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Common Questions
Frequently Asked Questions
What is price elasticity in ecommerce?
Price elasticity measures how much demand changes when price changes. An elasticity of 1.5 means a 5% price increase causes ~7.5% volume drop. Most DTC and ecommerce products fall between 1.0 (inelastic, premium) and 2.5 (elastic, commodity). The lower your elasticity, the safer it is to raise prices.
Why does raising prices often increase profit even with volume loss?
Margin% grows non-linearly with price because COGS is fixed. A $50 product with $22 COGS has 56% margin; raise to $55 (10% increase) and margin becomes 60%. The 4-point margin gain often outweighs even a 15% volume drop. The math is forgiving up to a point.
How do I estimate elasticity for my products?
Three methods: (1) A/B test prices across geographic markets or customer segments. (2) Look at historical sales when you ran sales/promos - the volume lift relative to price drop is your observed elasticity. (3) Use category benchmarks (1.5 is a reasonable default for DTC) and stress-test scenarios. Real elasticity often surprises - test before scaling.
Should I round prices to charm pricing (e.g. $49 vs $50)?
Charm pricing ($X.99 or $X9) typically lifts conversion 1-2% over round numbers in price-sensitive categories. Premium brands often go the opposite direction with round prices ($50 vs $49.99) to signal quality. The lift is small either way - elasticity matters far more than the cents digit.
When should I consider price testing vs just raising prices?
For under-5% price moves on established products, just raise them and watch sales for 30 days. The math almost always supports modest increases. For larger moves (10%+) or unproven products, test by segment or geography first. Most stores under-price out of fear, then leave money on the table.
Does this calculator account for ad spend changes?
No. The calculator assumes COGS stays constant and prices change in isolation. In practice, raising prices often lowers ROAS reporting (same ad spend, less revenue), so be ready for ad platforms to interpret price-raised products as weaker performers and reduce traffic. Compensate by lifting bids or shifting budget after a pricing change.
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