Meituan & Dianping Negative Review Auto-Reply Agent: 10-Minute Pacification + Invitation Follow-Up for 8,000 RMB Monthly
Workflow: Use scripts daily to automatically poll Meituan and Dianping store backends to capture new negative reviews. Within 10 m
Key Fields
FIELD STAMPS🔧 Workflow
Use scripts daily to automatically poll Meituan and Dianping store backends to capture new negative reviews. Within 10 minutes, the agent generates a pacification reply based on the review content and submits it automatically, while simultaneously sending an invitation follow-up private message to the user. Inputs are the negative review text and the merchant's historical reply style; outputs are the pending reply and invitation script. Humans spot-check reply quality daily and handle platform risk control prompts or complex negative reviews.
🛠 Setup Requirements
Requires a cloud server or local computer running 24/7, basic Python skills, and experience calling Large Language Model APIs. You need to be able to read interface documentation for the Meituan Merchant Open Platform or Dianping Merchant Backend. Building from scratch takes 2 to 3 weeks; if you write your own crawlers and automation scripts, the cost is about 300 to 500 RMB per month. If you have no coding experience, you can start by using off-the-shelf automation tools combined with manual review to run through the minimum viable process.
🧰 Toolchain
- 🔧 Meituan Merchant Open Platform API
- 🔧 Dianping Merchant Backend Automation Script
- 🔧 GPT or Claude API
- 🔧 Python Scheduled Tasks
💰 Revenue
1. Local F&B/Beauty Merchants (Primary Revenue): Subscription fee charged per store per month, 300-500 RMB/month × 20-30 stores = 6,000-15,000 RMB/month, consistent with the case study target of around 8,000 RMB monthly and scalable to 12,000-15,000 RMB. The proportion of subscription revenue in the total pie is undisclosed (case source, independently unverified); 2. New Client Review Diagnosis (Per-Project Service Fee): Charging 2,000-3,000 RMB per order for first-time cooperating merchants (increasing to 5,000-8,000 RMB/order after establishing cases), taking 5-8 new clients per month = 10,000-24,000 RMB/month. The proportion of this business in total revenue is unspecified (case data, unverified by third parties); 3. Hosting & Maintenance Monthly Fee: Charging cooperating merchants a monthly maintenance fee of 1,000 RMB × 10-15 stores = 10,000-15,000 RMB/month, with the proportion of maintenance revenue in total income also unstated (case metrics, no independent verification records); 4. Opportunity Item - Performance-Based Commission: Commission taken based on store rating/turnover increment. The case study store's turnover rose from less than 2,000 RMB per day to 12,000 RMB, but the commission rate was not publicly disclosed. Earnings from this channel are based solely on case claims, lack independent verification, and their share of total revenue is unmentioned.
💸 Cost
Server costs are about 50 to 100 RMB per month, and LLM API call costs are about 200 to 300 RMB per month. The marginal cost per store is very low, with each new store adding only a small amount of API calls.
⏱ Time Investment
30 to 60 minutes of human effort per day spent on spot-checking and exception handling. If serving more stores simultaneously, daily time input may increase to 1 to 2 hours, with the rest of the time handled automatically by the agent.
🚀 Getting Started
Step 1: Take a familiar local restaurant for a free pilot test, manually capturing negative reviews from the past 30 days. Use the LLM to generate reply templates to show the owner the results. After confirming reply quality and merchant acceptance, write scripts to connect automated polling and publishing. Once proven for one store, replicate to other dining establishments in the same commercial district to form scaled services.
🔑 Keys to Success
- ✅ Review replies must sound human and avoid robotic cookie-cutter templates, otherwise platforms will downgrade merchant search rankings
- ✅ Invitation follow-up scripts must be soft-toned to avoid customer complaints about harassment
- ✅ Single-store service costs must be low enough to support a scale of 20 to 30 stores
- ✅ The 10-minute response commitment must be maintained, as this is the core selling point merchants are willing to pay for
⚠️ 风险
- ⚠️ Meituan and Dianping have risk controls for automated operations; frequently operating from the same IP or device may trigger captchas or account bans
- ⚠️ Some negative reviews involve food safety or serious customer disputes, and automated agent replies may escalate conflicts, requiring human intervention
- ⚠️ Merchants may stop renewing subscriptions if reply results are unsatisfactory, requiring continuous optimization of reply templates and scripts
📌 Real Cases
- 📌 AI Review Manager: No review padding needed, using data diagnosis to help merchants boost ratings from 3.2 to 4.8, source youres.cn
- 📌 AI Online Review Management Side Hustle: Using AI to help local merchants manage reviews and earn 8,000+ RMB/month, source duckdblab.com
- 📌 The GitHub open-source project meituan-reply-bot demonstrates basic technical solutions for automatically monitoring and replying to Meituan negative reviews, proving the process is scriptable