A cloud-based contact center solution
The client–a medium-size business in California–wanted a cloud-based contact center solution that would facilitate automated request processing, improve customer service and allow them to monitor employees’ work.
The super admin creates a minimal infrastructure for the project; the admin configures its infrastructure, creates widgets, adds agents to the system, and monitors chats in order to check the agents' work; the agent receives a customer request and helps the user solve the issue.
A customer explains their issue to the chatbot and gets an automatic response that contains the numbers of the various departments. The user then sends a text message containing the number of the necessary department. The request is delivered, and an available agent undertakes the task.
Generally, only the customer can start communication, but in Telemojo the dialogue can be initiated by the customer and the agent.
Twilio Flex is the first fully programmable contact center platform that offers many features out of the box.
We chose Twilio Flex because it empowers the developers' work processes: They can build a major part of their apps on Flex while adding and customizing the logic and UI to their needs, modifying elements along the way.
As a result of such a choice, the client saved time and money.
We needed to give users the ability to upload files and images in messages.
Twilio Flex doesn’t provide this feature, so our team set it up manually by connecting Amazon S3 Buckets.
Flex allows only one-way dialogue between a customer and an agent. So, only a customer can initiate that dialogue. The client wanted to personalize customer service, so we needed to make two-way chat possible.
To enable a two-way chat, our team investigated how communication is initiated and enters a Flex general process. We analyzed its parameters and logic, and we manually implemented a solution that would allow agents to write messages first.
We needed to set up Studio Flow so that it could work with an API. Unfortunately, the documentation had no task description. We quickly found that each project part required a separate flow.
First, in Twilio Studio we made a skeleton for a chatbot. Second, we implemented the ability for a super admin in order to generate a JSON file, substituting the necessary variables for each project. The JSON file was then used to create a new Studio Flow and build a chatbot frame so as to avoid having to prepare it manually. As a result, our engineer made two flows: one for a webchat and the other for messages.
The result of our work was a complex contact-center solution that satisfied the client's needs.
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