Ai-driven Marketing Platform for Campaign Decisioning and Predictive Analytics
AI & ML|BDaaS|Business/Productivity Software|Media and Information Services
2019
Palo Alto, US
Apache Airflow|PostgreSQL|Python|Snowflake
AI|Data Engineering|Data Science|Machine Learning Analytics|Software Development
Dedicated team behind the project
The Client
This project involved a collaboration with conDati, a forward-thinking marketing team seeking to elevate their customer experience through data-driven insights. The company specializes in transforming massive volumes of customer, event, and transaction data into accessible insights and usable information for their clients. They offer advanced marketing data analysis solutions.
Their primary goals were:
- Improve marketing campaign effectiveness.
- Achieve rapid implementation within budget constraints.
- Augment their team with seasoned development expertise.
Client Achievements:
The Challenge
Condati aimed to enhance their existing marketing data analysis platform to provide clients with a more granular and real-time data-driven approach. They needed a solution that could:
- Consolidate and structure data from diverse sources (website traffic, social media, digital ads, etc.) in real-time.
- Generate actionable insights presented in clear, user-friendly reports.
- Provide predictive models to optimize future marketing decisions and maximize revenue growth.
- Offer anomaly detection for swift campaign adjustments.
- Visually demonstrate the impact of marketing initiatives on overall business outcomes.
What Was Done
To address these challenges, Ralabs partnered with conDati to develop an advanced marketing analytics platform leveraging a Data Science approach. Our team built most of the data engineering, Machine Learning (ML), and backend logic for the platform.
Implemented Features:
Apache Airflow was used to manage and automate data pipelines. It enabled the seamless integration of data from various sources and ensured real-time processing.
Structured workflows are established within DAGs, offering clear visibility into dependencies and execution order.
A user-friendly dashboard allows for seamless navigation and interaction with key marketing insights.
The platform generates forecast models to anticipate future marketing performance and identify revenue optimization opportunities.
Users can establish alerts for unexpected fluctuations in campaign activity, with notifications sent directly to Slack. This integration enables swift corrective actions.
Additional features
- Implemented a system that continuously gathers all available data, including website traffic, social network statistics, digital advertising, and more, in real-time.
- The gathered data is structured in real-time, allowing for immediate analysis.
- User-friendly reports present data in a clear and concise manner, empowering informed decision-making.
- Data visualization tools clearly illustrate how marketing efforts contribute to overall business results.
Results
Real-time insights fueled campaign optimization and improved marketing campaigns by using Data Science approach. Predictive models further improved decision-making, maximizing marketing ROI
The platform not only provides current statistics for the business but also generates forecast models. These models help in determining the best next actions to optimize revenue, enabling more targeted and effective marketing efforts
Leveraging Apache Airflow's "Configuration as Code" approach, Ralabs automated a significant portion of the platform's data pipeline workflows. This resulted in increased efficiency and reduced manual intervention
Businesses receive reports and analyses that are easy to understand and use, enabling more informed decision-making
Tech Stack
Daniel
Head of Engineering at Ralabs
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