CASE STUDY

Galeno improves user traceability, reducing lead discrepancy by 86%

 

Client: Galeno   |    OVERVIEW    |    CHALLENGE    |    SOLUTION    |  RESULTS 

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Overview

Data optimisation and user traceability at Galeno: a solution with BigQuery and Consent Mode

 

Galeno, an institute specialising in Professional Healthcare Training, a leader in the Spanish healthcare sector, faced significant challenges with lead duplication caused by an incomplete migration to GA4 and improving user traceability in a cookieless environment. To resolve these issues, Galeno implemented BigQuery technology, which allowed them to correct data discrepancies between GA4 and their CRM and optimise access to information for marketing teams through ad-hoc reporting. 

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Discrepancy of leads 2023 vs 2024

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Cookieless traffic 2023 vs 2024

Challenge

Solving duplicate leads and improving user traceability

 

Galeno faced two crucial challenges in order to make strategic business decisions based on its internal data. The first was to solve the lead duplication problems inherited from an incomplete migration to GA4, which affected around 65% of its conversions, and to improve online user traceability in an environment that is moving, by leaps and bounds, towards global cookieless. 

The correct implementation of this data was crucial, as it allows them to understand the performance of their marketing efforts and the effectiveness of their lead generation strategies in the competitive education sector.

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Solution

BigQuery technology 

Through BigQuery technology, data discrepancies between GA4 and Galeno's CRM were resolved and solutions were implemented to create a time-efficient dashboard for marketing teams, as these teams could access lead data by qualification without discrepancies through ad-hoc reporting in GA4. GA4's integration with BigQuery allowed relevant data to be stored in the Google Cloud Platform, and in parallel, the implementation of Consent Mode ensured user data privacy and regulatory compliance.

Results

Decrease in lead discrepancy and increase in cookieless traffic

 The results were not long in coming, following the implementation of these technology solutions: comparing Q4 2023 vs 2024, lead discrepancy decreased by 86% and the implementation of Consent Mode, coupled with data modelling techniques, allowed Galeno to collect 70% of traffic that was not being measured with cookies, filling gaps in data collection.

In a business like ours, which is directly linked to conversion, the correct measurement of user interaction and conversion advertising data is essential. Thanks to this work, Adsmurai has allowed us to carry out more accurate cross-device tracking.
Arancha Pérez
Digital Content Manager, FP Claudio Galeno

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