Delivery app and online store reviews: AI drafts the reply, the owner approves it
Collecting reviews, sorting them, and drafting replies can be automated. A person does the final check and posts the reply. Replies go to customers under the store’s name, so no reply should be posted without the owner reading it.
The real problem is not that checking takes effort. It is reviews that get missed. Reviews keep arriving, but someone only checks now and then, and low ratings go unanswered in the meantime. So the design starts not with “writing faster” but with “tracking the reviews that must not be missed”.
① Collection: start with one platform
Each platform has its own authentication and data format, so a separate collector is built for each. Connecting all of them at once makes the system heavy, and one failure can stop everything. We start with the platform that gets the most reviews and add others from there.
One thing to check first
Each platform’s terms set out how much data from the merchant system may be taken outside. For example, Article 38(2) of the Coupang Eats merchant terms restricts providing statistics from the seller system to third parties or processing them, and Article 44(2) of the same terms makes the seller responsible for managing the ID and password.
This is not difficult. Check the merchant terms of the platform you use once, and start with what is permitted. Terms differ by platform, and even within one company the rider terms and merchant terms are different.
We do this check for you when you contact us. Just tell us which platforms you use. The technical criteria are covered in Web crawling: what is allowed.
② Drafting: what the AI receives
The AI receives more than the review text. The star rating and the platform are included too. Even for the same wording, a reply to a 5-star review should differ from a reply to a 2-star review.
Drafts are generated within a set character limit. Replies display differently on each platform, so the limit is set after posting a real reply and checking how it looks.
There are clear limits. Emotional reviews and apologies that could be misread need to be edited by a person.
③ Check and post: from writing to choosing
- Open the review list
- Read the AI draft
- If it is fine, post it with one approve button
- If not, edit it on the spot
The button appears only on reviews that have not been answered. You can see at a glance what is still pending.
One thing must be decided: who gives the final approval.
④ The numbers to show on screen
| Metric | Why it matters |
|---|---|
| Unanswered low-rated reviews | Shows the backlog at a glance. Each store decides what counts as a low rating |
| Reply rate against target | Total counts alone do not show whether you are falling behind |
| Keyword and sentiment analysis | Shows reasons that ratings alone do not |
| Comparison by platform | Shows where ratings differ |
The last decision: should it run around the clock?
A setup that only runs while a PC is on is built differently from one that runs without it. Customers leave reviews at different times from when the owner is at the PC, so without around-the-clock operation, reviews will still be missed.
This is hard to change later, so it is decided at the start.
All we need is the name of the delivery app or online store you use.
There is no need to count your reviews. Tell us which platforms you use, and we will start by checking their merchant terms and tell you how much can be automated.
→ Contact us about review management · See our work
References
- Coupang Eats(쿠팡이츠) merchant terms of service, Article 38(2) · Article 44(2) [verified: original terms, retrieved 2026-08-17]
Sources
The terms were checked against the published original text (verified 2026-08-17): Coupang Eats(쿠팡이츠) merchant terms of service, Article 38(2) (no provision of seller-system data to third parties, no leaking or processing of it) and Article 44(2) (the seller bears losses caused by leaking, transferring, or lending an ID or password). Terms differ by platform, so the original terms of the platform you use apply. This article does not cite figures or clients from any specific project.
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