How to Set Up End-to-End Analytics for a Leading Employment Agency in Europe

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Project team: Ihor Pavlenko (Internet Marketer), Olha Hornostaieva (Web Analyst Team Lead), Oksana Demecheva (Project Manager), Oleksandr Konivnenko (Department Head).

Our client
In this project, our client was a leading recruitment agency that provides employment solutions for people from Ukraine and Eastern Europe for companies in Poland and the EU. It helps companies find employees for various sectors, including industry, logistics, and agriculture.

The challenge
Our client was actively attracting users through saudi arabia number dataset traffic channels, including Meta Ads and Google Ads. However, there was a problem: each tool produced separate reports that their employees had to combine manually. While the actual number of leads was only visible in the CRM system, the source of the leads was in Google Analytics 4 (GA4). To further complicate matters, the costs were in the advertising accounts.

Our task was to combine all sources into one automatic report to minimize the amount of manual work.

Stages of implementation
1. Tools and architecture development
To build end-to-end analytics, we primarily used Google tools and services that allowed us to automate data collection, processing, and visualization. Here is a diagram of the solution architecture:

Нижче — схема архітектури рішення.

The solution is long-term and stable, and it is also cost-effective. Using all the tools in the Google Cloud infrastructure costs no more than five dollars per month for this amount of data..

2. Creating layouts
After receiving all the necessary information from the client, we created report layouts in Miro and got them approved before starting the main work. This helped us save time and avoid misunderstandings when further developing the dashboards.

Це допомогло зекономити час і уникнути непорозумінь у подальшій розробці дашбордів.

3. Data storage and collection
We used Google BigQuery as our central storage method. This cloud-based database was built specifically for analytics, scales automatically, and requires no additional support. Google Analytics data is delivered there daily in its raw form, free of charge.

For advertising sources, we developed a special connector — a Python code hosted in Cloud Functions that automatically downloads data from Google Ads and Facebook daily.