debian-mirror-gitlab/doc/development/snowplow.md

stage	group	info
Growth	Product Intelligence	To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#assignments

Snowplow Guide

This guide provides an overview of how Snowplow works, and implementation details.

For more information about Product Intelligence, see:

• Product Intelligence Guide
• Usage Ping Guide

More useful links:

• Product Intelligence Direction
• Data Analysis Process
• Data for Product Managers
• Data Infrastructure

What is Snowplow

Snowplow is an enterprise-grade marketing and Product Intelligence platform which helps track the way users engage with our website and application.

Snowplow consists of the following loosely-coupled sub-systems:

• Trackers fire Snowplow events. Snowplow has 12 trackers, covering web, mobile, desktop, server, and IoT.
• Collectors receive Snowplow events from trackers. We have three different event collectors, synchronizing events either to Amazon S3, Apache Kafka, or Amazon Kinesis.
• Enrich cleans up the raw Snowplow events, enriches them and puts them into storage. We have an Hadoop-based enrichment process, and a Kinesis-based or Kafka-based process.
• Storage is where the Snowplow events live. We store the Snowplow events in a flat file structure on S3, and in the Redshift and PostgreSQL databases.
• Data modeling is where event-level data is joined with other data sets and aggregated into smaller data sets, and business logic is applied. This produces a clean set of tables which make it easier to perform analysis on the data. We have data models for Redshift and Looker.
• Analytics are performed on the Snowplow events or on the aggregate tables.

Snowplow schema

We have many definitions of Snowplow's schema. We have an active issue to standardize this schema including the following definitions:

• Frontend and backend taxonomy as listed below
• Structured event taxonomy
• Self describing events
• Iglu schema
• Snowplow authored events

Enabling Snowplow

Tracking can be enabled at:

• The instance level, which enables tracking on both the frontend and backend layers.
• User level, though user tracking can be disabled on a per-user basis. GitLab tracking respects the Do Not Track standard, so any user who has enabled the Do Not Track option in their browser is not tracked at a user level.

We use Snowplow for the majority of our tracking strategy and it is enabled on GitLab.com. On a self-managed instance, Snowplow can be enabled by navigating to:

• Admin Area > Settings > General in the UI.
• admin/application_settings/integrations in your browser.

The following configuration is required:

Name	Value
Collector	snowplow.trx.gitlab.net
Site ID	gitlab
Cookie domain	.gitlab.com

Snowplow request flow

The following example shows a basic request/response flow between the following components:

• Snowplow JS / Ruby Trackers on GitLab.com
• GitLab.com Snowplow Collector
• The GitLab S3 Bucket
• The GitLab Snowflake Data Warehouse
• Sisense:

sequenceDiagram
    participant Snowplow JS (Frontend)
    participant Snowplow Ruby (Backend)
    participant GitLab.com Snowplow Collector
    participant S3 Bucket
    participant Snowflake DW
    participant Sisense Dashboards
    Snowplow JS (Frontend) ->> GitLab.com Snowplow Collector: FE Tracking event
    Snowplow Ruby (Backend) ->> GitLab.com Snowplow Collector: BE Tracking event
    loop Process using Kinesis Stream
      GitLab.com Snowplow Collector ->> GitLab.com Snowplow Collector: Log raw events
      GitLab.com Snowplow Collector ->> GitLab.com Snowplow Collector: Enrich events
      GitLab.com Snowplow Collector ->> GitLab.com Snowplow Collector: Write to disk
    end
    GitLab.com Snowplow Collector ->> S3 Bucket: Kinesis Firehose
    S3 Bucket->>Snowflake DW: Import data
    Snowflake DW->>Snowflake DW: Transform data using dbt
    Snowflake DW->>Sisense Dashboards: Data available for querying

Structured event taxonomy

When adding new click events, we should add them in a way that's internally consistent. If we don't, it is very painful to perform analysis across features since each feature captures events differently.

