Business problem
“Every time we grow, support costs grow with us.”
If support cost rises in direct proportion to customers, the operation has no leverage in it. The fix is not deflection for its own sake — it is making sure the conversations that reach a person are the ones that needed one.
Short answer
Classify a month of real tickets before buying anything. In most businesses a small number of question types account for the majority of volume, and they are almost all status lookups or simple changes that require reading and writing to a live system. Resolve those end to end, route everything else to a person with full context, and measure the share handled unattended rather than a vendor's claimed deflection rate.
What it costs
How the money actually leaves.
- A predictable set of questions — where is it, can I change it, can I return it — consumes the majority of agent time
- First response is measured in hours, which generates follow-up contacts that inflate volume further
- Agents open several systems before they can answer anything, so handling time stays high even for trivial cases
- Weekends and evenings cannot be staffed economically, and customers notice
The expensive detour
The usual fix is a chatbot on the website
A well-written assistant with no system access can describe your returns policy but cannot process the return. Since most volume requires reading live order or account state, deflection lands far below expectation and the organisation concludes AI does not work. The constraint was integration, not language.
Diagnose it yourself
Four questions that tell you whether this is you.
You do not need us to answer these. If the answers are uncomfortable, that is the finding.
- 01
What are your top ten ticket reasons by volume?
If you cannot answer this, that classification exercise is the first project — and it is cheap.
- 02
How many of those require reading live system state?
This number is the real ceiling on unattended resolution. It is also why chatbots underperform.
- 03
What is your median first response time, by channel and by hour of day?
Aggregate figures hide the evenings and weekends where the experience is actually worst.
- 04
How many systems does an agent open to resolve a typical ticket?
Handling time is often dominated by navigation rather than thinking.
Every time we grow, support costs grow with us.
What a CEO actually says
The change
Where the work moves.
Today
3 human steps- Performed by Customer
Asks a routine question
- Performed by System
Queued behind everything else
- Performed by A person
Agent picks it up
Hours later
- Performed by A person
Looks it up across systems
- Performed by A person
Types the answer
After
1 human step- Performed by Customer
Asks a routine question
- Performed by Automated
Identified against live records
- Performed by Automated
Answered and actioned
Seconds, any hour
- Performed by A person
Handles genuine exceptions
With context attached
- Performed by System
Unanswered gaps logged weekly
- Automated
- A person
- System
- Customer
What we build
The capabilities this needs.
Do we have to cut the support team to justify it?
Most clients do not, and the common outcome is the same team absorbing more volume with faster response and less burnout. If headcount reduction is the objective, say so at the assessment and we will model it honestly rather than dress it up as an experience improvement.
What deflection rate is realistic?
It depends entirely on your ticket mix, and anyone quoting a number before reading your tickets is guessing. Classifying a month of real volume tells you the ceiling before you commit to anything.
You already know which process is bleeding.
You already know which process is bleeding.
Tell us how it actually works today — including the workarounds. That is the conversation that leads somewhere. Or email contact@koderead.com directly.
A person replies, usually within a working day