Today companies that run call centers are on the lookout for ways to improve customer service and reduce costs. To achieve these goals, the focus has historically been on outsourcing strategies or on improving their digital presence, to reduce inbound calls. The area often overlooked by these companies is the growth in computing power and cloud computing. Technologies that allow analysis and processing of huge volumes of data, in many cases, in real-time. Given these developments, companies looking to optimize call center operations need to use analytics as a strategic lever.
This paper discusses a hypothetical lending organization, EasyCredit. Its is struggling with addressing high volume calls to their customer care call center. EasyCredit is planning to use data science to optimize their call handling. This paper aims to describe the conceptual design, to utilize the power of Machine learning for optimization and simulation, to streamline call handling. Machine learning algorithms have been used to profile the complexity of callers and profile customer service executives/agents receiving the calls. Simulation has been used to design the abstract of a real system.
What You Will Learn in the Whitepaper
- Overview of Analytical Techniques
- Implementation of Machine Learning and Optimization
- Easy Credit Exploratory Analysis
- Caller Profiling using K-Means Clustering
- Agent Profiling using K-Means Clustering
- Optimization – Skill based Agent Assignment
- Designing Queue Simulation to Support Resource Planning
- Technology Stack
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About Core Compete
Founded in 2012, Core Compete is a pioneer in Cloud Analytics and is based in Durham, North Carolina with offices in Dallas, London and India (Pune and Hyderabad). We currently have 200+ employees and over 450 cloud and technology certifications across these locations, with highly specialized skills including: domain consultants, data scientists, and big data & cloud engineers. We are an ISO 27001 and SOC 2 certified organization.
We have delivered successful cloud analytics and big data transformations for major corporations worldwide. We partner with AWS, Google Cloud, Microsoft Azure, Snowflake, SAS, Hortonworks and Tableau to deliver the modern, elastic cloud analytic solutions.
We have been recognized as:
- Consulting Magazine Top 5 Fastest Growing Consulting Firms 2016, 2017 and 2018
- SAS Partner of the Year (2016, 2018)
- NC Top 10 Startups to Watch