Outline

The RED Measurement Framework (RMF) is a collection of javascript code that is to be implemented in a browser based measurement system for tracking of events on websites in the aim of segmenting users based on their behavior.

It's intentionally meant to integrate and work with the following:

• Google Tag Manager (GTM)
• Google Analytics (GA)
• Google Data Studio (GDS)

Integration visualised

Functional resume

As can be seen from the /dist/measurement-framework.js file, a structured set of operations coupled with the use of a standardized and generic naming convention ensures desired functionality.

Basically outlined, the above allows for the placement of consumers in segments based on consumer behavior, by utilizing cookie based data and accumulating (n) number of (x,y or z) events. The events used can be defined independently, but it is recommended to use generic event names, as this increases scalability significantly.

Exemplary segments could be:

• Aware
• Interested
• Considering
• Store Visit Intent
• Ecommerce Intent
• Ecommerce Purchase

The backbone of RMF

The following files can be found in the lib folder and are the backbone of the RMF. The below list presents these files and explains their functional intent.

• ajaxComplete.js (jQuery)

  • A set of operations that configures the tracking of asynchronous javascript and xml (AJAX).

• clientIdSetter.js

  • An operation that fetches the client ID (a numeric value that will be added to every call towards GA).

• contentEngaged.js

  • A set of operations to measure consumer engagement based on i.e. clicks, movement, scrolls etc. A predetermined threshold (usually between 15-20 seconds of activty) defines when a consumer is considered engaged in page content or not.

• customTask.js

  • A set of operations that utilizes the recently released task API from Universal Analytics, which lets you modify a dispathed payload fired to GA. Enabling the sending of i.e. client ID to GA.

• domReady.js

  • A set of operations that allows document object model (DOM) ready events to be fired to GA via callback funtionality. (needs cofirmation from Asim)

• klarnaCheckout.js

  • An operation that lets you track stages in klarnacheckouts, i.e. shipping address changed, order total changed and cannot complete order.

• sendHitTask.js

  • A set of operations that lets us overwrite the initial hitPayLoad in the measurement protocol request sent to GA servers.

• userTrail.js

  • A set of operations that relies on the use of cookies to store consumer web based actions leading to segmentation of consumers.

Optimal usage

As mentioned in the Outline section of this README, RMF is build to integrate and work with GTM, GA, GDS and jQuery. Therefore, it is recommended to use standardized procedures in all of the above to ensure validity in collected data and increase scalability of use.

In GA it is important to follow best practice when setting up accounts, as this will impact how RMF data will migrate with GA. This cannot be stressed enough. The following link is a guideline for what a GA audit might consist of:

[GA Audit Checklist] (https://www.distilled.net/resources/google-analytics-audit-checklist/)

Having successfully migrated the RMF data in GA it's recommended to use GDS to visualise the collected data. A link is provided below in which a GDS template is shared in a view link.

Currently the below link is NOT including any data in its charts, albeit a future commit will follow, in which the link will be updated to include data.

[GDS Template] (https://datastudio.google.com/open/1UyxbaJ8fWvwnE5llwyv2Ad1NeJvlZx5C)

The following screenshots show how data sources are added to or removed from the GDS report.

The next screenshots show how to add data sources. The first screenshot shows the first step in adding data to the GDS report. Choosing a data source, plain and simple, albeit to configure GDS to work optimally, you must either choose a dimension or add another "temporary" data source, then delete it, as shown in the second screenshot, because then you can save your added data source.

The final screenshots show the last steps in adding data sources, the two data sources used at RED Dentsu X and the edit and remove options.

Installation

A chronological list is provided below - explaining the installation of RMF:

• Make sure you have installed npm.

• $ npm init (to make a package.json file)

• $ npm install i measurement-framework

• Copy rollup.config.js to the root directory, from the measurement-framework folder placed within the node-modules folder.

• From the measurement-framework folder placed within the node-modules foler, copy the devdependencies in the package.json file and paste in package.json file in the root directory.

• $ npm install (installing devdependencies)

• To ensure you can execute the final step (rollup -c) in the installation, you'll have to make a src folder and create a file called measurement-framework.js, see the link provided below for further details.

  Measurement-framework example

Compressing the measurement-framework.js code for GTM

Finally, to compress the measurement-framework.js file, run the following:

• $ rollup -c

Confirming the compression has been successful, look inside the dist folder. If the file is there, copy its contents and make a custom html tag in the desired GTM account. In the custom html section, type the following:

<script>
<between the script tags insert the copied compression of measurement-framework.js>
</script>

Additionally, the trigger to be used in GTM is "All Pages". Finally, pick and awesome name for your RMF tag.

GTM and GA setup

GA setup

Unique Google Analytics (GA) variables are used in order for the script and GTM implementation to integrate properly with GA.

• In measurement-framework.js clientIdSetter(<index_no>) must be set for each GA account.
• In measurement-framework.js the userTrails section, must be modified in accordance to funnel-stage agreements.

The following two screenshots exemplify the path you need to use in order to obtain the clientIdSetter value:

When setting the client ID, you must also remember to set the following custom dimensions:

• Raw user trail
• User funnel stage
• Event funnel stage
• Triggering event

GTM setup

In GTM the following steps must be done in order for RMF to be implemented correctly.

Variables to create:

• Custom Task Runner

  • Name : Custom Task Runner
  • Variable Type : Data Layer Variable
  • Data Layer Variable Name : customTaskRunner
  • Data Layer Version : Version 2

• User Funnel Stage Changed

  • Name : User Funnel Stage Changed
  • Variable Type : Data Layer Variable
  • Data Layer Variable Name : funnelStageChanged
  • Data Layer Version : Version 2

• User Funnel Stage

  • Name : User Funnel Stage
  • Variable Type : Data Layer Variable
  • Data Layer Variable Name : funnelStage
  • Data Layer Version : Version 2

• User Funnel Change Label

  • Name : User Funnel Change Label
  • Variable Type : Data Layer Variable
  • Data Layer Variable Name : funnelChangeLabel
  • Data Layer Version : Version 2

• User Raw Trail

  • Name : User Raw Trail
  • Variable Type : 1st Party Cookie
  • Cookie Name : rmf

• Triggering Event

  • Name : Triggering Event
  • Variable Type : Data Layer Variable
  • Data Layer Variable Name : eventAction
  • Data Layer Version : Version 2

• GA settings

  • The below screenshot documents the configuration:

Triggers to create:

• User Funnel Stage Changed
  • The below picture documents the configuration:

Tags to create:

• GA - User Funnel Stage Changed

  • The below screenshot documents the configuration:

• GA - Debug User Funnel Stages

  • The below screenshot documents the configuration:

For the above tags the User Funnel Stage Changed trigger, we just created, is to be used.

Note on building with rollup

Rollup and other javascript compilers do not support removing unused methods from classes. This is why the RMF is running several functions instead of importing a class to hold them. Internally, these use the MeasurementFramework class to hold state and to orchestrate between classes. This makes the package nice and tight.

Honorable mention

This work is heavily inspired by Simo Ahava's blog workings. Therefore we'd like to thank him for his continued interest in working with and utilizing the possibilities within Google Analytics and Google Tag Manager to propel data driven digital marketing forward.