AI Services for Customer Support that Solve "Automated Chat Support Quality Evaluation"

Chat support quality is hard to quantify the way ticket volume is, so evaluation tends to lean on individual supervisors' judgment or spot checks. Spot checks only cover a small fraction of interactions, so problem interactions can go unnoticed and unaddressed. AI can analyze conversation logs to quantitatively evaluate tone and resolution process, generating material for coaching.

Reducing reliance on individual supervisors' judgment

Because it can automatically score every single chat log, it surfaces inconsistencies in support quality that spot checks would have missed. Tools that automatically flag interactions needing improvement also make it easier to select training targets. Codifying evaluation criteria explicitly also helps agents feel the process is fair.

Points to compare across tools

• Whether evaluation criteria can be customized to match your support playbook
• Whether results are formatted in a way that's easy to feed back to individual agents
• The scope of integration with your existing chat tool
• How easy it is to review cases where a false positive (an unfairly low score) occurs