Taking advantage of the Django framwork, I extended the user model so every user would have a profile with the office extension, their location, languages spoken, date of hire, and manager. The website was a collention of the following application:
- Utilities - Call quality evaluation - Phone system reporting system - Agent management control - Client CRM - Workorce Management System
Each application is described below with the details of the implementation
The utilities app is used to hold the web pages and logic to manage information that would be used across multiple apps. This includes the user profile, logging mechanism, and schedule job script.
The quality app is composed of 2 main pages. The first allows a amanger to evaluate the quality of a call through 7 different sections. If automatically calcualte the score of the call as the information is being entered. Each section allows for comments to be entered.
The second page is a search page for the quality forms that have been saved. Multiple parameters are possible such as the person who evaluated the call, the agent, score, date of the evaluation, and date of the call. From the results you can edit the form again.
As only manager are allowed to access this form, the system controls access to each app through roles. Presenting the app only to those users that have role access.
This is a simple app that holds a single page with a form. The form asks the details of an issue and forwards the infomration to a third party.
This is a complex app as it pull data from 4 different systems. It aggregates this data, and displays the information to the agent to the agent is aware of their performance in real time.
The system uses API to connect to the phone, email, and chat system. This allows the agent to manage their status on their phone, see their daily calls, emails, and chats as well as provides a basic reporting framework to allow the agent to see his/her intraday stats.
The fourth system is a connection to a SQL database to pull the satisfaction provided by users that interacted with the agent, as well as to pull comments from the survey.
The user control is well managed through the User Authorization app provided by default in Django and the extension of the user information through the profile model implemented in the Utilities app.
The app is composed of a web form to capture the information relevant to support the client in the long run. This includes number of members associated with the client, date of launch, languages required to support the users, solutoin sold, telephone numbers required, and any additional comments
The code in the back end automates the creation of IVR flows, chat windows, and email addresses based on the information entered. All of this is possibl through API connection to the different systems managing each channel of communication.
This is a complex app that uses Machine Learning in order to forecast call, email, and chat volume. As well, it uses algorithms to schedule agents in the most efficient way possible.
Due to the complexity of the system, I have created a different page for this app detailing the features of it and the roadbloacks I faced through its implementation