The current method provides several attributes that are sent on each click event. Please try to follow these guidelines when specifying events to capture:

attribute	type	required	description
category	text	true	The page or backend area of the application. Unless infeasible, please use the Rails page attribute by default in the frontend, and namespace + class name on the backend.
action	text	true	The action the user is taking, or aspect that's being instrumented. The first word should always describe the action or aspect: clicks should be click, activations should be activate, creations should be create, etc. Use underscores to describe what was acted on; for example, activating a form field would be activate_form_input. An interface action like clicking on a dropdown would be click_dropdown, while a behavior like creating a project record from the backend would be create_project
label	text	false	The specific element, or object that's being acted on. This is either the label of the element (e.g. a tab labeled 'Create from template' may be create_from_template) or a unique identifier if no text is available (e.g. closing the Groups dropdown in the top navigation bar might be groups_dropdown_close), or it could be the name or title attribute of a record being created.
property	text	false	Any additional property of the element, or object being acted on.
value	decimal	false	Describes a numeric value or something directly related to the event. This could be the value of an input (e.g. 10 when clicking internal visibility).

Web-specific parameters

Snowplow JS adds many web-specific parameters to all web events by default.

Implementing Snowplow JS (Frontend) tracking

GitLab provides Tracking, an interface that wraps the Snowplow JavaScript Tracker for tracking custom events. There are a few ways to use tracking, but each generally requires at minimum, a category and an action. Additional data can be provided that adheres to our Structured event taxonomy.

field	type	default value	description
category	string	document.body.dataset.page	Page or subsection of a page that events are being captured within.
action	string	'generic'	Action the user is taking. Clicks should be click and activations should be activate, so for example, focusing a form field would be activate_form_input, and clicking a button would be click_button.
data	object	{}	Additional data such as label, property, value, and context as described in our Structured event taxonomy.

Tracking in HAML (or Vue Templates)

When working within HAML (or Vue templates) we can add data-track-* attributes to elements of interest. All elements that have a data-track-event attribute automatically have event tracking bound on clicks.

Below is an example of data-track-* attributes assigned to a button:

%button.btn{ data: { track: { event: "click_button", label: "template_preview", property: "my-template" } } }

<button class="btn"
  data-track-event="click_button"
  data-track-label="template_preview"
  data-track-property="my-template"
/>

Event listeners are bound at the document level to handle click events on or within elements with these data attributes. This allows them to be properly handled on re-rendering and changes to the DOM. Note that because of the way these events are bound, click events should not be stopped from propagating up the DOM tree. If for any reason click events are being stopped from propagating, you need to implement your own listeners and follow the instructions in Tracking in raw JavaScript.

Below is a list of supported data-track-* attributes:

attribute	required	description
data-track-event	true	Action the user is taking. Clicks must be prepended with click and activations must be prepended with activate. For example, focusing a form field would be activate_form_input and clicking a button would be click_button.
data-track-label	false	The label as described in our Structured event taxonomy.
data-track-property	false	The property as described in our Structured event taxonomy.
data-track-value	false	The value as described in our Structured event taxonomy. If omitted, this is the element's value property or an empty string. For checkboxes, the default value is the element's checked attribute or false when unchecked.
data-track-context	false	The context as described in our Structured event taxonomy.

Caveats

When using the GitLab helper method nav_link be sure to wrap html_options under the html_options keyword argument. Be careful, as this behavior can be confused with the ActionView helper method link_to that does not require additional wrapping of html_options

nav_link(controller: ['dashboard/groups', 'explore/groups'], html_options: { data: { track_label: "groups_dropdown", track_event: "click_dropdown" } })

vs

link_to assigned_issues_dashboard_path, title: _('Issues'), data: { track_label: 'main_navigation', track_event: 'click_issues_link' }

Tracking within Vue components

There's a tracking Vue mixin that can be used in components if more complex tracking is required. To use it, first import the Tracking library and request a mixin.

import Tracking from '~/tracking';
const trackingMixin = Tracking.mixin({ label: 'right_sidebar' });

You can provide default options that are passed along whenever an event is tracked from within your component. For instance, if all events within a component should be tracked with a given label, you can provide one at this time. Available defaults are category, label, property, and value. If no category is specified, document.body.dataset.page is used as the default.

