Four reasons why you get discrepancies between Tmall sales data and Alipay cashflow data


If you run a store and try to match Tmall’s sales data with cashflow data in Alipay, you’ll find that the numbers will never match perfectly. Double-entry book keeping should be something pretty straight forward. Why is this always so complicated with Tmall?


“Confirmation of receipt” dictates when funds arrive in Alipay

The concept of “confirmation of receipt” creates quite a mess for accounting and it’s mandatory to first understand how this fits into the timeline of a Tmall order.

This is what a Tmall order’s status can look like. At any point in time, the order can be cancelled or refunded, which complicates things a bit.

The money only arrives at the store’s Alipay account after the customer “confirms” that they received the product. This can happen in one of two ways:


1. Customer manually enters payment password to tell the Taobao app that they successfully received the product.

Why do this?

It’s a necessary step before being able to leave a review. Leaving reviews is a huge part of the Taobao social experience. A shopper awaiting 20 packages at any given day will also likely do this to keep better track of her items.

2. If the customer doesn’t manually indicate they received the product, by default the order will automatically change to “confirmed” status 14 days after the item arrives.

Therefore, there’s no exact time for when the funds will be released by Alipay. You only know that it’s within 14 days of the package’s arrival.

The numbers can change at any time.

Based on when you look at the data, the numbers can change. Orders can get cancelled or put through a refund process at any point along the order’s lifetime. The thing is that it can happen even after the order is marked as completed. This will cause discrepancies as “total” sales can be defined differently. Should it include orders pending payment or shipment? What about refunds?


Different analytics apps will interpret the same data differently

Tmall’s store backend lets you see every single order. It also lets you see summaries through multiple analytics apps like SYCM ( the most-used analytics app) and SEJ. Alipay also has its own summary dashboard. The problem is that these different tools will show you different sales totals. One may have a delay in processing returns data. Another may define a ‘valid sale’ differently. The way they define valid sales may differ from what you have in mind.

Trying to compare two different data sources will often lead to numbers not matching.

There’s always an outlier

Something unexpected will always happen when running a Tmall store, often outside of your own control. But Taobao is set up in a way that makes 99% of those problems the store’s responsibility. As a result, your customer service will have to do some workarounds to deal with unusual situations every month. This will cause discrepancies in numbers that need an appendix of explanations outside the system.

What happens in the end?

In the end, nothing happens. As mentioned in the post about APIs, developers can’t just simply create a tool that can consolidate orders and cashflow data accurately in real time. There’s currently no alternative to existing tools.

With the effects of all these combined, companies trying to get an exact number on a daily basis end up spending countless man-hours just trying to put some numbers into the company database.That’s precious time taken away from activities that actually boost sales.



What can stores do about this?


Despite all this, we’ve never encountered a case where Alipay was overcharging. It’s just that little discrepancies here and there drive some accounting departments or employees crazy when they “need” to put numbers into their system.

Here are some ways to save time on this issue:


Record cashflow and sales separately. Because of the “confirmation of receipt”, those two will never align perfectly due to variable escrow time periods.

Leave some room for small discrepancies. Trying to balance debit and credit down to the penny creates a huge time sink for employees due to the various factors above. The only way to resolve this is by manually looking up orders.

Avoid real-time tracking of orders and sales for record keeping purposes. It is time consuming, expensive and far from being robust due to the way the API platform and app marketplace are set up. Most stores survive or thrive with weekly or monthly records.

Most importantly, don’t try to fit a square peg into a round hole. Make sure the way you record numbers is a good representation of reality. Companies often have a specific way they need to record data in their system and further complicate the data to fulfill that need. They just need to ensure the data they record is an accurate representation of what’s happening in Tmall. If your systems are designed for B2B and cannot accommodate frequent updates for a large number of orders, then it probably doesn’t make sense for it to try to track individual orders.


Cashflow isn’t the only area where interpreting data can be so confusing. Performance, traffic, ad spend all have countless data points that can be overwhelming and hard to interpret. They often produce more chaos than actionable insight, especially when they are all delivered through old school excel and powerpoint reports.

That’s why we finally decided to move away from such excel reports to using power BI. Data is so spread out that it’s hard for any manager to get an accurate birds-eye view without being overwhelmed, especially if they don’t speak Chinese.