Snowflake + DataRobot Unlock the Value of Data at Beacon Street Services
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Snowflake
- DataRobot
Tech Stack
- Snowflake
- DataRobot
- Rundeck
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Revenue Growth
- Productivity Improvements
Technology Category
- Analytics & Modeling - Predictive Analytics
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Finance & Insurance
Applicable Functions
- Sales & Marketing
Use Cases
- Predictive Replenishment
Services
- Data Science Services
About The Customer
Beacon Street Services is the services division of Stansberry Holdings, providing best-in-class subscription-based publications of financial information and software to millions of investors globally. The company is based in Baltimore, Maryland. Beacon Street Services is the services arm (and one of a handful of affiliates) of Stansberry Holdings, and they produce financial publications that are exclusively available through purchased subscriptions. For its marketing and sales teams, there was an opportunity to improve on previous tactics and processes of selling subscriptions, with a clearer feedback loop and signal for marketers to optimize their campaigns.
The Challenge
Beacon Street Services, the services division of Stansberry Holdings, provides subscription-based publications of financial information and software to millions of investors globally. The company had a vision to have one single source of truth for all of its data, housed within Snowflake, to ensure consistency and accuracy across all applications of that data. Having migrated from AWS Redshift to Snowflake several years ago, the company had collected and stored great volumes of data within Snowflake. However, the company realized there was value to applying a data science approach to this data, especially for its marketing and sales teams. There was an opportunity to improve on previous tactics and processes of selling subscriptions, with a clearer feedback loop and signal for marketers to optimize their campaigns.
The Solution
The company decided to use DataRobot’s enterprise AI platform to build a series of models quickly and automatically, using dozens of the latest cutting-edge data science algorithms. The historical user data they had in their Snowflake data warehouse was loaded into DataRobot, and the team was able to build a series of models quickly and automatically. Running an A/B test between their existing process and the new Snowflake + DataRobot methodology saw the new process gain a 10% lift. The platform also provided a significant time savings for the team. Previously, it would take as long as six weeks to develop a model, with no guarantees that the optimal algorithm was selected. With DataRobot, that time to develop and deploy models that used more appropriate algorithms had been reduced to just one week.
Operational Impact
Quantitative Benefit
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