NEOM needed a faster, more efficient way to process ad analytics data from TikTok, Snapchat, and Facebook. Manual data aggregation slowed reporting and impacted decision-making. To solve this, NEOM partnered with Pixelette Technologies, and our team worked closely with them to develop a system that automated data retrieval, enhanced analytics visualization and improved reporting accuracy.
Business Type
Ad Analytics & Automation
Industry
Marketing Technology
NEOM faced inefficiencies in collecting, processing and visualizing ad analytics data across multiple social media platforms like TikTok, Snapchat and Facebook. Manual data compilation consumed valuable time, delaying insights and affecting reporting accuracy. Without an automated system, the workflow remained fragmented and slow.
NEOM aimed to automate and optimize its ad analytics pipeline, reducing the time spent on data retrieval and reporting. The objective was to implement a scalable system that improved efficiency, accuracy and overall analytics performance.
Pixelette Technologies developed an automated data processing system for NEOM, using Azure Databricks, Azure Blobs and Datorama. This solution streamlined data retrieval, centralized analytics and enhanced visualization to reduce manual workload and improve reporting accuracy.
We took a structured, multi-phase approach to building NEOM’s optimized script-processing system. From research to deployment, our team ensured efficiency, scalability and long-term reliability. The project was successfully completed within three months.
We developed an optimized data processing system using Azure Databricks and Azure Blobs. To enhance real-time analytics visualization, we integrated Datorama making sure that NEOM had a clear, interactive view of their ad performance data.
Before deployment, the system was deeply tested. We validated data accuracy, stress-tested system performance and also looked into integration with NEOM’s existing tools. After fine-tuning, we successfully deployed the solution, empowering NEOM with a faster, more efficient ad analytics workflow.
Our team collaborated with NEOM to analyze their existing data workflows, pinpoint inefficiencies, and define key technical requirements for automation. We mapped out pain points and designed a customized solution to address them.
Our engineers automated data retrieval and compilation processes, eliminating repetitive manual work. This significantly improved processing speed and data accuracy, making reporting seamless and reliable.
The strategic IT staff augmentation led to significant improvements and achievements:
The new system delivered measurable improvements, revolutionizing NEOM’s ad analytics efficiency.
70% decrease in time spent manually aggregating ad analytics data.
75% reduction in time required for ad analytics reporting.