Operations & Inventory

Product Bundle Strategy Builder

Identify high-potential product bundles from your order data, get pricing recommendations, and estimate incremental AOV lift.

What This Skill Does

This skill analyzes your transaction data to find products frequently purchased together, identifies cross-sell opportunities, and designs specific bundles with pricing, placement, and estimated revenue impact. It uses market basket analysis principles to find non-obvious product pairings that customers actually want.

What You Need

Order data with line items: each order listing all products purchased. Product catalog with prices and margins.

Prompt Template

Copy this prompt, replace the [BRACKETED] placeholders with your data, and paste into Claude.

Analyze this transaction data to identify product bundling opportunities. Order data (orders with line items): [PASTE ORDER DATA — at minimum: Order ID, Product Name/SKU, Price] Product margins (if available): | Product | Price | Margin % | |---------|-------|----------| ... Current average order value: $[X] AOV target: $[X] Identify: 1. Products most frequently purchased together (top 10 pairs by co-purchase frequency) 2. High-affinity but low co-purchase rate pairs (untapped cross-sell opportunities) 3. Products that act as "gateways" — first products that lead to the highest repeat purchase rates For each recommended bundle: - Bundle name and included products - Individual price total vs. bundle price (target 10-20% perceived discount) - Estimated margin per bundle - Recommended placement (product page, cart upsell, email, or homepage) Estimate overall AOV lift if top 3 bundles are implemented.

Example Output

Here is what Claude produces when you use this skill with sample data.

**Top Co-Purchase Pairs (from 2,400 orders analyzed):** | Product A | Product B | Co-Purchase Rate | Lift vs. Random | Confidence | |-----------|-----------|-----------------|----------------|-----------| | Vitamin C Serum | Hyaluronic Moisturizer | 34% | 3.2x | High | | Cleanser | Toner | 28% | 2.8x | High | | Retinol Night Cream | Eye Cream | 22% | 2.4x | Medium | | Sunscreen SPF 50 | Vitamin C Serum | 19% | 1.9x | Medium | **Recommended Bundles:** **1. "Glow Duo" — Serum + Moisturizer** - Individual total: $83 | Bundle price: $69 (17% savings) - Bundle margin: $41 (59%) — above $35 floor - Your margin on individual sales: Serum $28 + Moisturizer $21 = $49 - Bundle discount cost: $14 | Net margin sacrifice: $8/bundle - Break-even: Bundle converts if it drives 16%+ more purchases vs. standalone - Placement: PDP cross-sell widget, cart page "Complete Your Routine" **2. "Fresh Start Kit" — Cleanser + Toner + Travel Moisturizer** - Individual total: $62 | Bundle price: $49 (21% savings) - Bundle margin: $28 (57%) - Strategic purpose: Acquisition bundle — lower price point brings new customers in - Placement: Homepage featured, Meta/Instagram ads, email welcome series **3. "Night Repair Set" — Retinol Night Cream + Eye Cream** - Individual total: $76 | Bundle price: $64 (16% savings) - Bundle margin: $38 (59%) - Placement: PDP of either product, post-purchase email upsell **Projected AOV Impact:** - Current AOV: $75 - Estimated bundle attachment rate: 12-15% of eligible PDPs - Projected new AOV: $83.50 (+$8.50, +11% lift) - Estimated monthly revenue lift: $3,400 at current traffic **Implementation Priority:** 1. Launch "Glow Duo" first (highest co-purchase rate, strongest signal) 2. Test "Fresh Start Kit" in acquisition ads (lower price point for new customers) 3. Add "Night Repair Set" to post-purchase email sequence for serum/moisturizer buyers

Tips for Best Results

Look beyond obvious pairings — the highest-lift bundles are often products customers did not know worked together.

Test bundle placement in post-purchase emails too: "Complete your routine" upsells after first order.

Track bundle attachment rate weekly and refresh quarterly as new products launch.

Skip the Prompt — Automate This

Finsi runs this analysis automatically on your live data. No prompting, no copy-pasting — just real-time insights and AI-powered recommendations.

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