Track AOV by Channel in MCP: 4-Minute Setup

Step 1: Connect Your Shopify Store to MCP

Let's start with the basics and build from there. First, we need to get your Shopify order data into MCP Analytics.

1. Log into your MCP Analytics dashboard at mcpanalytics.ai/analysis
2. Click "Add Data Source" in the top navigation
3. Select "Shopify" from the integrations list
4. Click "Install MCP Analytics" (this redirects to Shopify App Store)
5. Click "Install app" and authorize the following permissions:
   • Read orders
   • Read customers
   • Read order attributes (this includes UTM parameters)

Expected outcome: Within 2-3 minutes, you'll see a success message: "Shopify connected. Syncing 180 days of historical orders." Your dashboard will show a progress bar as data imports.

Step 2: Navigate to Orders → AOV Analysis Module

Now that your data is flowing in, let's find the AOV Analysis module. This is where the magic happens.

1. From your MCP dashboard, click "Commerce Analytics" in the left sidebar
2. Select "Orders" from the dropdown menu
3. Click "AOV Analysis" (you'll see it listed under "Revenue Metrics")

You should now see a default view showing your overall average order value—probably a single number like "$78.43" with a small trend chart. This is your baseline, but it doesn't tell us the full story. Let's segment it.

Expected outcome: A dashboard displaying your store-wide AOV with date range selector (default: last 30 days) and an empty "Segmentation" panel on the right.

Step 3: Add UTM Source as Segmentation Dimension

Here's where we transform a single number into actionable insights. By adding UTM Source as a dimension, we'll see exactly how AOV differs across your traffic sources.

1. In the right panel, click "Add Dimension"
2. From the dropdown, select "Acquisition → UTM Source"
3. Click "Apply"

The view will update in 2-3 seconds, transforming from a single number to a breakdown like this:

Traffic Source          AOV        Orders    Revenue
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
google                 $94.27      342      $32,240
facebook               $67.13      589      $39,540
email                  $112.84     156      $17,603
instagram              $71.22      234      $16,665
organic                $88.91      445      $39,565
(direct)               $76.33      892      $68,086
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Overall                $78.43     2,658    $213,699

What you're looking at: Each row represents a traffic source. The AOV column shows the average order value for customers acquired through that channel. Orders shows the volume, and Revenue shows total contribution.

Step 4: Interpret the AOV Distribution Chart

What does this visualization tell us? Let's look together at the example above and break down what we're seeing.

Key observations from the sample data:

1. Email has the highest AOV ($112.84) despite lower volume (156 orders). This suggests your email list contains engaged, higher-value customers who trust your brand enough to subscribe.
2. Facebook has the lowest AOV ($67.13) but high volume (589 orders). This is common—social traffic often includes browsers and impulse buyers who make smaller purchases.
3. Google sits in the middle ($94.27) with healthy volume (342 orders). Search traffic often converts well because these customers are actively looking for solutions.
4. Direct traffic has moderate AOV ($76.33) with the highest volume (892 orders). This includes returning customers, brand searches, and people who saved your URL.

Step 5: Identify High-AOV Channels and Create Campaign Strategy

Now comes the fun part—using these insights to make smarter marketing decisions. Let me walk you through a simple framework.

The High-AOV Channel Strategy:

1. Identify your top 2 AOV channels (in our example: email at $112.84 and Google at $94.27)
2. Calculate the revenue difference:
   • Email revenue per order: $112.84
   • Facebook revenue per order: $67.13
   • Difference: $45.71 per order (68% higher!)
3. Adjust budget allocation: If acquiring a customer costs $30 via Facebook and $35 via email, email is actually more profitable despite the higher cost because each customer spends $45.71 more on average.
4. Test channel-specific offers: High-AOV channels might respond well to premium products or bundle deals. Low-AOV channels might need starter offers to get customers in the door.

Step 6: Advanced — Time-Series AOV Trends by Channel

You've mastered the basics. Now let's add a time dimension to spot trends before they become problems (or opportunities).

1. In the AOV Analysis view (with UTM Source dimension already applied), click "Add Time Series"
2. Select your preferred interval: Daily, Weekly, or Monthly
3. Choose date range: Last 90 days (gives you enough data to spot trends without overwhelming the chart)
4. Click "Generate Trend Chart"

Expected outcome: A multi-line chart showing AOV trends over time for each channel. You might notice:

• Email AOV spikes during promotional campaigns (your loyal subscribers respond to sales)
• Google AOV remains steady (intent-driven traffic is consistent)
• Facebook AOV dips on weekends (casual browsers make smaller impulse purchases)
• Organic AOV increases month-over-month (your content marketing attracts increasingly qualified traffic)

This time-series view helps you answer questions like: "Did our Black Friday email campaign attract bargain hunters or high-value buyers?" The answer is in the data—if email AOV dropped during the sale, you attracted volume but not value. If it stayed steady or increased, your sale priced strategically.

For more advanced analysis combining AOV with customer lifetime value, check out our guide on statistical significance in A/B testing to ensure your insights are statistically valid, not just random noise.