Investigate Price Sensitivity for GlowSydney's New Moisturizer
Overview
What this challenge is about.
Run price elasticity analysis on GlowSydney data and competitor field notes, then compute revenue-maximizing price. Earn a verifiable certificate.
The scenario
GlowSydney is a small Sydney direct-to-consumer skincare brand that sells organic products exclusively through its own website, competing against established natural-beauty lines on large Australian online marketplaces. Its growth depends on pricing new products well, because as a lean startup it cannot recover easily from a launch priced too high or too low.
The Brief
What you'll do, and what you'll demonstrate.
Determine the launch price for GlowSydney's new organic moisturizer that maximizes revenue, using the company's historical transaction data and publicly observable competitor prices.
Earning criteria — what you'll demonstrate
- Summarize a real transaction dataset using descriptive statistics and interpret the distributions of price and quantity
- Fit and interpret a simple linear regression modeling demand as a function of price
- Estimate the price elasticity of demand and derive a revenue-maximizing price from it
- Translate observed market prices and statistical results into a single, defensible business recommendation
- Communicate quantitative findings clearly with accurate visualizations and concise writing
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Descriptive Statistics
Apply descriptive statistics to solve real industry problems and demonstrate production-level capability.
- Linear Regression
Apply linear regression to solve real industry problems and demonstrate production-level capability.
- Data Visualization
Transform complex data into clear, insightful visual representations.
- Price Elasticity
Apply price elasticity to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Junior Data Analyst
This challenge mirrors a real entry-level analyst task: cleaning a transaction dataset, summarizing it, modeling a relationship, and reporting a clear recommendation. It builds the core habit of moving from raw numbers to a decision stakeholders can act on.
This challenge sharpens
- descriptive-statistics
- linear-regression
- data-visualization
Pricing Analyst
Estimating demand sensitivity and locating a revenue-maximizing price is the daily work of pricing analysts in retail and consumer brands. The challenge develops the elasticity intuition and competitor-benchmarking discipline these roles require.
This challenge sharpens
- price-elasticity
- linear-regression
- descriptive-statistics
Marketing Analyst
Direct-to-consumer marketing teams rely on analysts who can quantify how customers respond to price and present it visually. This challenge bridges to that role by combining demand modeling with clear, persuasive data storytelling.
This challenge sharpens
- price-elasticity
- data-visualization
- descriptive-statistics