> For the complete documentation index, see [llms.txt](https://eraya.gitbook.io/eraya-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://eraya.gitbook.io/eraya-docs/use-cases/use-cases-for-price-test.md).

# 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.