Stages of an analytics overhaul

1. Defining objectives

👋 The measurement plan establishes a link between the questions we want to answer and the data needed to interpret them.

KPI: measuring the success of the user experience at key stages

To establish a tagging plan, we make sure to identify the key stages in the user journey and the business issues linked to the platform. This helps define the key KPIs to be analyzed and the essential data to be measured over time.

Business questions : performance-related issues leading to concrete action.

💡 The quality of the answers is determined by the quality of the questions. The measurement plan ensures that the marking plan will meet relevant customer needs.

Examples of best practice

✅ DO

• Does the search function return relevant results?

• What type of articles or content is most influential?

• How do my advertising campaigns compare with my business objectives?

• Where do we lose users in the conversion tunnel?

• How are filters used, and which are the most effective?

• What type of internal promotion works best?

• To what extent do site features contribute to conversions?

• How do you measure user engagement to create retargeting audiences?

Examples of bad practice

⛔️ DON'T

• "Measure clicks on elements and calls to action" ⚠️ What to do with this information?

• "Understanding the user journey"⚠️ Too vague, what actions can we take on this information?

• "Measuring clicks on product listings"⚠️ The number of products selected also depends on the number of "real" displays of each product. Impressions" must therefore be taken into account.

• "Page views, time on site"⚠️ Is it better if the user takes longer?

Additional business requirements

• Which advertising pixels should be considered? (Facebook Tag, Meta, Google Ads, Wizaly, Awin, Snapchat...)

• Should we deploy tracking with or without consent?

• Which CMP (Consent Mananagement Plarform) should we use to manage user consent? (Didomi, OneTrust, Cookiebot, Axeptio, CookiePro, Tarte au citron, Piwik PRO...)

• Is it worth collecting Server-Side data? (Facebook Conversion API, Google Tag Manager Server-Side...)

• Which tools are best suited for data collection? (GA4, Piwik Pro, Matomo, Piano Analytics, Aodbe Analytics, Plausible, Kissmetrics, Amplitude...)

2. Creation of tagging plan

A tagging plan is a clear, up-to-date documentation that details all the tracking for a website or mobile application.

It generally includes information such as events and associated parameters (variables). Advantages include :

• Serves as centralized reference documentation for all stakeholders

• Ensure consistent and accurate data collection for analysis

• Reduce the risk of follow-up errors or missing data

• Facilitate the implementation of new monitoring functions or tools

• Optimize data collection costs by avoiding unnecessary or incorrect tag additions or modifications.

3. Drafting of technical specifications

For developers, technical specifications can provide important information about the requirements and design of a product or system, including elements such as architecture, APIs, data models and other technical details.

In the context of a tracking implementation. Technical specifications generally aim to explain to developers how to pass information into a datalayer on the web or via SDKs for mobile applications.

Specifications will probably have to be tailored to the TMS used (TagCo, Tealium, GTM).

dataLayer.push({
	event: 'share'
	method: 'spotify'
});

Extract from a technical specification for an event share

⚠️ Do not declare empty variablesIf the variable value is not available like user_type , user_id , account_idor user_payment etc. then we do not declare the variable. This will avoid overriding user-level properties in Google Analytics.

⚠️ Events sequenceEnsure the page_view event is always the first event to be pushed on the page

4. Datalayer recipe

Once the developers have implemented the specifications, we need to check that the instructions have been followed.

In particular, you should check :

• Events are sent at the right time to the dataLayer

• Events are not sent twice

• Parameters, event keys and values are correct

You need to have access to a "test" environment (or "qa", "dev" or "preprod", environments take on different names).

5. Tool configuration

Tag Management Systems (TMS), Server-Side hosting infrastructures, analysis tools, Consent Management Platforms (CMP) and attribution solutions must be configured for web data collection.

To check that the beacons are triggered correctly and that the data sent to the various tools (analytics, media and CRM) is correct, you need to perform a final recipe for the various devices.

⚠️ Migration of audiences and other tags An analytics overhaul may involve modifying the dataLayer (the object used to feed the data associated with tags) and necessitating a readjustment of tag settings.

6. Opening BigQuery

Google BigQuery is a data processing and analysis platform that can be used to store, query and analyze data from Google Analytics 4 (GA4). The benefits of using Google BigQuery with GA4 include:

✅ Improved performance for high-volume GA4 data analysis

✅ More advanced query options for exploring and querying GA4 data

✅ The ability to combine GA4 data with other data sources, such as transactional or CRM data, for a more comprehensive analysis

✅ Advanced data analysis features such as machine learning or real-time analysis

✅ The ability to create custom dashboards and visualizations based on GA4 data stored in BigQuery

7. Reports and analyses

If data collection tools such as GA4, Piwik Pro, Piano or Matomo are useful, but are limited in their ability to transform your data into relevant, visual information.

Use a Dataviz tool such as PowerBI or Looker Studio will enable you to answer Measurement Plan questions visually and interact easily with the data.

Sample dashboards :