Download PDF
AbhiBus Achieved a 33% Increase in Agent Productivity after Moving to Live Chat Service
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Natural Language Processing (NLP)
Applicable Industries
- Transportation
Use Cases
- Chatbots
Services
- Software Design & Engineering Services
The Challenge
AbhiBus, a leading online ticketing platform in India, was facing a steep rise in customer queries as they scaled their services to provide technology solutions to state, national and international bus partners. The company needed an AI-powered automated solution that could maintain their excellent customer experience but with minimum human effort and at scale. Prior to implementing Verloop.io, AbhiBus engaged with customers on multiple platforms and agents were spending a lot of time to find and resolve queries.
About The Customer
AbhiBus is a leading online ticketing platform in India. Founded in 2008, this affordable travel provider is a pioneer in end-to-end software and value-added solutions such as e-ticketing, fleet management, vehicle tracking, passenger information and logistics management. As they scaled their services to provide technology solutions to state, national and international bus partners, they saw a steep rise in customer queries. The company has always turned to technology to offer unrivalled customer experience, be it on their ticketing platform or for their customer support service.
The Solution
To address the challenge, AbhiBus leveraged Verloop.io’s conversational support solution which is built on proprietary ML and NLP algorithms. They built a comprehensive FAQ section to create a chatbot enriched with details and integrated it with their CRM. The automation of frequent and repeated questions, be it on ticket status or refund process, allowed customers to self serve and find accurate data, every time. With each passing question, the chatbot improved itself to increase efficiency and achieve human-like conversational skills. With Verloop.io, Agents could find all customer questions (across platforms) in one place, along with real-time customer information and previous chats.
Operational Impact
Quantitative Benefit
Related Case Studies.
Case Study
Airport SCADA Systems Improve Service Levels
Modern airports are one of the busiest environments on Earth and rely on process automation equipment to ensure service operators achieve their KPIs. Increasingly airport SCADA systems are being used to control all aspects of the operation and associated facilities. This is because unplanned system downtime can cost dearly, both in terms of reduced revenues and the associated loss of customer satisfaction due to inevitable travel inconvenience and disruption.
Case Study
IoT-based Fleet Intelligence Innovation
Speed to market is precious for DRVR, a rapidly growing start-up company. With a business model dependent on reliable mobile data, managers were spending their lives trying to negotiate data roaming deals with mobile network operators in different countries. And, even then, service quality was a constant concern.
Case Study
Digitize Railway with Deutsche Bahn
To reduce maintenance costs and delay-causing failures for Deutsche Bahn. They need manual measurements by a position measurement system based on custom-made MEMS sensor clusters, which allow autonomous and continuous monitoring with wireless data transmission and long battery. They were looking for data pre-processing solution in the sensor and machine learning algorithms in the cloud so as to detect critical wear.
Case Study
Cold Chain Transportation and Refrigerated Fleet Management System
1) Create a digital connected transportation solution to retrofit cold chain trailers with real-time tracking and controls. 2) Prevent multi-million dollar losses due to theft or spoilage. 3) Deliver a digital chain-of-custody solution for door to door load monitoring and security. 4) Provide a trusted multi-fleet solution in a single application with granular data and access controls.
Case Study
Vehicle Fleet Analytics
Organizations frequently implement a maintenance strategy for their fleets of vehicles using a combination of time and usage based maintenance schedules. While effective as a whole, time and usage based schedules do not take into account driving patterns, environmental factors, and sensors currently deployed within the vehicle measuring crank voltage, ignition voltage, and acceleration, all of which have a significant influence on the overall health of the vehicle.In a typical fleet, a large percentage of road calls are related to electrical failure, with battery failure being a common cause. Battery failures result in unmet service agreement levels and costly re-adjustment of scheduled to provide replacement vehicles. To reduce the impact of unplanned maintenance, the transportation logistics company was interested in a trial of C3 Vehicle Fleet Analytics.
Case Study
3M Gains Real-Time Insight with Cloud Solution
The company has a long track record of innovative technology solutions. For example, 3M helps its customers optimize parking operations by automating fee collection and other processes. To improve support for this rapidly expanding segment, 3M needed to automate its own data collection and reporting. The company had recently purchased the assets of parking, tolling, and automatic license plate reader businesses, and required better insight into these acquisitions. Chad Reed, Global Business Manager for 3M Parking Systems, says, “With thousands of installations across the world, we couldn’t keep track of our software and hardware deployments, which made it difficult to understand our market penetration.” 3M wanted a tracking application that sales staff could use to get real-time information about the type and location of 3M products in parking lots and garages. So that it could be used on-site with potential customers, the solution would have to provide access to data anytime, anywhere, and from an array of mobile devices. Jason Fox, Mobile Application Architect at 3M, upped the ante by volunteering to deliver the new app in one weekend. For Fox and his team, these requirements meant turning to the cloud instead of an on-premises datacenter. “My first thought was to go directly to the cloud because we needed to provide access not only to our salespeople, but to resellers who didn’t have access to our internal network,” says Fox. “The cloud just seemed like a logical choice.”