E-commerce Mock Data Generator for Rybbit

This script generates realistic mock analytics data for Rybbit, simulating user behavior on an e-commerce website called ShopEase.

Features

Generates approximately 5 million events per day over a specified number of days
Creates realistic user shopping sessions with multiple pageviews and custom events
Models realistic e-commerce user journeys (browsing, product views, add to cart, checkout, purchase)
Sessions end after 30 minutes of inactivity
Distributes traffic realistically throughout the day (with peak hours)
Uses Faker.js to generate realistic product data, location information, and more
Uses weighted distributions for pages, browsers, operating systems, screen sizes, and more
Varies the number of events per day to be more realistic

Requirements

Node.js 14+
ClickHouse database set up (configuration in .env file)

Installation

Make sure all dependencies are installed:

npm install

Usage

Run the script with optional parameters:

# Default: 30 days with ~5 million events per day
npm run generate

# Custom parameters (days, events per day)
node index.js 15 2000000  # 15 days with ~2 million events per day

Parameters

daysInPast: Number of days in the past to generate data for (default: 30)
eventsPerDay: Approximate number of events per day (default: 5,000,000)

Data Distribution

The script creates realistic distributions of:

Page views with appropriate e-commerce user flows
Shopping behavior patterns (browsing, cart additions, checkouts, purchases)
Geographic distribution (countries and regions using Faker.js)
Browser types and versions
Operating systems
Screen resolutions
Referrers (including social media and other e-commerce sites)
Custom events specific to e-commerce (product views, add to cart, checkout steps, etc.)
Time of day (peak hours vs. off hours)

E-commerce Event Types

The generator includes these e-commerce-specific events:

page-view - Basic page view tracking
product-view - When a user views a product detail page
add-to-cart - When a user adds an item to their cart
remove-from-cart - When a user removes an item from their cart
begin-checkout - When a user starts the checkout process
checkout-step - Tracking each step of the checkout funnel
purchase - When a user completes a purchase
search - When a user searches for products
filter-products - When a user applies filters to product listings
add-to-wishlist - When a user adds items to their wishlist
And more...

Data Schema

Events are inserted into the ClickHouse pageviews table with the following schema:

site_id
timestamp
session_id
user_id
hostname
pathname
querystring
page_title
referrer
browser
browser_version
operating_system
operating_system_version
language
country
iso_3166_2
screen_width
screen_height
device_type
type (pageview or custom_event)
event_name (for custom events)
properties (JSON string for custom events)

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