You can then use the mixin normally in your component with the mixin Vue declaration. The mixin also provides the ability to specify tracking options in data or computed. These override any defaults and allow the values to be dynamic from props, or based on state.

export default {
  mixins: [trackingMixin],
  // ...[component implementation]...
  data() {
    return {
      expanded: false,
      tracking: {
        label: 'left_sidebar'
      }
    };
  },
}

The mixin provides a track method that can be called within the template, or from component methods. An example of the whole implementation might look like the following.

export default {
  mixins: [Tracking.mixin({ label: 'right_sidebar' })],
  data() {
    return {
      expanded: false,
    };
  },
  methods: {
    toggle() {
      this.expanded = !this.expanded;
      this.track('click_toggle', { value: this.expanded })
    }
  }
};

And if needed within the template, you can use the track method directly as well.

<template>
  <div>
    <a class="toggle" @click.prevent="toggle">Toggle</a>
    <div v-if="expanded">
      <p>Hello world!</p>
      <a @click.prevent="track('click_action')">Track an event</a>
    </div>
  </div>
</template>

Tracking in raw JavaScript

Custom event tracking and instrumentation can be added by directly calling the Tracking.event static function. The following example demonstrates tracking a click on a button by calling Tracking.event manually.

import Tracking from '~/tracking';

const button = document.getElementById('create_from_template_button');
button.addEventListener('click', () => {
  Tracking.event('dashboard:projects:index', 'click_button', {
    label: 'create_from_template',
    property: 'template_preview',
    value: 'rails',
  });
})

Tests and test helpers

In Jest particularly in Vue tests, you can use the following:

import { mockTracking } from 'helpers/tracking_helper';

describe('MyTracking', () => {
  let spy;

  beforeEach(() => {
    spy = mockTracking('_category_', wrapper.element, jest.spyOn);
  });

  it('tracks an event when clicked on feedback', () => {
    wrapper.find('.discover-feedback-icon').trigger('click');

    expect(spy).toHaveBeenCalledWith('_category_', 'click_button', {
      label: 'security-discover-feedback-cta',
      property: '0',
    });
  });
});

In obsolete Karma tests it's used as below:

import { mockTracking, triggerEvent } from 'spec/helpers/tracking_helper';

describe('my component', () => {
  let trackingSpy;

  beforeEach(() => {
    trackingSpy = mockTracking('_category_', vm.$el, spyOn);
  });

  const triggerEvent = () => {
    // action which should trigger a event
  };

  it('tracks an event when toggled', () => {
    expect(trackingSpy).not.toHaveBeenCalled();

    triggerEvent('a.toggle');

    expect(trackingSpy).toHaveBeenCalledWith('_category_', 'click_edit_button', {
      label: 'right_sidebar',
      property: 'confidentiality',
    });
  });
});

Implementing Snowplow Ruby (Backend) tracking

GitLab provides Gitlab::Tracking, an interface that wraps the Snowplow Ruby Tracker for tracking custom events.

Custom event tracking and instrumentation can be added by directly calling the GitLab::Tracking.event class method, which accepts the following arguments:

argument	type	default value	description
category	String		Area or aspect of the application. This could be HealthCheckController or Lfs::FileTransformer for instance.
action	String		The action being taken, which can be anything from a controller action like create to something like an Active Record callback.
label	String	nil	As described in Structured event taxonomy.
property	String	nil	As described in Structured event taxonomy.
value	Numeric	nil	As described in Structured event taxonomy.
context	Array[SelfDescribingJSON]	nil	An array of custom contexts to send with this event. Most events should not have any custom contexts.
project	Project	nil	The project associated with the event.
user	User	nil	The user associated with the event.
namespace	Namespace	nil	The namespace associated with the event.

Tracking can be viewed as either tracking user behavior, or can be used for instrumentation to monitor and visualize performance over time in an area or aspect of code.

