MediBuddy Increased Its CSAT To Over 90% After Moving To Verloop.Io's Chatbot
Customer Company Size
Large Corporate
Region
- Asia
Country
- India
Product
- Verloop.io's Chatbot
Tech Stack
- Chatbot Technology
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Application Infrastructure & Middleware - API Integration & Management
Applicable Industries
- Healthcare & Hospitals
Use Cases
- Chatbots
Services
- Software Design & Engineering Services
About The Customer
MediBuddy is a healthcare service provider that offers a wide range of services including health checkups, medicines, consultations, lab tests, dental care, hospitalization, and genome studies. The company has a large customer base of 175 million and receives over 10,000 calls per day. The company was relying on a team of over 250 service representatives to handle customer queries. However, the team was struggling to manage the volume of queries, especially the technical ones related to policy terms, coverage, partner hospitals, etc.
The Challenge
MediBuddy, a healthcare service provider, was struggling to manage the influx of customer queries across various service verticals such as health checkups, medicines, consultations, lab tests, dental care, hospitalization, and genome studies. The company was relying on traditional communication channels like email and phone calls, and a team of over 250 service representatives. However, the team was unable to handle the volume of queries, especially the 800+ concurrent questions in real-time. The challenge was to automate the customer service process without compromising on customer satisfaction.
The Solution
MediBuddy decided to implement Verloop.io's chatbot to automate their customer service process. The initial aim was to automate a small portion of FAQs, but after a sales call with Verloop.io’s VP – Business Development, the company decided to aim for complete automation with a skeletal support crew. Verloop.io's daily reporting tools helped MediBuddy identify bottlenecks and frequently asked queries, thereby improving documentation. The chatbot's analytic accuracy eliminated the noise that came from human error and intervention. The implementation of the chatbot reduced the customer support staff from over 250 to just 25, allowing them to respond to queries in seconds instead of minutes.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Hospital Inventory Management
The hospital supply chain team is responsible for ensuring that the right medical supplies are readily available to clinicians when and where needed, and to do so in the most efficient manner possible. However, many of the systems and processes in use at the cancer center for supply chain management were not best suited to support these goals. Barcoding technology, a commonly used method for inventory management of medical supplies, is labor intensive, time consuming, does not provide real-time visibility into inventory levels and can be prone to error. Consequently, the lack of accurate and real-time visibility into inventory levels across multiple supply rooms in multiple hospital facilities creates additional inefficiency in the system causing over-ordering, hoarding, and wasted supplies. Other sources of waste and cost were also identified as candidates for improvement. Existing systems and processes did not provide adequate security for high-cost inventory within the hospital, which was another driver of cost. A lack of visibility into expiration dates for supplies resulted in supplies being wasted due to past expiry dates. Storage of supplies was also a key consideration given the location of the cancer center’s facilities in a dense urban setting, where space is always at a premium. In order to address the challenges outlined above, the hospital sought a solution that would provide real-time inventory information with high levels of accuracy, reduce the level of manual effort required and enable data driven decision making to ensure that the right supplies were readily available to clinicians in the right location at the right time.
Case Study
Gas Pipeline Monitoring System for Hospitals
This system integrator focuses on providing centralized gas pipeline monitoring systems for hospitals. The service they provide makes it possible for hospitals to reduce both maintenance and labor costs. Since hospitals may not have an existing network suitable for this type of system, GPRS communication provides an easy and ready-to-use solution for remote, distributed monitoring systems System Requirements - GPRS communication - Seamless connection with SCADA software - Simple, front-end control capability - Expandable I/O channels - Combine AI, DI, and DO channels
Case Study
Driving Digital Transformations for Vitro Diagnostic Medical Devices
Diagnostic devices play a vital role in helping to improve healthcare delivery. In fact, an estimated 60 percent of the world’s medical decisions are made with support from in vitrodiagnostics (IVD) solutions, such as those provided by Roche Diagnostics, an industry leader. As the demand for medical diagnostic services grows rapidly in hospitals and clinics across China, so does the market for IVD solutions. In addition, the typically high cost of these diagnostic devices means that comprehensive post-sales services are needed. Wanteed to improve three portions of thr IVD:1. Remotely monitor and manage IVD devices as fixed assets.2. Optimizing device availability with predictive maintenance.3. Recommending the best IVD solution for a customer’s needs.
Case Study
HaemoCloud Global Blood Management System
1) Deliver a connected digital product system to protect and increase the differentiated value of Haemonetics blood and plasma solutions. 2) Improve patient outcomes by increasing the efficiency of blood supply flows. 3) Navigate and satisfy a complex web of global regulatory compliance requirements. 4) Reduce costly and labor-intensive maintenance procedures.
Case Study
Harnessing real-time data to give a holistic picture of patient health
Every day, vast quantities of data are collected about patients as they pass through health service organizations—from operational data such as treatment history and medications to physiological data captured by medical devices. The insights hidden within this treasure trove of data can be used to support more personalized treatments, more accurate diagnosis and more advanced preparative care. But since the information is generated faster than most organizations can consume it, unlocking the power of this big data can be a struggle. This type of predictive approach not only improves patient care—it also helps to reduce costs, because in the healthcare industry, prevention is almost always more cost-effective than treatment. However, collecting, analyzing and presenting these data-streams in a way that clinicians can easily understand can pose a significant technical challenge.
