Deflection has a good version and a bad version
The bad version hides the contact button, buries the help address, and calls the resulting silence "efficiency." Customers notice, and they leave. The good version answers questions earlier and cheaper than a ticket would — same answer, less friction, for both sides. Everything below is the good version.
Step 1: find the repeats
Export a month of tickets and chat transcripts and tally the questions. Every support queue has a power law: a handful of questions generate a third or more of volume. That short list is your deflection roadmap — nothing else matters until those are handled.
Step 2: fix the cause where you can
Some repeat questions are documentation gaps; others are product gaps wearing a costume. "How do I reset my password?" at volume might mean the reset link is hard to find. "Where is my invoice?" might mean invoices should be emailed automatically. The cheapest ticket is the one the product stops generating — check each top question for a fixable cause before writing an answer for it.
Step 3: put the answer where the question arises
- On the page. If checkout generates shipping questions, the shipping answer belongs on the checkout page — a line of copy, a tooltip, an FAQ block. Zero support interactions.
- In the knowledge base. One public, searchable article per repeat question, written in the words customers actually use. This becomes the backbone of everything downstream.
- Through the AI layer. An assistant trained on that knowledge base answers the long tail instantly, at 3am, without queueing — and hands off to a human, transcript intact, when the question stops being repetitive.
Step 4: let chat absorb what email inflates
A ticket thread is a slow ping-pong: question, clarification, answer, follow-up — days of latency for minutes of content. The same exchange in live chat resolves in one sitting, so it never becomes a ticket at all. Keeping chat honestly staffed (or AI-backed after hours) converts multi-day threads into five-minute conversations.
Step 5: measure deflection honestly
Two numbers, tracked together: volume per customer (raw volume can rise while per-customer volume falls — that is growth, not failure) and resolution without escalation (of the questions your KB and AI absorb, how many stayed absorbed). And one guardrail metric: time-to-reach-a-human. If deflection "works" by making humans unreachable, you have built the bad version — watch that number like a covenant.
What this looks like in MyLiveChat
The knowledge base doubles as your public help center and the AI assistant's training source — one set of answers maintained once. Chat, KB, and AI share the same flat plan, so absorbing more questions never meters your bill.
Most of your volume is created somewhere else
Support teams are measured on ticket volume and control almost none of the decisions that generate it.
A confusing checkout step, a shipping estimate written optimistically, a release that changed a screen
without telling anyone, a billing date that surprises people every month — each of these produces a
predictable stream of contacts, and no amount of faster answering removes them.
This reframes the work. Your job is partly to answer and partly to be the instrument that tells other
teams what their decisions cost. That only works if you can attribute volume to a cause, which is why
consistent tagging is worth the discipline it takes.
Report it as a cost rather than a complaint. “This wording produced four hundred conversations
last month, which is roughly a day of agent time a week” is a sentence a product owner can act on.
“Customers are confused by checkout” is one they have heard before and can safely ignore.
Deflection that backfires
There is a version of deflection that reduces tickets and increases dissatisfaction, and it is easy to
build accidentally because every individual step looks reasonable.
The recognisable forms: hiding the contact route so thoroughly that finding it becomes the customer's
first grievance; an AI or search step that must be exhausted before a human is offered; help articles
that answer the question the company wishes were asked; and a contact form that demands more information
than the answer requires. Each reduces contacts. None reduces the underlying need, and the frustration
resurfaces as a worse conversation later, or as a public review.
The test is whether the customer would choose your self-service route if the human one were equally
visible. If yes, it is genuinely better. If it only works because you hid the alternative, you have moved
a cost onto the customer and called it an improvement.
Making the reduction stick
Deflection decays. An article that removed a hundred contacts a month stops working when the product
changes, and nobody notices because the volume returns gradually rather than suddenly.
Attach an owner and a review date to every fix you make, and re-run the same analysis a quarter later.
The question is not whether volume fell after you shipped the change, but whether it stayed down, which
is a different and much less flattering measurement.
Keep a record of what you fixed and what it saved. Over a year that record is the argument for
resourcing the work at all, and without it the reduction is invisible — the reward for successfully
removing contacts is a quieter queue that looks like less need for the team that made it quiet.