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Red Ventures Enhances Client Support Through Data and AI
Technology Category
- Analytics & Modeling - Machine Learning
- Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries
- Education
- Equipment & Machinery
Applicable Functions
- Sales & Marketing
Use Cases
- Predictive Maintenance
- Time Sensitive Networking
Services
- Data Science Services
- System Integration
The Challenge
Red Ventures (RV), a global company with a focus on positively impacting people’s lives and communities, was facing a challenge in managing marketing data efficiently. The company's Red Digital division provides end-to-end performance marketing services to help business-to-consumer (B2C) services providers attract new customers. To deliver greater value to clients, RV needed to use timely insights from data to reach the right consumers. However, maintaining each client’s data in a separate cloud environment and integrating each client’s data for machine learning predictions was proving to be a tedious and time-consuming task. Data engineers had to write custom scripts to ingest data for each client, which was not an efficient use of their time and skills.
About The Customer
Red Ventures is a global company that seeks to positively impact the trajectory of people’s lives and the communities they touch. The company's Red Digital division aims to give marketing clients a greater return on investment than they’ve previously achieved. RV provides end-to-end performance marketing services that help business-to-consumer (B2C) services providers attract new customers. The company uses a modern, scalable data solution to optimize search campaigns, social campaigns, display, and landing pages in ways that will turn top-of-funnel marketing leads into repeat customers for their clients.
The Solution
To address this challenge, RV implemented Databricks to scale data engineering pipelines and speed up insights. The company also used Fivetran for data ingestion and dbt™ for data transformations. Databricks became the engine that performed RV’s heaviest computing tasks. For each client environment, RV set up a dedicated Databricks workspace, Fivetran connectors, and dbt™ projects that only designated employees could access. All three solutions fed data into a machine learning pipeline that drove functions such as budgeting for clients’ advertising spend. RV also received click data, event views, page views, scrolling depth, and more into its warehouse, simplifying and automating its ETL workloads.
Operational Impact
Quantitative Benefit
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