Expert answer · 3 min read
Can I A/B test different discount percentages?
The short answer
In depth
A/B Testing Discount Percentages in Growth Suite
Discount depth is one of the highest-leverage variables to test in your campaign strategy. A 5pp difference in discount (10% vs 15%) can be the difference between a profitable campaign and one that erodes margin without meaningful CVR improvement. Growth Suite's A/B Testing Module provides the infrastructure to answer this question with data from your actual visitor base rather than industry benchmarks.
What to Test in Discount A/B Tests
Discount Amount Variables
Test: 8% vs 12%, 10% vs 15%, 15% vs 20%. Each comparison isolates whether the incremental discount depth delivers proportional CVR improvement. If 15% converts at only 5% higher than 10%, the extra margin cost isn't justified - run the lower discount.
Discount Format Variables
Test: "15% off" vs "$8 off" vs "Free shipping" vs "Free sample + 10% off." The same economic value delivered in different formats often converts at meaningfully different rates. Fixed dollar amounts can feel more tangible on lower-priced items; percentages on higher-priced items.
Offer Framing Variables
Test: "Get 15% off" vs "Save 15% on your order" vs "Your exclusive 15% off expires in 12 minutes." The psychological framing of the same discount can affect click-through rate by 10-25% without changing the actual offer value.
Timer Duration Variables
Test: 10-minute timer vs 20-minute timer vs 1-hour timer. Very short timers create stress; very long timers reduce urgency. Most stores find an optimal window between 15-30 minutes for exit-intent offers, but this varies by category and product consideration time.
A/B Test Evaluation Criteria
| Metric | What It Measures | Weight in Decision |
|---|---|---|
| Campaign CVR | % of campaign recipients who purchase | Primary metric |
| Margin per session | Revenue minus discount cost, per eligible session | Secondary metric (higher discount may win CVR but lose margin) |
| AOV of converted sessions | Whether different discounts attract different order sizes | Context metric |
| Statistical significance | Confidence that result is real, not random | Minimum threshold before declaring winner |
Growth Suite - A/B Testing Module
Growth Suite's A/B Testing Module splits eligible campaign traffic between variants and tracks conversion outcomes per variant. You set the traffic split (50/50 or weighted), configure each variant's offer parameters, and let the test run until statistical significance is reached. The reporting dashboard shows CVR, redemption rate, and revenue per variant side-by-side, making the winning variant clear. Once a winner is identified, it can be set as the primary campaign configuration with one click.
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