For example:

class Projects::CreateService < BaseService
  def execute
    project = Project.create(params)

    Gitlab::Tracking.event('Projects::CreateService', 'create_project', label: project.errors.full_messages.to_sentence,
                           property: project.valid?.to_s, project: project, user: current_user, namespace: namespace)
  end
end

Unit testing

Use the expect_snowplow_event helper when testing backend Snowplow events. See testing best practices for details.

Performance

We use the AsyncEmitter when tracking events, which allows for instrumentation calls to be run in a background thread. This is still an active area of development.

Developing and testing Snowplow

There are several tools for developing and testing Snowplow Event

Testing Tool	Frontend Tracking	Backend Tracking	Local Development Environment	Production Environment	Production Environment
Snowplow Analytics Debugger Chrome Extension	{check-circle}	{dotted-circle}	{check-circle}	{check-circle}	{check-circle}
Snowplow Inspector Chrome Extension	{check-circle}	{dotted-circle}	{check-circle}	{check-circle}	{check-circle}
Snowplow Micro	{check-circle}	{check-circle}	{check-circle}	{dotted-circle}	{dotted-circle}
Snowplow Mini	{check-circle}	{check-circle}	{dotted-circle}	{status_preparing}	{status_preparing}

Legend

{check-circle} Available, {status_preparing} In progress, {dotted-circle} Not Planned

Preparing your MR for Review

1. For frontend events, in the MR description section, add a screenshot of the event's relevant section using the Snowplow Analytics Debugger Chrome browser extension.
2. For backend events, please use Snowplow Micro and add the output of the Snowplow Micro good events GET http://localhost:9090/micro/good.
3. Include a member of the Product Intelligence team as a reviewer of your MR. Mention @gitlab-org/growth/product_intelligence/engineers in your MR to request a review.

Snowplow Analytics Debugger Chrome Extension

Snowplow Analytics Debugger is a browser extension for testing frontend events. This works on production, staging and local development environments.

1. Install the Snowplow Analytics Debugger Chrome browser extension.
2. Open Chrome DevTools to the Snowplow Analytics Debugger tab.
3. Learn more at Igloo Analytics.

Snowplow Inspector Chrome Extension

Snowplow Inspector Chrome Extension is a browser extension for testing frontend events. This works on production, staging and local development environments.

1. Install Snowplow Inspector.
2. Open the Chrome extension by pressing the Snowplow Inspector icon beside the address bar.
3. Click around on a webpage with Snowplow and you should see JavaScript events firing in the inspector window.

Snowplow Micro

Snowplow Micro is a very small version of a full Snowplow data collection pipeline: small enough that it can be launched by a test suite. Events can be recorded into Snowplow Micro just as they can a full Snowplow pipeline. Micro then exposes an API that can be queried.

Snowplow Micro is a Docker-based solution for testing frontend and backend events in a local development environment. You need to modify GDK using the instructions below to set this up.

• Read Introducing Snowplow Micro
• Look at the Snowplow Micro repository
• Watch our installation guide recording

1. Ensure Docker is installed and running.

2. Install Snowplow Micro by cloning the settings in this project:

3. Navigate to the directory with the cloned project, and start the appropriate Docker container with the following script:

   ./snowplow-micro.sh
   

4. Update your instance's settings to enable Snowplow events and point to the Snowplow Micro collector:

   gdk psql -d gitlabhq_development
   update application_settings set snowplow_collector_hostname='localhost:9090', snowplow_enabled=true, snowplow_cookie_domain='.gitlab.com';
   

5. Update DEFAULT_SNOWPLOW_OPTIONS in app/assets/javascripts/tracking.js to remove forceSecureTracker: true:

   diff --git a/app/assets/javascripts/tracking.js b/app/assets/javascripts/tracking.js
   index 0a1211d0a76..3b98c8f28f2 100644
   --- a/app/assets/javascripts/tracking.js
   +++ b/app/assets/javascripts/tracking.js
   @@ -7,7 +7,6 @@ const DEFAULT_SNOWPLOW_OPTIONS = {
      appId: '',
      userFingerprint: false,
      respectDoNotTrack: true,
   -  forceSecureTracker: true,
      eventMethod: 'post',
      contexts: { webPage: true, performanceTiming: true },
      formTracking: false,
   
