Customer support is always reactive. When an average user like you or me is faced with a technical difficulty like Internet outage or cellphone service outage we spend hours on the telephone line or interacting with chatbots trying to get issues fixed. Customer churn rates become very high when they are not satisfied with service. We wanted to challenge the current status quo of how customers are served and how service is managed.
What is our idea?
Our idea is to monitor proactively for device connectivity, cybersecurity threats for business and home customers who subscribe for smart home, security, internet, cable TV and cellular services. Generate a message to a customer if a problem persists and cannot be remotely fixed Inform the customer of next immediately available customer service professional who can come to their home or let the customers schedule a time. Our backend scheduling uses AI to determine which service staff gets it based on expertise at local stores or employees who are conducting installations nearby in that area, based on the time the customer chose. PowerPoint Link: https://1drv.ms/p/s!AhWBaJ2b-xJ_0BzuWXMw5SQhnnVr?e=pNfzlP
How we built it
We used html, css, js for front end. We utilized node.js for php for back end
The device and threat monitoring system looks for issues in connectivity, potential malware or issues and tries to trigger fixes remotely.
For issues that could not be fixed remotely, Node.js is utilized in triggering SMS messages to the customer to schedule for the technical service representative to fix on site.
The scheduling algorithm is based on the inputs of customer's chosen time and location: Finds out a high-likelihood for request acceptance by filtering out the potential matches to the send the request
- proximity of stores that service the problem
- New service installation professionals who are scheduled to be in the neighborhood
When one of the service technicians accepts the request, an SMS is sent to the customer with details of the tech and time.
Challenges we ran into
Accomplishments that we're proud of
Solving a challenge that is valuable to the rogers business
What we learned
We gained better understanding of customer pain points in service and utilized the datasets provided to interpolate. We examined through this app, how large datasets can be harnessed to fit technology seamlessly with minimum to no user interaction.
What's next for Aesir Support Systems
Eliminating middle-men and multiple steps in technical support. Design the modern day support systems. Identifying more threats and fixing more service issues through extensive learnning of the blackbox data of all devices connected in the rogers network.