E-commerce
July 1, 2026
When a store offers personalized AI-driven recommendations, customers may wonder what data is being used, whether their consent is required, and how to opt out of personalization. This issue is as much about trust as it is about compliance.
The chatbot must explain the difference between generic and personalized recommendations, guide the user to their available preferences, and clarify what changes when the customer opts out of certain data uses.
This guide shows how to answer questions about consent for AI recommendations with simple, complete, and helpful phrasing.
Summary
Why must consent to AI recommendations be explained?
A recommendation can seem practical when it helps to find the right product. It can also become worrying if the customer does not understand why that particular product is being proposed to them or what information was used to select it.
The chatbot must make this logic readable. It should not go into excessive technical explanation, but it must indicate what relates to personalization and what relates to a generic recommendation.
Personalization inspires trust when the customer knows they can understand, modify, and refuse it.
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What information should be distinguished?
The bot must distinguish between the data necessary for the service, declared preferences, purchase history, viewed products, wishlists, marketing interactions, and anonymous or aggregated signals if the brand uses them.
It must also explain if recommendations change based on the logged-in account, the device, cookies, privacy preferences, or the responses given in the chat.
How do you explain opt-in and opt-out?
The chatbot can explain where to activate, modify, or refuse personalization: privacy center, cookie preferences, customer account, or unsubscribe link depending on the channel. It must specify that some choices may affect the displayed recommendations.
Refusing a personalized recommendation does not necessarily mean deleting the account, cancelling an order, or stopping transactional messages. This distinction must be clear.
How to address concerns?
If the customer asks why a product appears, the bot can explain the general logic: similarity to a viewed product, popular category, declared preference, or editorial selection. It must not reveal sensitive data or make up a specific reason if one is not available.
If the customer believes their preferences are not being respected, the chatbot must help verify the settings or transfer to privacy support.
How to remain commercially useful?
The response must not give the impression that the customer loses all assistance if they refuse personalization. The bot can offer non-personalized recommendations based on the needs expressed in the conversation, the budget, or product criteria.
Thus, the customer retains control while still receiving relevant assistance.
Which flow to follow?
The flow must separate personalization, consent, and product help.
Identify the issue: data used, displayed recommendation, opt-in, opt-out, or deletion.
Explain the difference between general and personalized recommendations.
Guide toward preferences, cookies, account, or privacy center.
Offer non-personalized product help if the customer refuses personalization.
Forward privacy requests, consent disputes, and data deletions.
Which messages should be used?
To clarify: "Some recommendations may be personalized based on your preferences or interactions, if your settings allow it."
To opt-out: "You can change your personalization preferences from the privacy center or cookie settings."
For alternative: "Even without personalization, I can help you choose according to your needs, budget, and criteria."
When to transfer?
Transfer is necessary if the customer disputes a consent, requests data deletion, reports a sensitive recommendation, requires proof of processing, or is unable to modify their preferences.
The bot must transmit the account, channel, concerned preference, disputed recommendation, action already attempted, potential screenshot, and exact request.
Which KPIs should be monitored?
Follow the questions on AI recommendations, preference modifications, opt-outs, objections, privacy transfers, hidden recommendations, and satisfaction after explanation.
These indicators show whether personalization is understood or if it creates distrust.
Which mistakes should be avoided?
Avoid saying that all recommendations are personalized, denying the use of data without certainty, hiding the opt-out, or using difficult-to-understand legal language.
The chatbot must explain the control given to the customer, not defend AI at all costs.
How can Qstomy help?
Qstomy can connect the chatbot to customer preferences, AI recommendation rules, review workflows, the catalog, shipping restrictions, marketing campaigns, customer service, and logistics data to answer clearly, then transfer sensitive cases with an actionable summary.
The chatbot helps the customer understand the situation without inventing a consent, an internal validation, a product recommendation, an air transport authorization, or a commercial promise that has yet to be confirmed by a reliable source.
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Key takeaways
Key Takeaways
Consent to AI recommendations must distinguish between personalization, general recommendations, preferences, and the data used.
What the customer must understand
The customer must know what they can modify or refuse without losing access to the essential service.
The appropriate limit of the chatbot
The chatbot can explain and guide settings, but it must transfer disputes, deletions, and privacy requests.
Enzo
July 1, 2026
