Among the Fortune 500 and Global 500, MongoDB customers include 10 of the top telcos.
As the telecommunications market matures, operators are looking for new ways to increase revenue, decrease churn, streamline network operations and deliver new services to monetize their networks. Telcos need to reduce their time to market for new products and services to compete with over-the-top (OTT) entrants like Google, Facebook and Amazon. They have enormous amounts of data in various forms, systems and lines of business. But operational and billing support systems (OSS/BSS) have evolved over the last several decades, and many service providers find themselves supporting a mix of disparate systems, limiting their ability to innovate. MongoDB can help telcos generate new revenue and reduce operational complexity.
With MongoDB Enterprise, telcos can partner with MongoDB and get to success faster with lower cost, effort and risk.
Example Telecommunciations Solutions
Consumer Cloud. Operators are looking for new services to offer customers to increase stickiness and reduce churn. Many are turning to consumer cloud apps like online storage and file sharing. MongoDB offers a superior platform for developing consumer cloud services because of its flexible and scalable data model. By storing raw files with valuable metadata, like viewing permissions, location data and timestamps, MongoDB simplifies the deployment of consumer cloud apps, allowing operators to keep pace with standalone consumer cloud storage sites like Dropbox, social networking sites and online photo album services. These apps not only improve user experience and stickiness but also provide operators a new source of data on consumer behavior.
Product Catalog. Many telcos find it difficult to maintain consistent product catalogs across all their channels: stores, telesales and the web. They need systems that enable product teams to update offers once and have those offers be instantaneously available to consumers searching catalogs in any channel. They also need the ability to change products quickly to respond to shifting market demands. MongoDB’s flexible data model enables telcos to store, categorize, search and update an array of products, such as prepaid and postpaid plans, devices and value-added services. This not only provides a superior customer experience but also accelerates time to market for adding new products to telcos’ portfolios.
Customer Service Improvement. Service is a cornerstone of the telco business, and call centers comprise a large portion of spend and effort. Telcos have troves of customer data -- such as purchasing behavior, demographic information, and product usage -- yet this information exists in various formats and in disparate systems. MongoDB’s flexible and scalable data model can help telcos improve customer experience by serving as a hub to aggregate this information, providing real-time analysis, and serving a 360-degree view of the customer to service and sales representatives. The superior customer experience strengthens customer loyalty and decreases churn.
Machine-to-Machine (M2M) Platform. Machine-to-machine (M2M) communication presents a promising opportunity for telcos to monetize their networks in new ways. But telcos need scalable, highly performant systems that are still cost-effective. Further, to realize the promise of M2M, telcos must deliver value-added data collection, storage and analytical services on top of core data transport. Global operators are choosing MongoDB to power their M2M platforms due to its lower total cost of ownership, scalability and real-time analytics capabilities. By enabling new M2M services, MongoDB is helping telcos offer new services and get to market faster, increasing revenue and differentiating versus competitors.
Other use cases for MongoDB in telecommunications include:
- Location-Based Services
- The Connected Home
- Content Aggregation and "TV Everywhere" Platform
- Real-Time Customer Sentiment Analysis
- Targeted Ad-Serving Platform
- mHealth App
- WiFi Offloading
- Real-Time Network Analysis and Optimization
Pablo Enfedaque, Telefonica Digital
Richard Kreuter, MongoDB
Heather Kirksey, MongoDB
Edouard Servan-Schreibe, MongoDB