Large Sales and Marketing Services Company
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Birst Networked BI
Tech Stack
- Data Analytics
- Business Intelligence
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Revenue Growth
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Big Data Analytics
Applicable Industries
- Retail
- Consumer Goods
Applicable Functions
- Sales & Marketing
- Business Operation
Use Cases
- Supply Chain Visibility
- Real-Time Location System (RTLS)
Services
- Data Science Services
About The Customer
The customer is a leading sales and marketing services company in the consumer packaged goods (CPG) industry. It serves as the hub between CPG manufacturers and retailers, helping CPG clients get products in and out of stores. The company's expertise spans various channels, including the grocery, mass, club, drug, convenience store, and home improvement channels. As the 'middle man' between CPG manufacturers and retailers, the company collects and generates massive amounts of data.
The Challenge
The company, a leading sales and marketing services provider in the consumer packaged goods (CPG) industry, wanted to provide value-added data services to its clients. It aimed to offer analytics on product types, brands, regions, campaigns, inventory, and sales. The objectives were to create value-added services for its clients, give manufacturers visibility into sell-thru rates, and give retailers visibility into product sales, fit, propensity to buy, etc. The technical challenges included managing data relationships between various factors for 1000+ brands across 10,000 stores, the need for near real-time intraday data processing, and catering to 1000+ end users who need easy-to-consume information.
The Solution
The company chose Birst Networked BI due to its capabilities of providing the ability to stamp out new customer environments rapidly. It also offered enterprise scale and speed to value, along with easy-to-use dashboards for thousands of non-analytic users. This solution helped the company to provide value-added data services to its clients, giving manufacturers visibility into sell-thru rates and retailers visibility into product sales, fit, propensity to buy, etc.
Operational Impact
Quantitative Benefit
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