About The Company
Established in the year 1996, the company is a Malaysian and ASEAN content and consumer company leading in the Digital, TV, Radio, and Commerce space. It serves more than 23 million individuals in 5.5 million homes in Malaysia as well as globally. Moreover, the OTT platform of the company provides access to their content at anytime, anywhere and at multiple screens.
The Challenge
In the company’s call centers, the team used to spend every day answering myriads of support requests through telecom model. Due to this traditional method, the team was unable to offer 24-hours support as the responses to the customer queries around, subscription services, product and/or service knowledge, etc were restricted to the working hours due to a lot of human intervention required to offer solution. Moreover, before connecting to the support agent, the customers had to wait in a long IVR queue making it a time-consuming process for customers. Moreover, in a legacy environment, the support agents were spending too much time on basic tasks instead of offering quick solutions to the customers.
As the company started receiving customer complaints due to delayed responses, they decided to look at the root cause and the bottlenecks in the support process. They identified frequent customer queries such as billing queries, renewal-related queries, etc. and decided to build a responsive support model for them. Hence, the team was willing to on-board a customer-centric solution.
Bringing a cost-efficient and intelligent solution accelerating the turnaround time of the entire communication process and providing quick resolutions to the support queries, enhancing the overall efficiency of the support unit, was the biggest business requirement.
The Solution
Content & Intent Management System: The Blazeclan team created an intelligent conversational system (Chatbot) by using Dialogflow. Dialogflow made it easy to add intent and ensured that the system is well trained to understand the incoming query making it a two-way communication system.
WhatsApp Integration: With WhatsApp integration, blazeclan team enhanced customers’ reach offering them a user-friendly and highly engaging support platform. Because of this integration, the customers were getting the solutions to their queries at any point of time, simply by using WhatsApp. As per the statistics of FY2019, the company witnessed an increase of 79% in customer satisfaction.
Account Management: The dynamic conversational system was hosted on AWS EC2 which could be accessed by providing customer account details as an authentication parameter. For example, with the help of Chatbot, the company’s team could get all the account information of both, green-field customers and brown-field customers, such as account id, last payment, the total amount due, etc.
Response Time: To reduce response time for the query raised by the customer, the database was stored on DynamoDB for quick data extraction. The customers who were previously waiting in the telephonic queues could now get the answers in a few milliseconds. This led to an increase of 52% of user engagement.
Agile & DevOps: Blazeclan followed scrum methodology which helped the product owner to get the visibility and track the business requirements efficiently. The deployment process is designed to push out features on production at a faster pace using automated CI/CD pipelines with Jenkins tool.
The blazeclan team also integrated Sonarqube, a tool that checks, tracks, and visualizes source code metrics which has helped in enhancing code standards and reducing critical vulnerabilities and bugs by 92%.
Benefits
- Reduced Turnaround time: Chatbot helped in reducing the overall turnaround time to sort queries. With the programmed keywords, data was extracted and provided within a few milliseconds.
- Enhanced Business Prospects: Using chatbot, the client was able to offer additional services on the go with this highly conversational system as it can deliver more, based on the keywords used for training it.
- Operational Cost: The company reduced tremendously on operation costs by 2 Mn MYR in FY 2019 as the conversational system is less expensive to operate compared to a telecom-based support model which was previously used. Moreover, the client was able to offer additional services through this conversational system.
- Defined Task Delegation: Use of simple and flexible Dialogflow in the Chatbot offered first call resolutions giving the support agents ample time to focus on other complicated queries and tasks which required human interaction.
- High scalability: Auto-scaling feature of DynamoDB offered single-digit millisecond latency, further, handling the heavy rush of users demanding information from the Chatbot.
- Enhanced User-experience & Customer Satisfaction: As AHT (Average Hold Time) was reduced because of Chatbot, the company’s team was able to enhance the overall user-experience raising the customer satisfaction to 79%.
Tech Stack
Amazon EC2 |
Amazon S3 |
Amazon Elastic Cache |
AWS Redis |
Amazon SQS |
Amazon SNS |
Glacier |
Amazon Elasticsearch |
Elastic Load Balancing |
AWS Identity and Access Management (IAM) |
AWS Lambda |
Amazon SES |
Amazon RDS |
Amazon API Gateway |
Amazon CloudWatch |
Amazon VPC |
AWS Athena |
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