Slash Resolution Time with AI
By Up to 53%
Case resolution time can be significantly impacted when you do not get the right agent on the case from the start. However, purely manual approaches to case assignment can cause delays due to the human factor; and rules-based approaches are rigid, limited in effectiveness, and require constant maintenance to be effective.
The answer?
AI-driven case assignment that analyzes each case across multiple factors to make a dynamic, real-time recommendation on the best agent to handle the case, right now. By optimizing the support cycle through streamlining case assignments, companies can reduce mean time to resolution by as much as 50%.
Join us on October 27th to see how you can use AI to assign cases intelligently and start watching you case resolution times plummet.
Get the Right Cases to the Right Agents, Right Away
No more round robins. No more assigning cases based only on agent “capacity”. With SupportLogic, agents are matched with cases based on multiple factors including availability and the agent’s demonstrated skillset.
On October 27th, we’ll detail how SupportLogic’s technology helps you get the right cases to the right agents with minimal effort from managers. That results in dramatic reductions in case resolution time and dramatic increases in customer satisfaction.
In this session, we will outline:
- The importance of optimized case assignment
- How AI delivers a superior assignment model to legacy models
- How to quickly implement AI case assignment tools for your business
The SupportLogic team will also show AI-powered case assignments in action with a live product demo.
Join us to see the breakthrough technology that has leaders at Salesforce, Coveo, and Snowflake raving!
Speakers
Martin Schneider
Chief Evangelist, SupportLogic
Ryan Radcliff
Technical Product Marketing, SupportLogic
SX focused companies use SupportLogic
About SupportLogic SX
The Continuous Support Experience Platform
- Seamlessly integrate with your existing ticketing system
- Read every ticket and automatically extract signals using AI/NLP
- Maintain context across conversational and ticket boundaries
- Predict outcome and provide proactive recommendations with intelligent workflows