Custom development
AI customer-support automation
Automate the answers your store can prove — order status, stock, returns policy — and hand everything else to a person quickly.
Scoped and quoted per project. Fixed quote before any work starts. No hourly billing.
WooCommerce customer support automation is worth building when most of your inbox is four questions: where is my order, is this in stock, does it fit, and how do I return it. Three of those have an answer sitting in your database. The fourth usually needs a person, and the value of a good system is that it recognises the difference and stops rather than improvising.
The failure mode of support bots is confident invention — a delivery date nobody promised, a returns window that is not your policy. We ground answers in what the store actually holds: the order record, the stock level, your own policy pages, your product data. When there is no grounded answer, the conversation goes to a human with the context attached instead of looping. Every reply is logged, so you can read what customers were told last week rather than hoping.
Typical build
- Answers grounded in live WooCommerce data — order status, tracking, stock, delivery and returns policy — never invented.
- Identity checks before anything order-specific is revealed, so an order number alone is not a key to someone’s address.
- A hand-off to your helpdesk with the full conversation attached, triggered by uncertainty rather than by a keyword list.
- Scope limits in writing: what it may answer, what it must escalate, and what it never discusses.
- A log of every question and answer, reviewable from wp-admin, with the data used to produce each reply.
Good fit if…
- Most of your support volume is order status and stock questions that the store could answer itself.
- You want automation that cites your policy rather than paraphrasing it into something you did not agree to.
- You need a record of what customers were told, for disputes and for consumer-law obligations.
How it connects to AI visibility
The work is the same underneath. A support assistant answering “what is your returns window” needs your policy in a structured, current, machine-readable form — which is precisely what makes external assistants able to describe your terms correctly in a shopping answer. Stores that write delivery, returns and warranty information properly get both: fewer support mails and fewer wrong answers about them in ChatGPT.
FAQ
Straight answers to the questions store owners ask
Will it make things up?
It answers from retrieved store data and your own policy text, and is built to say it does not know and hand over. That is a design decision with a cost: it escalates more than a chattier system, which is the trade we recommend.
Which model does it use?
Whichever fits the store — the grounding layer and the logs are the build, and the model is a setting. We will tell you the running cost per conversation before you commit to one.
Is this GDPR-safe?
It has to be, so it is scoped that way: minimal data in the prompt, identity verified before order details are revealed, a stated retention period for logs, and a processor agreement with whichever model provider you choose.
Custom development
Tell us what should happen automatically.
Describe the job someone does by hand, or the system your store cannot talk to. You will get a reply from the engineer who would build it, within one working day.
Describe your automation