Shopify Customer Spending Analyzer

Task

Use @Shopify/Get Customer Orders by EmailName it "Shopify/Get Customer Orders by Email" and call it with @Shopify/Get Customer Orders by Email to pull order history for a list of customers, analyze their spending patterns, and use @Google Sheets/Add RowsName it "Google Sheets/Add Rows" and call it with @Google Sheets/Add Rows to build a segmented customer spreadsheet. Optionally use @google_searchName it "google_search" and call it with @google_search to research best practices for the segments you find.

Example: Analyze spending for our top 20 customers, segment them into VIP / Regular / At-Risk tiers, and export the results to a Google Sheet.

Input

The user will provide:

1. A list of customer email addresses to analyze
2. The Google Sheet ID to export results to
3. Optional: custom segment thresholds (e.g., VIP = $500+, Regular = $100-499, At-Risk = no orders in 90+ days)

Example: "Analyze these 15 customer emails and segment them. VIP is anyone who spent over $1,000 total. Flag anyone who hasn't ordered in 60 days as at-risk."

Context

Segmentation Criteria

VIP Customers (default: $500+ total spend):

• High total lifetime spend
• Multiple orders (3+ orders)
• Recent activity (ordered within last 60 days)

Regular Customers (default: $100-499 total spend):

• Moderate spending
• 1-2 orders
• Some recent activity

At-Risk Customers:

• No orders in 90+ days regardless of spend
• Previously active but gone quiet
• Single purchase with no repeat

New Customers:

• First order within last 30 days
• Still evaluating — potential to move up

Metrics to Calculate Per Customer

For each customer, compute:

• Total lifetime spend (sum of all order totals)
• Order count (number of completed orders)
• Average order value (total spend / order count)
• First order date and last order date
• Days since last order
• Top products purchased (most frequent line items)
• Segment assignment based on thresholds

Spreadsheet Structure

Export to Google Sheets with columns: | Email | Name | Segment | Total Spent | Order Count | Avg Order Value | First Order | Last Order | Days Since Last Order | Top Products | Currency |

Analysis Summary

After processing all customers, provide:

• Segment distribution (how many in each tier)
• Total revenue across all analyzed customers
• Average metrics per segment
• Recommendations for each segment

Output

Google Sheet: One row per customer with all computed metrics and segment assignment.

Summary Report:

Customer Spending Analysis

Customers Analyzed: [Count] Total Revenue: [Sum]

Segment Breakdown

| Segment | Count | % of Customers | Total Revenue | Avg Order Value | |---------|-------|---------------|---------------|-----------------| | VIP | X | Y% | $Z | $W | | Regular | X | Y% | $Z | $W | | At-Risk | X | Y% | $Z | $W | | New | X | Y% | $Z | $W |

Key Findings

• [Insight about VIP concentration — e.g., "Top 3 VIPs account for 45% of revenue"]
• [Insight about at-risk customers — e.g., "5 previously active customers haven't ordered in 90+ days"]
• [Recommendation — e.g., "Consider a win-back campaign for at-risk segment"]

Recommended Actions

1. VIP segment: [Specific action, e.g., "Send exclusive early access to new collection"]
2. At-Risk segment: [Specific action, e.g., "Trigger a 15% discount win-back email"]
3. New segment: [Specific action, e.g., "Send product education series to drive second purchase"]