Business Metrics and KPIs Course with Python
Business Metrics and KPIs is a beginner-level course of 5 lessons (about 2 h 27 min), with 15 exercises and 15 quiz questions. Prerequisites: Descriptive Statistics. Exercises run in the browser, with nothing to install.
- Data analysis
- Beginner
- 5 lessons
- 2 h 27 min
- 15 exercises
- Exercises run in the browser
The course in brief
This course teaches you to choose and calculate the indicators that steer a business. You will write KPI sheets, build metric trees, and calculate average order value, conversion, churn, CLV, year-over-year changes, growth contributions, margins, CAC and ROAS with pandas, while avoiding classic pitfalls such as averaging ratios or confusing percentage points with percentages.
What you will be able to do
- Distinguish a metric, an indicator and a KPI, and document a KPI in a KPI sheet
- Calculate sales KPIs and break them down by segment without ratio errors
- Calculate churn, retention, repurchase rate and a simple CLV
- Compare periods (year-over-year, year-to-date, moving average) and track target attainment
- Calculate margin, margin rate, markup rate, CAC, ROAS and ROI
- Explain a change through the contribution of each segment
Syllabus: 5 lessons
- Distinguish data, metric, indicator and KPI
- Formulate a precise KPI (definition, formula, scope, period, target)
- Break a business objective down into a metric tree
- 02
Calculating Sales KPIs
- Calculate revenue, number of orders, average order value and items per order
- Calculate a conversion rate
- Break KPIs down by segment with groupby
- 03
Customer KPIs: Retention, Churn and Customer Value
- Calculate active customers, new customers and repurchase rate
- Calculate a churn rate and a retention rate over a period
- Estimate a simple customer lifetime value (CLV)
- 04
Trends, Comparisons and Target Tracking
- Calculate percentage changes and differences in points
- Compare a period with the previous year, calculate a year-to-date total and a moving average
- Measure target attainment and each segment's contribution to growth
- 05
Margin, Profitability and Marketing KPIs
- Calculate gross margin, margin rate and markup rate
- Calculate the CAC, ROAS and ROI of a campaign
- Compare acquisition channels on profitability rather than volume
Final project
KPI Dashboard for a Multichannel Shop
Generate in Python (fixed seed) two years of data for a shop: orders (date, customer, channel, status, amount excl. VAT, purchase cost excl. VAT), sessions per day and marketing spend by channel and by month. Define 5 to 7 KPIs in sheets, calculate them, compare 2026 with 2025, measure attainment of targets that you set, and produce a commented dashboard table.
Deliverables
- The KPI sheets (name, definition, formula, scope, frequency, owner, target)
- A reproducible Python script that calculates all overall and per-channel KPIs
- A monthly table with N-1 change, year-to-date total and status against the target
- An analysis of each channel's contribution to revenue growth
- A marketing profitability analysis (CAC, ROAS, ROI on margin, CLV / CAC)
- A half-page management commentary with three recommendations
Assessment criteria
- The KPIs are relevant, few in number and documented
- Ratios are calculated by aggregating numerators and denominators
- Points and percentages, margin rate and markup rate are correctly distinguished
- Time comparisons neutralize seasonality
- Recommendations follow from the figures and take their limits into account (attribution, small bases)
Frequently asked questions
What is the difference between an indicator and a KPI?
An indicator is a measure interpreted against a reference. A KPI is an indicator chosen because it directly reflects a strategic objective and is used to make decisions.
Do I need to know how to program to take this course?
Basic Python is enough: the calculations use simple operations and a few pandas functions explained as you go. Basic descriptive statistics are recommended.
What is the difference between margin rate and markup rate?
The margin rate (markup on cost) divides the margin by the purchase cost excluding VAT; the markup rate (gross margin on price) divides it by the selling price excluding VAT. For a purchase at 40 and a sale at 60, they are 50% and 33.3%.
Is this course useful for Power BI?
Yes: KPI definitions, the sum-over-sum rule for ratios and time comparisons translate directly into measures and dashboard visuals.
This course, told for your job
Say what you want to be able to do: “Business Metrics and KPIs” takes its place in your path, with examples from your field. The concepts stay those of the course.