- Why CCS
- Product
- SolutionsBY BUSINESS TYPESmall & Medium Business
Grow your business
EnterpriseUpgrade your CX
BPO/OutsourcingElevate your operation
BY ROLE - ResourcesINSPIRECONNECTWHY CALL CENTER STUDIO?
- Partners
Transitioning from complex, server-dependent systems (Gen 1: 2000-2010) to early cloud-based solutions with minimal software innovation (Gen 2: 2010-2015), the contact center industry evolved with public clouds and microservices for modular, easier management (Gen 3). The latest generation (Gen 4), epitomized by Amazon Connect and Call Center Studio, fully embraces native cloud services for enhanced scalability, simplicity, and rapid integration, supported by advanced cloud technology use (e.g., Call Center Studio's utilization of 49 Google Cloud services) to achieve superior functionality and financial performance, including leading gross margins.
Not to brag but, we have lots of customers migrating from other call center solutions to Call Center Studio. Here are some of the major pain points customers experienced with their previous call center solutions and how we aided them. In other words, the backstage of our astonishing churn rate of merely 1%.
Call Center Studio enables rapid integrations within days using its microservices, APIs, and serverless framework, complemented by accessible no-code/low-code options for seamless external application connectivity.
Call Center Studio streamlines routing by using skill-based assignments instead of complex scoring, starting with preferred agents and expanding as needed, simplifying the process and avoiding proficiency routing’s challenges.
Call Center Studio’s native multichannel capabilities streamline agent configuration, routing, and reporting by handling all interactions through unified microservices, avoiding the complexity and limitations of competitors’ bolt-on solutions.
Call Center Studio’s CX Pilot uses generative AI selectively for efficiency, answering simple queries like an IVR and escalating to AI only when necessary. This approach optimizes speed, accuracy, and cost, embodying the principle: use a database when possible, generative AI when essential.
