Forethought Solve and Triage help Achievers reach 69% deflection rate and 93% first contact resolution
Achievers' support queue was backed up with repetitive, low-complexity inquiries — 22% were password resets — assigned to agents without context, while a homegrown chatbot provided no deflection capability and no meaningful ticket classification.
Achievers' previous homegrown chatbot lacked the ability to deflect simple inquiries, causing the agent queue to back up with tickets that should have been self-served.
Achievers achieved a 69% deflection rate with Solve (far exceeding the initial expectation of 10%), 93% first contact resolution, a 50% increase in engagement score, and eliminated the need for 5 support agent headcounts through natural attrition.
Show all 9 reported metrics
Frequently asked questions
What did this team achieve with this AI workflow?
Achievers achieved a 69% deflection rate with Solve (far exceeding the initial expectation of 10%), 93% first contact resolution, a 50% increase in engagement score, and eliminated the need for 5 support agent headcou…
What tools did this team use?
Forethought, Solve, Triage, Discover, Salesforce Service Cloud.
What results were reported?
Solve deflection rate: 69%; Triage and Solve combined deflection rate: 44%; First contact resolution rate: 93%; Engagement score increase: 50% (source-reported, not independently verified).
What failed first in this deployment?
Achievers' previous homegrown chatbot lacked the ability to deflect simple inquiries, causing the agent queue to back up with tickets that should have been self-served.
How is this customer support AI workflow structured?
Support inquiry arrives → Triage predicts and classifies ticket → Spam detection deflects spam → Solve resolves repetitive tickets → Gap detection content feedback → CSAT metrics collected.