AnalyticsPricing

Price Sensitivity: 10% Price Increase = 20% Volume Drop (Elastic Demand)

9 May 2026·Updated May 2026·5 min read·GuideIntermediate
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In this article
  1. What Is Price Elasticity?
  2. Why Elasticity Varies by Product
  3. The Pricing Optimization Math
  4. AskBiz Elasticity Modeling
  5. Running a Safe Price Test Without Guessing
  6. Worked Example: Testing Two Products at Once
  7. Common Mistakes in Elasticity Testing
Key Takeaways

Product A: base price SGD 50, volume 100 units. Raise to SGD 55 (10% increase): volume drops to 80 units (20% drop). Elasticity = 2.0 (elastic = price sensitive). Revenue impact: old SGD 5K, new SGD 4.4K = -12% revenue. Bad move. Product B: base SGD 50, raise to SGD 55: volume drops to 95 units (5% drop). Elasticity = 0.5 (inelastic = price insensitive). Revenue impact: old SGD 5K, new SGD 5.225K = +4.5% revenue. Good move. Which to raise? Product B (inelastic).

  • What Is Price Elasticity?
  • Why Elasticity Varies by Product
  • The Pricing Optimization Math
  • AskBiz Elasticity Modeling
  • Running a Safe Price Test Without Guessing

What Is Price Elasticity?#

Elasticity = % volume change ÷ % price change. Elastic (>1): volume changes more than price. Inelastic (<1): volume changes less than price. At elasticity = 1 (unit elastic): volume % and price % change equally = revenue neutral. Example: SGD 50 price, 100 units = SGD 5K revenue. Raise 10% to SGD 55, lose 10% volume to 90 units = new revenue SGD 4.95K (nearly same).

Why Elasticity Varies by Product#

Luxury goods (watches, jewelry): inelastic (customer willing to pay, price = status). Commodity goods (milk, rice): elastic (many alternatives, customer price-sensitive). Branded goods: more inelastic (brand loyalty = price forgiveness). Unbranded: more elastic (no differentiation = price driven).

The Pricing Optimization Math#

Profit = (Price - COGS) × Volume. If you raise price but lose volume, profit might drop. Example: Product with COGS SGD 30. Current: SGD 50 price, 100 volume = (SGD 50 - SGD 30) × 100 = SGD 2K profit. Raise to SGD 55 (inelastic, only 5% volume loss): (SGD 55 - SGD 30) × 95 = SGD 2.375K profit (+18.75% increase). But elastic product (20% volume loss): (SGD 55 - SGD 30) × 80 = SGD 2K profit (no change). Conclusion: raise price on inelastic products only.

AskBiz Elasticity Modeling#

Models elasticity by testing price changes (A/B test: 10% of customers see SGD 55, rest see SGD 50, measure volume change). "Product A: elasticity 2.0 (elastic). Price increase would reduce profit. Recommendation: don't raise, focus on cost reduction instead. Product B: elasticity 0.5 (inelastic). 10% price increase = 4.5% profit increase = SGD 200/month additional profit. Recommended: implement price increase."

More in Analytics

Running a Safe Price Test Without Guessing#

You don't need a formal A/B test infrastructure to estimate elasticity. Pick a product with stable, predictable demand (not one currently on promotion or affected by a seasonal spike). Change the price for a 2-4 week window and compare volume to the same window the prior month or the prior year, adjusting for any known trend. Calculate: % change in volume ÷ % change in price = elasticity. If you have multiple similar outlets or an online store alongside physical retail, you can run a true A/B test — change price in one channel only and compare volume trends between the two. The key discipline is isolating the price variable: don't run a price test during a marketing push or a competitor's stockout, because those confound the volume change and give you a false elasticity reading.

Worked Example: Testing Two Products at Once#

A Singapore specialty grocer tested price increases on two products simultaneously. Product A (imported olive oil, minimal local substitutes): price raised from SGD 18 to SGD 20 (11% increase). Volume over the following month: 340 units versus a prior 4-week average of 355 units — a 4.2% volume drop. Elasticity = 4.2 ÷ 11 = 0.38 (inelastic). Revenue: old = 355 × SGD 18 = SGD 6,390. New = 340 × SGD 20 = SGD 6,800 — a 6.4% revenue gain. Product B (a common local rice brand, many substitutes on the same shelf): price raised from SGD 12 to SGD 13.20 (10% increase). Volume dropped from 600 units to 468 units — a 22% drop. Elasticity = 2.2 (highly elastic). Revenue: old = SGD 7,200, new = 468 × SGD 13.20 = SGD 6,178 — a 14% revenue loss. The test confirmed the grocer should raise olive oil prices further but reverse the rice price change immediately.

Common Mistakes in Elasticity Testing#

The first mistake is testing during an atypical period — school holidays, a local event, or a competitor's temporary closure will distort volume independent of your price change, producing an elasticity estimate you can't trust. The second is testing too small a price change to detect a real signal; a 2-3% price move often falls within normal week-to-week volume noise, so use at least a 8-10% change for a clean read. The third is assuming elasticity is permanent — a product can become more elastic over time as competitors enter or customers become more price-aware, so re-test annually rather than relying on a single historical estimate indefinitely. AskBiz logs price changes against POS transaction volume automatically, so elasticity estimates update as new sales data comes in rather than requiring a manually scheduled test each time.

📊 By The Numbers
10%5%18.75%20%4.5%

People also ask

How do I estimate elasticity without testing?

Benchmark: luxury goods 0.3-0.7 (inelastic), staples 0.8-1.2 (unit elastic), commodity 1.5-2.0 (elastic). Start conservative (assume less elastic than you think), test with small segment first.

Should I always raise prices on inelastic products?

Not always. Consider: competitor response (they match price = no margin gain), customer goodwill (too many hikes = brand damage), elasticity changes over time (inelastic now, elastic later if customers find alternatives).

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