Company Size
1,000+
Product
- Service-IQ
- Marketing Analytics
Tech Stack
- Big Data Analytics
- Machine Learning
- Real-time Edge Analytics
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
- Revenue Growth
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Machine Learning
Applicable Industries
- Telecommunications
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Cybersecurity
- Predictive Maintenance
- Supply Chain Visibility
Services
- Data Science Services
About The Customer
With millions of subscribers nationwide, this popular Mobile Service Provider has earned its position as a market leader by providing its customers with quality service, relevant products and new offerings. The marketing team developed a plan to offer advertising agencies target market insights to optimize their advertising ROI. They planned to gather subscriber analytics including demographic, geographic and behavioral statistics in an anonymous format, and offer this information to current and prospective advertising customers.
The Challenge
The marketing team of a leading Mobile Service Provider had a plan to offer advertising agencies target market insights to optimize their advertising ROI. They planned to gather subscriber analytics including demographic, geographic and behavioral statistics in an anonymous format, and offer this information to current and prospective advertising customers. However, due to the size of the network and volume of data that needed to be analyzed, the option of rolling out a deep packet inspection solution was extremely cost prohibitive and could not be done within the timeframe needed. The complexity of correlating content data with subscriber demographics and geographical location, put the marketing team’s initiative beyond reach.
The Solution
Guavus worked with the network team to deploy a cost-effective advanced analytics solution that met the needs and timeframe of the marketing team. Millions of records per second of subscriber content data were collected in each regional site and analyzed in real-time. The redundant data was stripped off and only the pertinent information was transported to the central data center on an hourly basis, where it was enhanced with demographic information from the data lake. By analyzing the data up front rather than later, the Service Provider was able to avoid sending huge amounts of unnecessary traffic across their network and less storage was needed at the central data lake. With the aggregated data in hand, the marketing team could then create customer segments based on the needs of the advertising agencies who could in turn present their services and products to the right audience.
Operational Impact
Quantitative Benefit
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