# Quick Order – Analytics & Metrics

The Metrics section gives you a simple overview of how customers interact with your Quick Order pages. All metrics update based on the **selected time range** and **store type** (All / Default Store / B2B Store).

### 1. Active Users

**Definition:**\
The number of **unique users** who visited any Quick Order page during the selected time range.

**How to use:**

* Measures how many customers actually engage with Quick Order.
* Useful for tracking adoption over time.
* Compare **Default Store** vs **B2B Store** to understand usage by customer type.

**Examples:**

* If you choose “Last 7 days”, the number shows how many different users opened Quick Order at least once within those 7 days.

***

### 2. Quick Order Page Visits

**Definition:**\
Total number of **sessions (page visits)** to all Quick Order pages during the selected time range.

**How to use:**

* Shows how frequently Quick Order pages are opened.
* Helps identify whether customers return multiple times.
* Differences between **Active Users** and **Page Visits** show intensity of usage.

**Example:**

* 10 active users and 40 visits → each user visited Quick Order \~4 times in that time range.

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### 3. Time Range Filter

Use the date selector (e.g., Today, Last 7 days, Last 30 days) to view metrics for a specific period.

**Uses:**

* Check short-term trends after new updates or campaigns.
* Understand long-term adoption by selecting larger time windows.

***

### 4. Store Type Filter (All / Default Store / B2B Store)

**All:** combined metrics for both store types.\
**Default Store:** standard Shopify storefront metrics.\
**B2B Store:** interactions from Shopify B2B customers.

**Why it matters:**

* Helps compare how B2B customers use Quick Order vs normal customers.
* Useful when optimizing Quick Order specifically for B2B workflows.

***

## Request for Quote – Analytics & Metrics

These metrics help you track how many quotes customers send and how many turn into orders.

***

### 1. Number of Quote Requests

**Definition:**\
Total number of **quote requests** submitted during the selected time range.

**Includes:**

* Quotes submitted through the storefront
* Quotes created manually in the admin

**How to use:**

* Evaluate RFQ adoption.
* Compare Default Store vs B2B Store to see which side drives more requests.

***

### 2. Quote-to-Order Conversion Rate

**Definition:**\
Percentage of quote requests in the selected time range that were converted into **draft orders**.

**Formula:**\
Conversion Rate = (Quotes converted to draft orders ÷ Total quote requests) × 100%

**How to use:**

* Measures the effectiveness of your quote workflow.
* High conversion = strong pricing and negotiation flow.
* Low conversion = check response time, pricing strategy, or communication gaps.

***

### 3. Time Range Filter

Select a date range (Today, Last 7 days, Last 30 days, etc.) to analyze RFQ performance within that timeframe.

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### 4. Store Type Filter (All / Default Store / B2B Store)

**All:** show combined metrics.\
**Default Store:** requests from non-B2B customers.\
**B2B Store:** requests from Shopify B2B Company/Location customers.

**Use case:**

* Compare how B2B buyers behave vs normal customers.
* Optimize quote logic and form fields based on user type.

***

## Quick Interpretation Examples

* **Low Active Users + Low Visits (Quick Order)**\
  → Promote Quick Order more clearly; add navigation links or highlight benefits.
* **High Visits + Low Add-to-Cart (if measured)**\
  → Improve product scope, filters, search, or layout.
* **High Quote Requests + High Conversion**\
  → RFQ flow is performing very well.
* **High Quote Requests + Low Conversion**\
  → Check sales handling, pricing strategy, or customer communication.


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