   

6. Update snowplow_options in lib/gitlab/tracking.rb to add protocol and port:

   diff --git a/lib/gitlab/tracking.rb b/lib/gitlab/tracking.rb
   index 618e359211b..e9084623c43 100644
   --- a/lib/gitlab/tracking.rb
   +++ b/lib/gitlab/tracking.rb
   @@ -41,7 +41,9 @@ def snowplow_options(group)
              cookie_domain: Gitlab::CurrentSettings.snowplow_cookie_domain,
              app_id: Gitlab::CurrentSettings.snowplow_app_id,
              form_tracking: additional_features,
   -          link_click_tracking: additional_features
   +          link_click_tracking: additional_features,
   +          protocol: 'http',
   +          port: 9090
            }.transform_keys! { |key| key.to_s.camelize(:lower).to_sym }
          end
   

7. Update emitter in lib/gitlab/tracking/destinations/snowplow.rb to change protocol:

   diff --git a/lib/gitlab/tracking/destinations/snowplow.rb b/lib/gitlab/tracking/destinations/snowplow.rb
   index 4fa844de325..5dd9d0eacfb 100644
   --- a/lib/gitlab/tracking/destinations/snowplow.rb
   +++ b/lib/gitlab/tracking/destinations/snowplow.rb
   @@ -40,7 +40,7 @@ def tracker
            def emitter
              SnowplowTracker::AsyncEmitter.new(
                Gitlab::CurrentSettings.snowplow_collector_hostname,
   -            protocol: 'https'
   +            protocol: 'http'
              )
            end
          end
   
   

8. Restart GDK:

   `gdk restart`
   

9. Send a test Snowplow event from the Rails console:

   Gitlab::Tracking.self_describing_event('iglu:com.gitlab/pageview_context/jsonschema/1-0-0', data: { page_type: 'MY_TYPE' }, context: nil)
   

10. Navigate to localhost:9090/micro/good to see the event.

Snowplow Mini

Snowplow Mini is an easily-deployable, single-instance version of Snowplow.

Snowplow Mini can be used for testing frontend and backend events on a production, staging and local development environment.

For GitLab.com, we're setting up a QA and Testing environment using Snowplow Mini.

Snowplow Schemas

gitlab_standard

We are including the gitlab_standard schema with every event. See Standardize Snowplow Schema for details.

The StandardContext class represents this schema in the application.

Field Name	Required	Type	Description
project_id	{dotted-circle}	integer
namespace_id	{dotted-circle}	integer
environment	{check-circle}	string (max 32 chars)	Name of the source environment, such as production or staging
source	{check-circle}	string (max 32 chars)	Name of the source application, such as gitlab-rails or gitlab-javascript

