Support automation returns money in two different ways and they behave differently. Deflection removes a ticket from a human entirely — the agent answers, the customer is satisfied, no one touches it. Assistance keeps the human but shortens the work: the ticket arrives classified, prioritised, routed, with a draft reply and the relevant history attached.
Deflection is the bigger saving per ticket and the smaller share of volume. Assistance is the smaller saving per ticket across nearly all of it. Most business cases that disappoint were built on deflection alone, and most that hold up counted both.
Take a team handling 3,000 tickets a month at an average of eight minutes, loaded cost €30 an hour. That is 400 hours, about €12,000 a month.
A realistic deployment on a mixed ticket base deflects 20–30% of volume outright — order status, password resets, delivery windows, opening hours — and shortens the remainder by a couple of minutes each through classification, routing and drafting. That combination typically removes 30–40% of the total hours. On these numbers, in the region of €4,000–5,000 a month, against a build that is a small multiple of one month of that saving.
The deflection share is the number to be sceptical about in any proposal, including ours. It is knowable in advance: it is roughly the share of your last six months of tickets that fall into repetitive, answerable categories. Ask for it to be measured, not estimated.
How repetitive your volume actually is. A support base dominated by unique technical problems deflects poorly no matter how good the agent is. Six months of ticket history will tell you before you spend anything.
Whether the answers are written down. The agent grounds its replies in your help centre, macros and past resolutions. If the real answers live in senior agents’ heads, that content is the first phase of the project.
Where the escalation line sits. Refunds, account actions and anything legally sensitive should route to a person by rule. Every rule of that kind lowers deflection and raises trust; that trade is a business decision, not a technical one.
Whether quality is measured. CSAT on automated replies and reopen rate, tracked separately from human replies. Without them, deflection is just a number going up.
Model usage scales with ticket volume and is usually a small line, but it is not zero and it should be in the model. More significant is the review time in the first weeks: someone senior reads a sample of automated replies daily until the escalation rules are tuned. Budget a few hours a week for a month.
There is also a quality risk with a real cost. An agent that answers confidently and wrongly is worse than no agent, which is why confidence thresholds start conservative and are loosened only against measured reopen rates.
Under a couple of hundred tickets a month the saving cannot cover the build; better macros and a clearer help centre will. If your ticket base is genuinely non-repetitive, the deflection assumption collapses and so does the case. And if answers depend on judgement nobody has written down, the agent has nothing to ground on — documenting it is the project, and it has value even if no agent is ever built.