Use AI to save time drafting customer replies, but treat the model as a drafting assistant—not an oracle. The simplest, safest route is: (1) verify your AI provider’s data‑sharing settings, (2) send only a tiny STORE_SNIPPET (SKU, stock status, short return summary) plus the customer message, and (3) block any message that mentions price, stock, delivery dates, warranty or refunds until a human checks and signs off.
Contents
Check provider data‑sharing
Before you send any customer content to an external model, open your AI provider account docs and settings and confirm whether content you submit may be logged, retained or used for training. For example, OpenAI documents where data may be kept for abuse monitoring and how account-level controls affect retention—owners must verify and set those options in their account before sending PII. See OpenAI’s guidance on data controls for the API and consumer services for what to check in your account: OpenAI API data controls and OpenAI consumer data usage notes.
Choose your STORE_SNIPPET
Decide the minimal set of verified store facts that the model may use. Keep this short and canonical: the goal is to remove invention, not to feed the whole order. Example canonical fields (adapt to your platform and confirm exact field names in your own store):
- product_name
- sku
- stock_status or availability (e.g. instock / outofstock / onbackorder — see WooCommerce product REST fields)
- The WooCommerce product API exposes
manage_stock(boolean) andstock_quantity(integer). Do not assumestock_quantityis meaningful for unmanaged products—check your store’s API responses (it may be null or absent) and handle that case in your workflow. - price (only if safe to disclose and verified by a human step)
- return_window_days or short return summary
For WooCommerce shops, check the official REST API fields and variation docs to confirm where those values live and how variations expose stock fields: WooCommerce product REST fields and WooCommerce variation REST fields. Implementers must confirm exact field names in their own store—plugins or custom code can change them.
Prompt template and instructions
Use a canned prompt template that injects only the STORE_SNIPPET plus the customer message. In the system or instruction text make two constraints explicit: (1) use only the facts within STORE_SNIPPET and the customer message; (2) never invent price, stock, delivery or legal claims. Below is a compact example you can copy and adapt (replace field names to match your store schema):
System: You are a drafting assistant for a shop. Use ONLY the STORE_SNIPPET facts provided. Do NOT invent product details, prices, stock, delivery dates or legal claims. If a required fact is missing, say "I don't have that information—please check" and stop.
User: Customer message: "{customer_message}"
STORE_SNIPPET:
product_name: {product_name}
sku: {sku}
stock_status: {current_stock_status}
stock_quantity: {stock_quantity}
return_window_days: {return_window_days}
Task: Draft a polite, concise reply (2–4 short sentences) acknowledging the request and using only the facts in STORE_SNIPPET. If the reply would mention price, stock quantity, delivery date, warranty or refunds, write a note that human verification is required instead of a full statement.Do not include full orders, payment details or customer IDs in the STORE_SNIPPET. Treat such fields as out‑of‑bounds for external prompts.
Human verification and automated gating
Require human review before any draft mentioning price, stock level, delivery dates, warranty or refunds is sent. Implement a simple automated gate that flags drafts needing verification—use a keywords/phrase detector or a short rule that marks messages containing the words “price”, currency symbols, “in stock”, “out of stock”, “delivery”, “refund”, “warranty” or definite dates. Don’t rely on the model to self‑police; use the gate as a programmatic block.
Human sign-off process (example):
- AI produces a draft and a short machine-readable summary of which STORE_SNIPPET fields it used.
- If the draft triggers the gating rules, the system marks it “Needs verification” and notifies a reviewer.
- The reviewer checks the STORE_SNIPPET against the store admin (or the source-of-truth), confirms the values, records an approval entry (who, when, what they checked) and then either sends the reply or edits the draft and documents changes.
Log approvals and edits for auditability. The approval record should reference the product SKU, the store snapshot the reviewer used and a short reason for any change. Keep these logs internal and subject to your retention policy.
Operational and security checks
Don’t forget the operational side: review your AI provider’s integration best practices (error handling, retries and rate limits) and minimise the privileges of the account that fetches STORE_SNIPPET data. For store security and handling of credentials, follow platform guidance—for WooCommerce see their security best practices: WooCommerce security guidance. For privacy and data‑handling hooks in WordPress, see the plugin privacy documentation: WordPress plugin privacy guidance and the exporter/eraser hooks documentation: privacy hooks and capabilities.
Customer disclosure and privacy pages
Update your privacy policy or FAQ to say if and when customer content may be sent to third‑party AI services, and what you do to minimise the data sent. Don’t invent legal language—state the practical controls you apply (minimal STORE_SNIPPET, no payment data sent, human verification for sensitive claims) and link to your contact method for data requests. For guidance on where to place these settings in WooCommerce and WordPress, review the platform help: WooCommerce accounts & privacy and WordPress plugin privacy guidance.
Test the workflow (fictional example)
Fictional example — labelled: imagine a customer asks whether the “Trailpack 22” is available and when it will be restocked. Your STORE_SNIPPET for SKU TG-100 contains stock_status: OutOfStock and an internal expected_restock_date: 2026-11-01 (ensure the expected date is treated as internal and verified before publication).
Customer message: "Hi — is the Trailpack 22 (SKU TG-100) available? When will you get more?"
Injected STORE_SNIPPET:
product_name: Trailpack 22
sku: TG-100
stock_status: OutOfStock
return_window_days: 30
Prompt: (use the template above)Expected AI behaviour in this fictional test: the draft acknowledges the message, states the product is out of stock using the STORE_SNIPPET value, and includes a human-verification note before any restock date is stated (because expected_restock_date is an internal field that must be checked). The reviewer then checks the inventory system, confirms the date is correct, records approval, and sends or edits the reply. The observable check is simple: the sent message must match the verified STORE_SNIPPET values or include a documented reviewer correction.
Quick checklist
- Open your AI provider account settings and confirm data retention/opt-out options (OpenAI data controls).
- Decide and document your STORE_SNIPPET fields; confirm exact field names in your store API (WooCommerce product API, WooCommerce variation API).
- Implement the canned prompt template that injects only those fields.
- Add an automated gate that flags drafts mentioning price, stock, delivery, warranty or refunds.
- Require human reviewer sign-off for flagged drafts and keep an auditable approval log.
- Minimise service account privileges and follow platform security guidance (WooCommerce security).
- Update your privacy policy/FAQ to disclose AI usage and data minimisation steps (WooCommerce privacy settings; WordPress privacy guidance).
That’s the workflow. The next practical action is to open your AI provider account settings and confirm the data‑sharing/retention choices, then implement a single STORE_SNIPPET and test the draft-and-verify flow on a non‑production message channel. For help improving the product facts you feed the model, see related guides: “Writing product descriptions with AI” and “How to use ChatGPT with WooCommerce.”