At a Glance: Tagging scheme regressions are a common challenge for marketing and technical teams. This guide covers: What is a tagging scheme regression?, Managing tagging scheme regressions—steps to follow, Creating a well-structured tagging scheme, Implementing automated tests.
Labeling scheme regressions are a common challenge for marketing and technical teams.
Of course, the lack of precise data makes it difficult to make informed decisions, which is why it’s crucial to be able to address these regressions quickly before they affect the reliability of your data layer.
In this article, we explore how to handle labeling scheme regressions to ensure the quality of your analytical data.
What is a marking plan regression?
Tagging scheme regressions occur when changes to a website’s code or structure affect data tracking and analysis, which can result in the loss of information essential for decision-making at various levels:
Advertising: To provide more relevant and personalized ads.
Web analytics: to improve the user experience based on information about user behavior.
SEO Level: To learn exactly how to optimize web content.
A redesign or update to the tracking platform may cause tracking tags to malfunction and, as a result, lead to a regression in the tagging scheme.
By affecting data collection in analytics tools such as Google Analytics or Hotjar, for example, a tagging plan regression causes a discrepancy in performance reports.
This makes it impossible to make “data-driven” decisions, which are essential for understanding user behavior, which is constantly changing.
Managing Marking Plan Regressions – Steps to Follow
There are several tag management practices that make it easier to identify and effectively correct Data Layer anomalies before they significantly impact performance tracking:
1. Have a well-structured labeling plan
A tagging plan (also known as a tracking plan) is a strategic document that serves as a guide for implementing and managing tags on a website.
Its purpose is to clearly identify what information needs to be collected, how it will be collected, where it will be stored, and who is responsible for it.
The main benefits of a marking plan:
Translating business objectives into measurable metrics: helps clarify what needs to be measured and why, by aligning metrics with the company’s objectives.
Optimizing Marketing Efforts: Gaining a better understanding of the effectiveness of marketing campaigns, which helps optimize efforts and increase return on investment (ROI).
Facilitating Technical Implementation: Guides business analysts on where, when, and how to implement the code needed to collect data.
Marking Plan – Best Practices
A well-structured labeling plan facilitates a rapid response to correct a regression before it has a real impact on the collected data.
Name your tags clearly: this ensures clarity and prevents confusion when analyzing the data (or the lack thereof).
Don't try to measure everything: focus on the most relevant data.
Appoint a project manager: This person must have strong technical knowledge and an understanding of marketing issues.
Make the tracking plan accessible to everyone: The tracking plan must be accessible to all relevant members of the organization via Google Sheets, ClickUp, Notion, or Excel, ensuring consistency and proper implementation of the pixels.
2. Implement automated testing
When applied to a data layer, automated tests allow you to regularly verify that tracking tags are working properly on all critical pages of your site.
This real-time monitoring allows you to quickly detect regressions as soon as they occur, and some automated testing tools can alert you in the event of a malfunction or anomalies in the collected data by sending you:
Custom Alerts: Set up alerts to be notified when a critical tag stops working or records abnormally low data.
Automated reports: Receive regular reports on the status of your marking plan to track progress and identify trends or recurring issues.
Here are a few steps to successfully set up automated tests to verify your data layer:
Define critical tags: By analyzing your tagging plan, identify the tags that are essential for your reporting and analysis (transactions, conversions, or user behavior).
Use an automated testing tool: As mentioned earlier, automated testing solutions such as Mr Suricate be used to automatically verify the presence and proper functioning of tags.
Schedule regular tests: This allows you to quickly detect problems and fix them before they affect your reports.
3. Establish a process for approving changes
To prevent regressions, it is crucial to implement a validation process before any code is deployed to production.
Here are some best practices to follow:
Review of Changes: Before implementing changes to the site, consider the potential impact on tracking tags.
Pre-production environment: Test the changes in a pre-production environment to verify that the tags continue to function properly.
Manual verification: In addition to automated tests, manual verification may be necessary to ensure that the tags are properly configured and active on key pages.
4. Foster collaboration between technical and marketing teams
Managing labeling plan regressions cannot be effective without good communication between the technical and marketing teams, as both teams are affected.
Technical teams are often responsible for updating the website, while marketing teams rely on the accuracy of the data collected to optimize campaigns and analyze user behavior.
To facilitate this collaboration:
Reminders and training: Train teams on the importance of tracking tags and data collection to avoid common errors during updates.
Designated point of contact: Designate a point of contact to handle questions related to the labeling plan and coordinate efforts among teams (a Slack channel, for example).
Continuous feedback: Encourage continuous feedback to improve tag management processes and respond quickly to regressions.
Test your Data Layer with Mr Suricate
A proactive approach makes it possible to effectively manage marking plan regressions.
In addition to Data Layer testing, the no-code SaaS solution Mr Suricate a wide range of automated tests to help you manage your acceptance testing and provide your users with the best possible experience.
Take control of your applications and detect bugs in real time on your websites, applications and APIs by reproducing your user journeys at regular intervals.