Retail · kids fashion
Support that protects the brand: the agent only says what the brand approved
Automated support with zero brand risk: the agent answers only with what was approved and escalates everything else.
“What scared us most was AI promising something we couldn't deliver. It's the opposite: it answers better than we do because it never leaves the script we approved.”
Where they started
01
Growing volume of size, shipping, and returns questions the team answered late and inconsistently.
02
Seasonal campaigns (back to school, Christmas) multiplied messages exactly when there was least time.
03
A carefully built brand: the risk of a "creative" AI quoting wrong prices or promotions was unacceptable.
A day with the system
An ordinary day at this business, told through the channel itself: what happens while the team works and while it sleeps.
8:30 AM
The team walks in to an inbox that's already caught up: overnight questions were answered as they arrived, in the brand's voice.
10:15 AM
A sizing question before an order. The agent answers from the approved size guide, so the order ships in the right size, with no return already on its way.
1:02 PM
Someone asks about a discount that doesn't exist. The agent doesn't improvise: it only offers promotions the brand has approved.
4:45 PM
A gift that didn't arrive on time. The case moves to the team with the full history summarized, and the customer never has to repeat her story.
7:30 PM
Peak campaign season: messages multiply exactly when there's the least time. Response quality doesn't move.
10:58 PM
Last question of the day: a return, resolved by the approved policy. The team has gone home; the standard hasn't.
-
8:30 AM
The team walks in to an inbox that's already caught up: overnight questions were answered as they arrived, in the brand's voice.
-
10:15 AM
A sizing question before an order. The agent answers from the approved size guide, so the order ships in the right size, with no return already on its way.
-
1:02 PM
Someone asks about a discount that doesn't exist. The agent doesn't improvise: it only offers promotions the brand has approved.
-
4:45 PM
A gift that didn't arrive on time. The case moves to the team with the full history summarized, and the customer never has to repeat her story.
-
7:30 PM
Peak campaign season: messages multiply exactly when there's the least time. Response quality doesn't move.
-
10:58 PM
Last question of the day: a return, resolved by the approved policy. The team has gone home; the standard hasn't.
What was built
Checks
Six automatic checks review every reply before it goes out: prices, promotions, and policies come only from brand-approved information.
Support
Sizes, stock, shipping, and returns resolved instantly, in the brand voice.
Escalation
Anything outside the approved information goes to the team with a summary, in a shared inbox.
QA
Periodic conversation sampling against agreed criteria and a monthly report.
How it was rolled out
The same path we follow with every client: measure before you scale.
Week 0
Diagnosis
We analyze real conversations from the channel and agree in writing on what the pilot has to achieve.
Weeks 1–3
Build
The system connects to the business calendar and tools, and learns only from approved information.
Weeks 4–8
Measured pilot
Live with real customers under supervision, compared every week against the starting numbers.
Week 9 onward
Monthly operation
Full rollout, a monthly results report, and continuous improvement: the system stays operated, not handed off.
Results
87%
conversations resolved without intervention
0
prices or promotions improvised by the agent
−92%
first-response time
Illustrative figures from real systems in operation; names are published with each client's permission.
Your WhatsApp can be your best salesperson.
See it on your own cases: bring three real conversations and we'll replay them in the demo.