Use Cases for Price Test
Eraya’s Price Test allows you to run controlled A/B experiments to understand how pricing changes impact your revenue, conversion rate, and customer behavior. With Eraya, you can compare two versions of a product — the Control (A) and one Variation (B) — to make data-driven pricing decisions.
1. Measuring Price Sensitivity
Price Tests help you measure how customer demand changes when you increase or decrease prices. By testing a single alternative price against your current price, you can quickly learn if your audience is price sensitive or value tolerant.
Example:
A (Control): $39.99
B (Variation): $44.99
If revenue increases without a major drop in conversion, customers are not highly price-sensitive — and a higher price may be sustainable.
2. Validating Price Increases Before a Full Rollout
Instead of updating all products at once, test a small segment of traffic with a higher price to ensure it doesn’t hurt conversions. This helps you de-risk pricing changes before applying them store-wide.
Example: You test raising the price of your best-selling candle from $24.99 → $27.99. If revenue per visitor remains steady or improves, you can confidently update your live price.
3. Evaluating Discount Impact
Compare performance between a discounted and non-discounted price to understand if discounts truly drive incremental revenue or only shift purchasing timing.
Example:
A (Control): $59.99
B (Variation): $59.99 → $49.99 (with 15% discount)
Eraya tracks which version generates more profit after factoring in the discount margin.
4. Testing Perceived Value
Small price changes can influence perceived value — especially for premium or limited-edition products. Use Price Tests to see if slightly higher prices reinforce quality perception or reduce conversions.
Example:
A (Control): $89.00
B (Variation): $95.00
If higher prices maintain conversion but improve revenue, you’ve validated stronger brand positioning.
5. Subscription Conversion Optimization
If you offer both one-time and subscription options, test different one-time prices to see how they affect subscription adoption rates.
Example: When the one-time price increases from $39.99 to $44.99, more users choose the subscription plan — improving recurring revenue.
⚙️ Supported Setup
Eraya currently supports:
A/B price tests only (one control and one variation)
Both Duplicate Product and Cart Transform testing methods
Automatic data collection on sessions, conversions, and revenue per variant
Multi-variant (A/B/C/D) tests will be available in future updates.
✅ Best Practices
Test for at least 2–3 weeks to capture both new and returning visitors.
Use meaningful price differences (e.g., 10–20%) to detect clear behavioral impact.
Avoid testing multiple variables (price, image, or title) at once — focus only on price.
Set clear goals before starting — e.g., maximizing revenue, conversion rate, or subscription adoption.
Include all major traffic sources to ensure a balanced and representative sample.
🚫 When Not to Run a Price Test
During major sale events (e.g., Black Friday, Cyber Monday, or holiday promotions).
When your inventory is low or products are frequently out of stock.
If traffic is inconsistent or below the minimum required to achieve significance.
When other experiments (discounts, shipping tests, or bundle offers) are running on the same product.
If the product has recent major changes (new photos, titles, descriptions), as it can bias results.
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