Definition:
A/B testing compares two different price points by exposing separate groups of visitors to each price and measuring their performance. The goal is to determine which price generates better outcomes such as higher revenue, profit, or conversion.
Why it matters:
- Provides data-driven validation for pricing decisions.
- Reduces guesswork when adjusting product prices.
- Helps identify price points that improve business performance.
Example:
An apparel store tests a jacket at $120 vs $130. Half of visitors see each price. After two weeks, the $130 price produces higher profit even with slightly lower conversion, so the merchant adopts that price.