Юнит-экономика для креативных проектов: от данных к решениям
Короткий курс
How to read the numbers of your project and make decisions that increase profit.
What is this course about?
Once a project is launched, hypotheses end and data begins: sales, customers, expenses, and acquisition channels. Merely looking at the numbers is not enough; you need to understand precisely where money is being lost, which metrics are dragging down the business, and which can be scaled.
This course is about dissecting real project data and transforming it into actionable management decisions. Students will learn how to clean data, build cohorts, calculate actual LTV, CAC, and OPEX. They will assemble a comprehensive model based on facts and identify the bottleneck. They will analyze sensitivity and build scenarios—what happens if the price increases by 10% but CAC increases by 20%?
The course is practice-driven. After every session, you will have a prepared spreadsheet, a cohort matrix, a calculation, or a conclusion. At the end, participants will complete a final project: an analysis of a real business and a 90-day action plan.
Who is this course for?
This course is suitable for:❙ Practicing creators (designers, illustrators, photographers) who already have an active project or service and want to understand where money is being lost.❙ Specialists who have completed the first course, «Unit Economics for Creative Projects: From Hypothesis to Model, ” and wish to learn how to work with factual data.❙ Instructors from the School of Design and other creative programs who want to equip students with tools for analyzing real-world projects.❙ Everyone who wants to make decisions based on data, not just intuition.
Course Duration: 6 weeks.
Total Contact Hours: 36 academic hours.
Classes are conducted in an asynchronous online format.
Course Prerequisites:
▪ Basic proficiency in spreadsheet software (Excel, Google Sheets).▪ Completion of a working project or access to real-world data (sales, customer data, expenses).
▪ Familiarity with the fundamentals of unit economics (or completion of the introductory course).
▪ Readiness to work with data and draw conclusions.
What will students learn in this course?
During this course, students will learn to:
1
Prepare data for analysis: clean and standardize formats.2
Build customer cohorts based on the initial purchase period.3
Conduct cohort analysis: revenue, active customers, repeat actions.4
Calculate actual LTV over a defined horizon.5
Calculate actual CAC by channels and periods.6
Allocate operating expenses (OPEX) to the customer.7
Assemble the fact model: from Gross LTV to Net LTV.8
Identify bottlenecks within the model.9
Analyze metric sensitivity and elasticity.10
Construct scenarios: baseline, optimistic, stress test, and crisis.What practical assignments will students complete for this course?
Throughout the course, students will complete the following tasks:
1
Data Preparation: create a data readiness checklist and cleanse the sales table.2
Cohorting: assign each client to a cohort based on their first purchase month.3
Cohort Analysis: construct matrices for revenue, active customers, and repeat actions.4
Horizon LTV Calculation: calculate LTV12 for the case study.5
Actual CAC Calculation: calculate CAC by month and channel, and derive the weighted CAC.6
Actual OPEX Calculation: allocate operating expenses to the customer.7
Fact Model Assembly: consolidate Gross LTV, Contribution LTV, Net LTV, and diagnostic coefficients.8
Bottleneck Identification: calculate diagnostic coefficients (Contribution LTV / Gross LTV, Net LTV / CAC, Payback period) and determine where money is being lost.9
Sensitivity Analysis: build a one-way sensitivity table for key metrics.10
Scenario Analysis: assemble a scenario panel based on Net LTV.Final Project: a management memo including a diagnosis, the top 3 actions, and a 90-day plan.Thematic Curriculum Plan
Moving to Facts and Data Preparation
— What changes when we move from hypotheses to facts.
— Data readiness checklist.
— Cleaning rules: one row equals one event, one cell equals one value.Practice: cleaning a sales table.
Cohort Analysis and Cohorting
— How to assign a customer to their initial purchase cohort.
— Building matrices: revenue, active customers, repeat actions.
— Comparing cohorts by customer lifetime, not by calendar time.Practice: cohorting and matrix building.
LTV and Cost Based on Facts
— Purchase frequency and average order value.
— Calculating Gross LTV over a given horizon.
— Fixed versus variable costs based on factual data.Practice: calculating LTV12 and margin.
CAC and OPEX Based on Facts
— Actual CAC by month and channel.
— Weighted CAC.
— Distributing OPEX per customer.Practice: calculating CAC and OPEX.
Assembling the Fact Model and Identifying Bottlenecks
— Assembling Gross LTV → Contribution LTV → Net LTV.
— Diagnostic metrics: Contribution LTV / Gross LTV, Net LTV / CAC, Payback period.
— Sensitivity and elasticity analysis.Practice: building the model and identifying the bottleneck.
Scenarios and Final Project
— Scenario analysis: Base, Optimistic, Stress, Crisis.
— Break-even point across scenarios.
— Final memo format.Practice: building scenarios and defending the final project.
