1688 customer service tool practical operation: reduce refund rate
# Is a high return rate on quality issues really just a sign of poor product quality?
Once the "quality refund rate" in the backend turns red, many 1688the first reaction of merchants is often to check the production line themselves That's right, but in the actual operation of b2b wholesale, things are often not that simple. In the eyes of the system, "product description does not match" or "wrong size" that the buyer casually checks are all considered quality issues To put it bluntly, sometimes it’s not that your goods are defective, but that the pre-sales information is not aligned, or the after-sales response is slow, making the buyer feel “unhappy” and then click on the refund
Here's a crucial rule detail: according to [1688](... www.1688.com The "merchant service classroom" definition specifies that the numerator for the 30-day quality refund rate is the total number of sub-orders where the buyer's initial refund reason was related to quality issues. the denominator is the total number of sub-orders paid for within the last 30 days. Even if the buyer later changes their reason for return to "dislike/made a mistake," if the initial reason selected was "quality issue," they are still liable for the return. The evaluation period is from t-30 to t-1. the data is lagging. by the time you see the red light and change the details page, it will be too late. ✅ [product experience] quality refund rate ( https://peixun.1688.com/space/l2AmoYb53knMgzdb/detail/MNDoBb60VLrOoyeeuKr0qeKL8lemrZQ3 )
If you're still manually responding to size inquiries and mechanically copying and pasting canned responses, you're wasting at least two hours a day on useless work. This inefficiency isn't just draining; more importantly, it drags down response times, pushing potentially salvageable orders straight into the abyss of refunds.
# Don’t treat customer service tools as chat software, they are your risk control center
Many merchants think that the backend customer service tool is just a "wangwang" and can just send messages. In fact, under the current platform rules, it is more like a "breakwater" for product experience. Through structured data and automated strategies, it can help you eliminate potential refund landmines in advance at three key nodes: pre-sale, during-sale, and after-sale.
| Functional module | Traditional manual mode pain points | Tooling solutions | Expected effect |
|---|---|---|---|
| Smart size recommendation | Buyer chose the wrong size, resulting in a return or exchange. | Tmall genie automatically pushes size charts. | Reduce size-related refunds by 30%+ |
| Product description accuracy check | The title/details page information is unclear. | The system automatically identifies and prompts for optimization. | Reduce discrepancies between product descriptions and complaints. |
| After-sales quick response | Slow manual response leads to buyer dissatisfaction. | Preset scripts + automatic comfort | Improve negotiation success rate |
| Chat history migration | Taobao domain account message lost | 1688 workbench unified collection | Ensure the continuity of inquiries. |
data source: [function notification] taobao domain account cannot communicate with 1688 merchants ( https://peixun.1688.com/space/l2AmoYb53knMgzdb/detail/20eMKjyp81RNX4nnSze7OE5wWxAZB1Gv )
Speaking of which, since the end of may 2024, taobao domain accounts can no longer be directly given to 1688the merchant has sent a message. Historical chat records have also been moved to the 1688 buyer workbench or seller center. This change is actually a signal: the platform is strengthening its control over native service data. Merchants who haven't adapted yet may not even know why they lost their inquiries.
# Three practical axioms: use tools to reduce the refund rate
# # Hand over size recommendations to xiaomimi.
Go to admin panel → customer service management → store assistant settings → product knowledge base. Upload the size chart of the core sku and turn on "smart size recommendation". When a buyer asks, "what height is suitable for size m?", the system directly adjusts the data and returns it in seconds, which is much more reliable than guessing based on experience.
[action] → upload accurate size data and link it to the product id. → [reason] buyers selecting the wrong size is a leading cause of quality-related refunds in the apparel category. → [expected result] we anticipate a reduction of over 30% in size-related refund rates (based on internal platform research data).
# # Conduct regular self-inspections of product descriptions, just like a physical health check-up.
The numerator of the quality problem rate also includes the "main order with quality problems in the buyer's evaluation/refund remarks". In other words, even if there is no refund, as long as the evaluation mentions "poor quality" or "wrong version", points will still be deducted. It is recommended to run the "product diagnosis" in the background once a week to check whether there are any conflicts in the title, attributes, and details page. Is the material specification missing? are all the parameters complete? has the image been over-edited? these are all potential red flags.
[action] → run a weekly product diagnostic report → [reason] mismatched product descriptions are a key driver of quality issue rates → [expected result] reduce passive refunds due to unclear information
# # After-sales sop needs to be embedded in the tool
Everyone says "quick response," but whether you can actually deliver one consistently, regardless of your mood or current state, all boils down to having a solid process in place. Pre-set three types of scripts in the customer service tool, so that customer service does not improvise on the spot:
- quality dispute resolution: acknowledge the issue first, then offer a solution (replacement, partial refund, or return are all acceptable). don't let the buyer feel like you're passing the buck.
- logistics exception follow-up: be proactive in explaining the reason for the delay and when the delivery will arrive. don't wait for the buyer to chase you up.
- negotiation guidance: this is a technical job. Redirect "quality refund" to "mutual agreement" or "buyer's responsibility."
Here's a key point to emphasize: only orders where the outcome of a dispute resolution is "mutually agreed" or "buyer's responsibility" will be excluded from the quality refund rate calculation. Therefore, after-sales communication is not only to solve problems, but also to strive for a judgment result that is beneficial to the store's indicators. ✅ [product experience] quality problem rate ( https://peixun.1688.com/space/l2AmoYb53knMgzdb/detail/NZQYprEoWoer1wddI0zylQ9kJ1waOeDk )
# What to do next
- Take a look at the backend – have you enabled the smart sizing recommendations feature in store honey? if not, aim to have it set up within 48 hours.
- Download the latest "freight sub-line timeliness standard table" and calibrate the promised delivery time. It’s really unfair to make a wrong judgment on quality due to logistics timeout. Freight - detailed route-specific delivery time standards download https://peixun.1688.com/space/l2AmoYb53knMgzdb/detail/YMyQA2dXW793mzjju9X1glx5JzlwrZgb )
- Pull up the quality refund orders from nearly 30 days ago and see where the initial refund reasons are concentrated. Is it more of a sizing issue, or are the product descriptions often inaccurate? focus on optimizing your sales copy and product information based on these pain points, instead of trying to address everything at once.
The tool itself won't automatically lower your refund rate, but using the right strategies can. Transforming customer service from "chat support" to "experience operators" might just be what [1688]( needs to thrive. www.1688.com In the current market saturation, this is what truly allows merchants to maintain a solid foundation.