Default Schema

Field Name	Required	Type	Description
app_id	{check-circle}	string	Unique identifier for website / application
base_currency	{dotted-circle}	string	Reporting currency
br_colordepth	{dotted-circle}	integer	Browser color depth
br_cookies	{dotted-circle}	boolean	Does the browser permit cookies?
br_family	{dotted-circle}	string	Browser family
br_features_director	{dotted-circle}	boolean	Director plugin installed?
br_features_flash	{dotted-circle}	boolean	Flash plugin installed?
br_features_gears	{dotted-circle}	boolean	Google gears installed?
br_features_java	{dotted-circle}	boolean	Java plugin installed?
br_features_pdf	{dotted-circle}	boolean	Adobe PDF plugin installed?
br_features_quicktime	{dotted-circle}	boolean	Quicktime plugin installed?
br_features_realplayer	{dotted-circle}	boolean	RealPlayer plugin installed?
br_features_silverlight	{dotted-circle}	boolean	Silverlight plugin installed?
br_features_windowsmedia	{dotted-circle}	boolean	Windows media plugin installed?
br_lang	{dotted-circle}	string	Language the browser is set to
br_name	{dotted-circle}	string	Browser name
br_renderengine	{dotted-circle}	string	Browser rendering engine
br_type	{dotted-circle}	string	Browser type
br_version	{dotted-circle}	string	Browser version
br_viewheight	{dotted-circle}	string	Browser viewport height
br_viewwidth	{dotted-circle}	string	Browser viewport width
collector_tstamp	{dotted-circle}	timestamp	Time stamp for the event recorded by the collector
contexts	{dotted-circle}
derived_contexts	{dotted-circle}		Contexts derived in the Enrich process
derived_tstamp	{dotted-circle}	timestamp	Timestamp making allowance for inaccurate device clock
doc_charset	{dotted-circle}	string	Web page’s character encoding
doc_height	{dotted-circle}	string	Web page height
doc_width	{dotted-circle}	string	Web page width
domain_sessionid	{dotted-circle}	string	Unique identifier (UUID) for this visit of this user_id to this domain
domain_sessionidx	{dotted-circle}	integer	Index of number of visits that this user_id has made to this domain (The first visit is 1)
domain_userid	{dotted-circle}	string	Unique identifier for a user, based on a first party cookie (so domain specific)
dvce_created_tstamp	{dotted-circle}	timestamp	Timestamp when event occurred, as recorded by client device
dvce_ismobile	{dotted-circle}	boolean	Indicates whether device is mobile
dvce_screenheight	{dotted-circle}	string	Screen / monitor resolution
dvce_screenwidth	{dotted-circle}	string	Screen / monitor resolution
dvce_sent_tstamp	{dotted-circle}	timestamp	Timestamp when event was sent by client device to collector
dvce_type	{dotted-circle}	string	Type of device
etl_tags	{dotted-circle}	string	JSON of tags for this ETL run
etl_tstamp	{dotted-circle}	timestamp	Timestamp event began ETL
event	{dotted-circle}	string	Event type
event_fingerprint	{dotted-circle}	string	Hash client-set event fields
event_format	{dotted-circle}	string	Format for event
event_id	{dotted-circle}	string	Event UUID
event_name	{dotted-circle}	string	Event name
event_vendor	{dotted-circle}	string	The company who developed the event model
event_version	{dotted-circle}	string	Version of event schema
geo_city	{dotted-circle}	string	City of IP origin
geo_country	{dotted-circle}	string	Country of IP origin
geo_latitude	{dotted-circle}	string	An approximate latitude
geo_longitude	{dotted-circle}	string	An approximate longitude
geo_region	{dotted-circle}	string	Region of IP origin
geo_region_name	{dotted-circle}	string	Region of IP origin
geo_timezone	{dotted-circle}	string	Timezone of IP origin
geo_zipcode	{dotted-circle}	string	Zip (postal) code of IP origin
ip_domain	{dotted-circle}	string	Second level domain name associated with the visitor’s IP address
ip_isp	{dotted-circle}	string	Visitor’s ISP
ip_netspeed	{dotted-circle}	string	Visitor’s connection type
ip_organization	{dotted-circle}	string	Organization associated with the visitor’s IP address – defaults to ISP name if none is found
mkt_campaign	{dotted-circle}	string	The campaign ID
mkt_clickid	{dotted-circle}	string	The click ID
mkt_content	{dotted-circle}	string	The content or ID of the ad.
mkt_medium	{dotted-circle}	string	Type of traffic source
mkt_network	{dotted-circle}	string	The ad network to which the click ID belongs
mkt_source	{dotted-circle}	string	The company / website where the traffic came from
