Feedback on AI review flow
Hi team,
First, the AI-generated follow-up questions are excellent. The contextual analysis by sector is very strong and becomes even better with proper briefing.
However, I have an issue with the current review flow.
When a customer gives a high rating (e.g. 5 stars), the system still allows follow-up answers that include clearly negative wording (e.g. “waiting time was disappointing”). The AI then combines positive and negative feedback and suggests copying this directly into a public Google review.
This creates a problem:
A satisfied customer can unintentionally publish a mixed or negative review on public platforms.
In my view, this is not ideal for two reasons:
It distorts the initial high rating (NPS-style inconsistency).
It increases the risk of users posting unintended negative public reviews.
What I would suggest instead:
The AI should detect negative sentiment keywords in follow-up answers.
If negative sentiment is detected after a high rating, the flow should switch from “public review generation” to an internal feedback form (private feedback / support loop).
Ideally, there should be a final AI “review check” step before anything is sent to Google, to validate consistency between rating and text.
In short, the system is very powerful, but it needs a stronger gating logic before publishing public reviews.
Happy to discuss if needed.
Best regards,
Rudy Mence
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