New to SupportLogic?
One of the first things you will want to do is to set up a Global Filter. This will help you narrow the volume of cases that are displayed to only those that are relevant to you.
Quickly zero in on the cases that you and those reporting to you are responsible for, create a Virtual Team, which includes your direct reports, and Virtual Account, which could be a list of the customers you are responsible for.
3 Easy Steps
Three easy steps to complete before get you started:
- Define Your Virtual Team(s)
- Define Your Virtual Account(s)
- Create Your Global Filters, leveraging the Virtual Team and Account you created in the previous two steps
- You can further refine the list of cases by combining your Global Filter with Dynamic Filters.
Next step: Start reviewing cases in the Console - The Support Operations Consoles provides an overview of all your open cases today, or going back a week. From the Console you have a bird's eye view of your case backlog and can immediately take actions, assign cases, or add cases to queues to be addressed at a later time.
Sentiment Analysis Core Concepts
Below we have put together a few short videos that introduce how SupportLogic works and how we do signal detection from unstructured case text.
Preventing Escalations Before They Happen
Once you are have set up your Global Filter(s) and become acquainted with the various features of the Console, you can start to gain familiarity with the power that artificial intelligence can arm you with while using SupportLogic.
One key feature of SupportLogic is Escalation Prediction, which is designed to make your life easier and your ability to support your customers for effective.
What is Escalation Prediction?
Check out the 1.5 minute video explanation below for an explanation.
How to use Escalation Prediction
Check out the Escalations Workflow (starting at 6:18 in the video below) to learn how to use the predictive ability of SupportLogic most effectively.
Was this article helpful?
That’s Great!
Thank you for your feedback
Sorry! We couldn't be helpful
Thank you for your feedback
Feedback sent
We appreciate your effort and will try to fix the article