Fetch Achieves 26% More Customer Support with Same Workforce and 3.9x ROI Using Forethought
Fetch's rapidly expanding user base drove recurring ticket surges whenever new app features launched. About 30% of tickets were easily answered FAQ-type questions and another 20% required agents to gather additional information from users, creating a high reopen rate. The team was deeply skeptical of chatbots after poor experiences with clunky keyword-based tools.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Customer submits ticket via email
Fetch's customer support team communicates with thousands of users a day mainly over email.
Tools used
ForethoughtForethought SolveScout
Outcome
After deploying Forethought Solve as their AI agent Scout, Fetch achieved 26% more customer support capacity with the same workforce and a 3.9x ROI, automating 316,000 ticket actions for $90,000 in 11 months, with CSAT scores for fully automated chats as good or better than those of human agents.
What failed first
Fetch initially deployed Forethought Triage to predict ticket content and send automated email responses, but this approach only addressed less than 1/3 of the basic ticket types it was meant to deflect.