Outsourced Adobe Analytics Team for 8-Figure Ecommerce Brand

Hookflash were engaged by an 8-figure ecommerce brand to support with web analytics, media tagging and reporting support across three distinct brands. 

The client was deploying dual Adobe Analytics and Google Analytics tracking, and required significant support in updating their set-up. 

In particular, much of the tracking set-up from an Adobe perspective had remained unchanged since the deprecation of Adobe Dynamic Tag Manager. As a result, many of the tags relied on custom code rather than the more robust rule templates.

As part of a wider replatform and redesign project, the decision was made to migrate the existing solution to a cleaner, more scalable and datalayer-driven tracking model. Hookflash was brought in to lead the project.

The Adobe Analytics implementation had become outdated and difficult to maintain. Most tracking rules in Adobe Launch relied on heavy custom code, including third-party rules and Adobe Analytics event rules. This led to frequent conflicts between Javascript codes in the rules as well as slower site performance. This also made debugging very difficult. 

On the other hand, there was no centralised data dictionary, resulting in inconsistent use of variables and duplicated custom events and variable. Due to siloed working practices, tracking was often implemented ad hoc, without co-ordination or standardisation. 

We partnered to design and implement a robust, scalable Adobe Analytics tracking framework, aligned with their replatforming timeline. 

Starting with a full audit of the legacy implementation, we identified key issues and collaborated with product and marketing teams to define core tracking requirements. We introduced a centralised, data layer-driven model, where all custom variables and user actions are exposed by the application itself. This eliminated dependency on front-end HTML structure. Custom code was replaced with standard Adobe Launch templates wherever possible, reducing complexity and improving performance. 

Alongside the technical implementation, we created a comprehensive data dictionary and documentation to bring clarity and consistency across teams. This included clear definitions for events and variables, helping to standardise tracking and make data more accessible and trustworthy across the business.

The new implementation provided the brand with a streamlined, reliable, and scalable analytics setup. Data quality significantly improved, thanks to reduced duplication, cleaner variable mapping, and consistent data layer usage. Tracking became far easier to maintain and troubleshoot, with fewer custom scripts and conflicts. 

Product and media teams now operate from a shared understanding of web data, reducing silos and improving collaboration. The internal experimentation team gained access to high-quality, event-level data, enabling more accurate analysis and test evaluations. 

Meanwhile, the analytics team was empowered to build faster, more actionable dashboards in Adobe Workspace. 

Overall, our work helped to modernise the analytics foundation, improve site performance, and increase confidence in digital decision-making across the organisation.