Intercom Fin vs the old Drift flows. The honest comparison: when LLM chat is overkill, and when a decision tree is malpractice.
Intercom Fin replaced an old Drift decision-tree bot. Six months later, an analyst noticed that one entire customer segment was getting worse outcomes than they had under the decision tree. The reason: LLM chat is not better at everything. What to measure in the first 30 days Most teams measure too many things and then measure nothing. The 30-day measurement plan is short: Handle rate.
The 30-day measurement plan is short: Handle rate. Of inbound contacts in the channel where AI is now answering, what percent did AI successfully complete versus escalate or drop. This is the deflection metric in chat language. Median minutes from first contact to whatever the business cares about: booked, ordered, refunded, qualified. Cost per completed interaction.
Intercom Fin vs the old Drift flows. The honest comparison: when LLM chat is overkill, and when a decision tree is malpractice. It is filed under AI Strategy because that is where operators looking for this problem actually start, and it is written from production work rather than from a content calendar.