mkt_term	{dotted-circle}	string	Keywords associated with the referrer
name_tracker	{dotted-circle}	string	The tracker namespace
network_userid	{dotted-circle}	string	Unique identifier for a user, based on a cookie from the collector (so set at a network level and shouldn’t be set by a tracker)
os_family	{dotted-circle}	string	Operating system family
os_manufacturer	{dotted-circle}	string	Manufacturers of operating system
os_name	{dotted-circle}	string	Name of operating system
os_timezone	{dotted-circle}	string	Client operating system timezone
page_referrer	{dotted-circle}	string	Referrer URL
page_title	{dotted-circle}	string	Page title
page_url	{dotted-circle}	string	Page URL
page_urlfragment	{dotted-circle}	string	Fragment aka anchor
page_urlhost	{dotted-circle}	string	Host aka domain
page_urlpath	{dotted-circle}	string	Path to page
page_urlport	{dotted-circle}	integer	Port if specified, 80 if not
page_urlquery	{dotted-circle}	string	Query string
page_urlscheme	{dotted-circle}	string	Scheme (protocol name)
platform	{dotted-circle}	string	The platform the app runs on
pp_xoffset_max	{dotted-circle}	integer	Maximum page x offset seen in the last ping period
pp_xoffset_min	{dotted-circle}	integer	Minimum page x offset seen in the last ping period
pp_yoffset_max	{dotted-circle}	integer	Maximum page y offset seen in the last ping period
pp_yoffset_min	{dotted-circle}	integer	Minimum page y offset seen in the last ping period
refr_domain_userid	{dotted-circle}	string	The Snowplow domain_userid of the referring website
refr_dvce_tstamp	{dotted-circle}	timestamp	The time of attaching the domain_userid to the inbound link
refr_medium	{dotted-circle}	string	Type of referer
refr_source	{dotted-circle}	string	Name of referer if recognised
refr_term	{dotted-circle}	string	Keywords if source is a search engine
refr_urlfragment	{dotted-circle}	string	Referer URL fragment
refr_urlhost	{dotted-circle}	string	Referer host
refr_urlpath	{dotted-circle}	string	Referer page path
refr_urlport	{dotted-circle}	integer	Referer port
refr_urlquery	{dotted-circle}	string	Referer URL query string
refr_urlscheme	{dotted-circle}	string	Referer scheme
se_action	{dotted-circle}	string	The action / event itself
se_category	{dotted-circle}	string	The category of event
se_label	{dotted-circle}	string	A label often used to refer to the ‘object’ the action is performed on
se_property	{dotted-circle}	string	A property associated with either the action or the object
se_value	{dotted-circle}	decimal	A value associated with the user action
ti_category	{dotted-circle}	string	Item category
ti_currency	{dotted-circle}	string	Currency
ti_name	{dotted-circle}	string	Item name
ti_orderid	{dotted-circle}	string	Order ID
ti_price	{dotted-circle}	decimal	Item price
ti_price_base	{dotted-circle}	decimal	Item price in base currency
ti_quantity	{dotted-circle}	integer	Item quantity
ti_sku	{dotted-circle}	string	Item SKU
tr_affiliation	{dotted-circle}	string	Transaction affiliation (such as channel)
tr_city	{dotted-circle}	string	Delivery address: city
tr_country	{dotted-circle}	string	Delivery address: country
tr_currency	{dotted-circle}	string	Transaction Currency
tr_orderid	{dotted-circle}	string	Order ID
tr_shipping	{dotted-circle}	decimal	Delivery cost charged
tr_shipping_base	{dotted-circle}	decimal	Shipping cost in base currency
tr_state	{dotted-circle}	string	Delivery address: state
tr_tax	{dotted-circle}	decimal	Transaction tax value (such as amount of VAT included)
tr_tax_base	{dotted-circle}	decimal	Tax applied in base currency
tr_total	{dotted-circle}	decimal	Transaction total value
tr_total_base	{dotted-circle}	decimal	Total amount of transaction in base currency
true_tstamp	{dotted-circle}	timestamp	User-set exact timestamp
txn_id	{dotted-circle}	string	Transaction ID
unstruct_event	{dotted-circle}	JSON	The properties of the event
uploaded_at	{dotted-circle}
user_fingerprint	{dotted-circle}	integer	User identifier based on (hopefully unique) browser features
user_id	{dotted-circle}	string	Unique identifier for user, set by the business using setUserId
user_ipaddress	{dotted-circle}	string	IP address
useragent	{dotted-circle}	string	User agent (expressed as a browser string)
v_collector	{dotted-circle}	string	Collector version
v_etl	{dotted-circle}	string	ETL version
v_tracker	{dotted-circle}	string	Identifier for Snowplow tracker