We need to reduce customer support ticket volume by at least forty percent using an AI knowledge base. Where should I start?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
We need to reduce customer support ticket volume by at least forty percent using an AI knowledge base. Where should I start?
1 real search · 1 real-search pass
AI customer support knowledge base ticket deflection best practices measure containment rate resolution rate 2025Google ↗
OBSERVEDReason
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (1)
Classes come from the query-classifier (a local Laya model). 1 of 1 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT1 real searches · gpt-6
AI customer support knowledge base ticket deflection best practices measure containment rate resolution rate 2025 Google ↗
- Ticket deflection vs. resolution: Metrics that matter · zendesk.com
- Plain — AI Ticket Deflection for B2B SaaS: Cut Volume Without the Per-Resolution Penalty (2026) · plain.com
- AI Customer Support Benchmarks: Resolution, Containment and Deflection Rates (2026) · supportrequest.ai
- Explore Zendesk · zendesk.com
- Explore Intercom · intercom.com
- Explore Freshdesk · freshworks.com
- Explore Salesforce Service Cloud · salesforce.com