YNAB replaced a basic chatbot with Forethought and saw deflection jump from 25% to 70%
YNAB's legacy chatbot relied on rigid menus and decision trees, making it hard for users to get correct answers in their own words. Deflection was stuck at 25%, meaning three out of four users required human intervention, and the system could not scale to support YNAB's growth ambitions.
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 chat or email
A customer submits a support inquiry via chat or email.
Tools used
ForethoughtSolve AgentAssist AgentDiscover Agent
Outcome
After deploying Forethought Solve in October 2024, YNAB's ticket deflection rate rose from 25% to over 70% — a 45% improvement over the legacy chatbot — and monthly chat conversations tripled to about 12,000 without requiring additional headcount.
What failed first
The legacy chatbot could not understand natural language context — it could not distinguish whether a user meant their bank account or their YNAB account — and if users chose the wrong menu category there was no easy way to backtrack.