) to group them into actionable segments like loyal, at-risk, or new. It's a simple, powerful way to target retention and marketing without a complex model.
Why can the average customer be misleading?
Averages hide skew. If a few large customers dominate, the mean misrepresents the typical one, and decisions based on it misfire. Look at the median and the full distribution — segments and percentiles usually tell a truer story than a single average.