cross-sell-opportunity-engine

Analyze transaction data to identify and prioritize cross-sell opportunities.

1|1|Updated Feb 19, 2026

Search Tags:#e-commerce #recommendations #customer segmentation #retail #upsell #cross-sell #product bundling

Ready to run

npx skills add https://github.com/GoldenZero/skills --skill cross-sell-opportunity-engine-goldenzero

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: cross-sell-opportunity-engine
Source: https://github.com/GoldenZero/skills/tree/main/skills/cross-sell-opportunity-engine
Command: npx skills add https://github.com/GoldenZero/skills --skill cross-sell-opportunity-engine-goldenzero

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) and references (resource) components.

What problem does it solve?

This Skill helps businesses increase revenue by identifying and prioritizing the most effective cross-selling opportunities, leading to larger basket sizes and improved customer engagement.

Core Features & Use Cases

Product Affinity Analysis: Uncovers which products are frequently bought together using association rules.
Sequential Purchase Insights: Identifies products customers tend to buy in sequence over time.
Bundle Design: Creates data-driven product bundles to maximize appeal and value.
Use Case: A retail e-commerce manager wants to increase average order value. This Skill analyzes transaction data to recommend "Frequently Bought Together" items on product pages and suggests optimal product bundles for promotional campaigns.

Quick Start

Analyze cross-sell opportunities for our natural skincare brand using 12 months of transaction data.

Frequently Asked Questions about cross-sell-opportunity-engine

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I identify cross-sell opportunities in retail e-commerce transaction data?▼

Product affinity analysis uses market basket association rules to uncover which products are frequently bought together. By evaluating basket composition, it generates actionable insights for designing product bundles and increasing basket size in retail e-commerce.

How do I design product bundles using market basket analysis?▼

Design data-driven product bundles by applying market basket analysis to transaction data to find high-affinity product pairs. Evaluating category penetration gaps and customer segment behavior ensures bundles maximize cross-sell appeal and basket size.

Can I use sequential purchase path analysis to increase category penetration for CPG brands?▼

Sequential path analysis tracks products customers buy in sequence over time, revealing category penetration gaps for CPG brands. Targeting these cross-sell sequences builds recommendation strategies that systematically improve category penetration.

What is the best way to build a cross-sell recommendation strategy for CPG e-commerce?▼

Build a cross-sell recommendation strategy by combining product affinity analysis, sequential purchase insights, and customer segment behavior evaluation. This multi-layered approach prioritizes cross-sell opportunities to effectively increase basket size and retail engagement.

Do I need customer segmentation data to analyze cross-sell opportunities?▼

Customer segmentation data significantly enhances cross-sell analysis by revealing segment-specific behavior and category penetration gaps. While basic product affinity relies on transaction data, segment insights are required to prioritize personalized product bundling strategies.