fullstory-ecommerce

Configure FullStory ecommerce analytics with privacy masking and event tracking.

Updated Dec 20, 2025

Search Tags:#analytics #privacy #ecommerce #event-tracking #FullStory #PII-masking #PCI-compliance

Ready to run

npx skills add https://github.com/rcmaples/btx --skill fullstory-ecommerce

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: fullstory-ecommerce
Source: https://github.com/rcmaples/btx/tree/main/.claude/skills/fullstory-ecommerce
Command: npx skills add https://github.com/rcmaples/btx --skill fullstory-ecommerce

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a privacy-conscious, end-to-end guide for deploying FullStory in ecommerce environments, enabling rich product interaction analytics while safeguarding PII and PCI data.

Core Features & Use Cases

Privacy-aware instrumentation: configure data collection with fs-unmask, fs-mask, and data redaction strategies to protect sensitive information.
Ecommerce event taxonomy: track product_viewed, add_to_cart, checkout_start, purchase_completed, and product_impression events with structured properties.
Commerce workflows: implement PDP, PLP, and cart/checkout pages with consistent analytics and privacy controls.

Quick Start

Enable FullStory on your storefront and validate that product data (id, name, category, price) is captured while sensitive fields are masked.
Integrate the provided examples for PDP, PLP, cart, and checkout tracking into your web app and verify in FullStory dashboards.
Review PCI and PII guidelines to ensure no card data or personal identifiers are transmitted.

Frequently Asked Questions about fullstory-ecommerce

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

FAQPage Schema

How do I set up FullStory ecommerce tracking without exposing PII or PCI data?▼

FullStory ecommerce tracking protects sensitive data by applying fs-unmask and fs-mask attributes alongside data redaction strategies. This ensures product interaction analytics are captured while safeguarding PII and PCI data during checkout.

What ecommerce events should I track for product interaction analytics?▼

Product interaction analytics require tracking product_viewed, add_to_cart, checkout_start, purchase_completed, and product_impression events. These structured events capture product data like id, name, category, and price across PDP and PLP workflows.

Does FullStory work with PCI-compliant checkout workflows?▼

FullStory integrates with PCI-compliant checkout workflows by implementing strict data governance practices. It uses fs-mask to redact sensitive fields, ensuring no card data or personal identifiers are transmitted during checkout tracking.

How do I mask sensitive customer data during FullStory session replay?▼

Mask sensitive customer data during FullStory session replay by configuring fs-mask and fs-unmask attributes. This privacy-aware instrumentation strategy prevents PII exposure while still allowing product-level analytics on PDP and cart pages.

What is the best way to structure ecommerce event taxonomy for privacy-conscious analytics?▼

The best way to structure ecommerce event taxonomy for privacy-conscious analytics is mapping specific user actions like purchase_completed to structured properties. This approach ensures consistent tracking across commerce workflows while maintaining data governance.

Why does my FullStory implementation capture sensitive checkout fields?▼

FullStory implementations capture sensitive checkout fields when fs-mask and fs-redaction strategies are not applied. Reviewing PCI and PII guidelines and applying privacy-aware instrumentation ensures compliant data collection during checkout.