Problem Statement

The client was managing marketing data from multiple platforms like Google Ads, Meta Ads, Bing Ads, Mixpanel, and APIs such as Ringba and Everflow. However, they lacked a centralized data warehouse, and their data was stored in a single flat table, leading to inconsistencies and requiring high processing power. Additionally, there was no established data model, making reporting and analysis inefficient.

Approach & Solution

DataRopes.ai integrated diverse data sources, built efficient extraction and loading pipelines, and implemented data cleaning and transformation processes within a centralized data warehouse.

We connected data from 5 major platforms (Google Ads, Meta Ads, Bing Ads, Mixpanel, Ringba, and Everflow), consolidating over 1 million rows of marketing data into a unified system.
Using custom Python scripts for API data retrieval, deployed via Google Cloud Functions, we automated the ingestion of data from external sources.
We designed a tailored data model to standardize and optimize the flow of marketing data, reducing inconsistencies.
Automated CI/CD pipelines were implemented to ensure seamless data updates and continuous data integration.

Results & Outcomes

The centralized data warehouse provided the client with an integrated view of over 1 million data points across platforms, improving reporting speed by 35%. The automation saved the team approximately 50 hours per month by eliminating manual data handling, and real-time data updates improved decision-making. The streamlined data flow and timely insights led to a 20% improvement in marketing campaign performance, optimizing resource allocation and delivering a measurable boost in ROI.