E-Commerce Analytics Guide

This guide will walk you through some best practices for using Keen to track common e-commerce metrics such as:

  • Sign Up Rate
  • Activation Rate / Conversion Rate
  • Add to Cart Rate
  • Average Order Value
  • Repeat Purchase Rate
  • Lifetime Value

Data Model

In order to be able to do the queries for the metrics, we’ll have to have the right data collections in place. Below, you’ll find an example data model to use for your shop.

Collections

We’ll be using the following collections that will help us

Collection: first_visits

Purpose: To track the first visit of each visitor. Attributes:

  • path: Path of the page.
  • referrer: Referrer URL, taken from document.referrer.
  • params: Desired URL params.
  • user: Information about the user, explained here.

Example event:

var client = new Keen({
    projectId: "your_project_id",
    writeKey: "your_write_key"
});

client.addEvent('first_visits', {
    path: "/ad-landing-page",
    referrer: "http://google.com",
    params: {
        utm_source: "google",
        utm_medium: "cpc",
        utm_campaign: "campaign_name"
    },
    "user": {
        uuid: "xxxx-xxxx-xxxx-xxxx-xxxx",
        first_visited_at: "2015-06-29T07:36:55.929Z"
    }
});

Collection: product_views

Purpose: To track product page views. Attributes:

  • path: Path of the page.
  • product_id: Product’s ID.
  • product_name: Product’s Name.
  • product_price: Product’s Price.
  • user: Information about the user, explained here.

Example event:

var client = new Keen({
    projectId: "your_project_id",
    writeKey: "your_write_key"
});

client.addEvent('product_views', {
    "path": "/products/1800-summer-pants",
    "product_id": "1800",
    "product_name": "Summer Pants",
    "product_price": 69.99,
    "user": {
        uuid: "xxxx-xxxx-xxxx-xxxx-xxxx",
        first_visited_at: "2015-06-29T07:36:55.929Z"
    }
});

Collection: add_to_carts

Purpose: To track a user adding a product to their Cart. Attributes:

  • cart_id: Cart’d ID.
  • product_id: Product’s ID.
  • product_name: Product’s Name.
  • product_price: Product’s Price.
  • quantity: Quantity being added to Cart.
  • user: Information about the user, explained here.

Example event:

var client = new Keen({
    projectId: "your_project_id",
    writeKey: "your_write_key"
});

client.addEvent('add_to_carts', {
    "cart_id": "201",
    "product_id": "1800",
    "product_name": "Summer Pants",
    "product_price": 69.99,
    "quantity": 1,
    "user": {
        uuid: "xxxx-xxxx-xxxx-xxxx-xxxx",
        first_visited_at: "2015-06-29T07:36:55.929Z"
    }
});

Collection: purchases

Purpose: To track a succesful purchase. Attributes:

  • cart_id: Cart being purchased’s ID.
  • total: Total amount being purchased.
  • user: Information about the user, explained here.

Example event:

var client = new Keen({
    projectId: "your_project_id",
    writeKey: "your_write_key"
});

client.addEvent('purchases', {
    "cart_id": "201",
    "total": 139.98,
    "user": {
        uuid: "xxxx-xxxx-xxxx-xxxx-xxxx",
        first_visited_at: "2015-06-29T07:36:55.929Z"
    }
});

Common attributes

In order to connect the different collections, we will be sending a user object attributes with all our events:

  • user.uuid: An identifier generated for the user when they first visited.
  • user.first_visited_at: A date for when the user first visited.

The common user attribute will help us to follow the user’s journey through their experience on the site over time.

Tracking

To illustrate how to use the data model, we’ve created a fake example e-commerce website here with detailed examples of how and when to send events during the user’s experience with your shop.

Visualization

Based on this data model and the events that are sent on the shop, we’ve setup an example dashboard here. You can also view the source for this dashboard in dashboard.js and dashboard.html.

What’s Next?

Sign up for a free account to get started. If you’d like to learn more about e-commerce analytics, reach out to Schedule a free data consultation with our data science team.