The internal logic of Amazon’s review capture!

Amazon relies on big data + seller’s fake order records + buyer’s purchase history to catch fake orders
 
First, Amazon can use basic big data such as conversion rate and review rate (for example, if the conversion rate is obviously abnormal) to catch some sellers who are obviously manipulating the rankings. For example, if Seller A
At this time, Amazon will block SellerA's account (of course, it will not be blocked immediately if it is suspicious, but will first conduct a high-level review), and then ask SellerA to write a complaint report, requiring a detailed list of each abnormal VP and review. This means that you have to confess and strive for leniency. (If SellerA does not confess, the store is basically doomed. If he tells everything, the store will restore the sales privileges, but of course all the problematic reviews and even products will be removed)
 
At this time, Amazon will get a new batch of data, which is BuyerA, BuyerB, BuyerC provided by SellerA... Then, based on the comprehensive analysis of these Buyers’ VP and review history data, Amazon will follow the clues and catch SellerB and SellerC...
 
Then SellerB and SellerC are banned from selling, and the above steps are repeated. . . . .
 
This feels a bit like interrogating a prisoner, 2333333
 

The risk of evaluation comes from these Buyers. For example, if the Buyer you find helps ten Sellers to do evaluations, and there is a problem with the data of one of them, you may be implicated.
 

There are two main evaluation methods now. One is to find foreigners or service providers on FB.
One is self-brushing.
 
First, let's talk about the first
 
After more than two years of using Facebook, I have also transformed from a newbie to a so-called "experienced person". It is actually very difficult to find reviews on Facebook. My personal summary is as follows:

1/ Many foreigners raise their own smurfs to look for a "free lunch"

Therefore, when looking for reviews, you must ask foreigners to send a profile, and then match it with the account that left the review. Many foreigners deliberately use their old accounts to lure you, and then use their small accounts to purchase reviews to reduce the risk of their main accounts.

2/ Many fake order agents pretend to be foreigners to receive fake orders without reviews and maintain their own accounts

If you see that the reviewer’s Facebook page is relatively blank, it is usually that most of these people are agents or use fake accounts to pretend to be foreigners and ask you to place fake orders.

3/ Many of those who claim to be foreign students are fake agents

Generally they ask you to transfer money via WeChat or something like that. Most of these are intermediaries because they may not have a foreign PayPal account.

4/ Generally, the studios that help people do reviews make a living from this. They must have many buyer accounts and use VPS or multiple virtual machines. This is not fundamentally different from our own agency reviews.
 
Therefore, it is really rare to find high-quality reviewers on Facebook. I mainly work in the UK and US markets. Reviews from the UK are relatively easy to find, but reviews from the US are really scarce!
 
To sum it up in one sentence, it is difficult to find good and real buyers, and most of them take orders in large quantities. Referring to the logic of Amazon's interrogation of prisoners mentioned above, the risk is very high.
 

The second type is self-brush orders. Let me analyze several common evaluation environments for you:

How to: Install VMware/Virtualbox virtual machine software

Install Win10/Win7 image in the virtual machine

Register a 911 account and install and run 911 on the virtual machine

Advantages: Easy to operate, low cost Disadvantages: When Amazon obtains the virtual machine hardware information, there will be some special identification (for example, the hardware name of the VM will start with vm
As the beginning), it is easy to identify. 911 shared data center IP, if the same IP is evaluated by multiple sellers at the same time, it may trigger Amazon's advanced review. The result is self-evident.

How to do it: Register an Alibaba Cloud/Google Cloud account, create a pay-as-you-go US cloud server, and use remote desktop for operations.

Advantages: Pay-as-you-go, low cost, and real data centers abroad Disadvantages: Pay-as-you-go IPs need to be changed frequently, which is not suitable for number maintenance. When searching for IPs, the IP number segment will be displayed as Alibaba Cloud or Google Cloud.

How to do it: Buy a large VPS server from some service providers, and then divide it into multiple small VPSs, and use virtual network cards to virtualize multiple IPs.

Advantages: Real computer room, fixed IP, can keep the account logged in for a long time, suitable for account maintenance Disadvantages: Use virtual network card for multiple IPs when partitioning, and use intranet penetration tools will be useless. The cost is high, and you need to buy a larger VPS server first.

How to operate: Use software partitioning on iPhone to modify different local parameters

Luminati registration setting fixed exclusive residential IP

Use a disguised iPhone to connect to a residential IP address

Advantages: Compared with PC and Android, iPhone is the best environment. Uses static fixed IP, suitable for account maintenance. Using camouflage software, a 64G iPhone can open 1000+ environments. Disadvantages: The operation is relatively complicated and not easy to use. Luminati IP is also relatively expensive $12.5/G
 
 
Without going into the conclusion, let's first talk about the conditions required for security assessment:
 
I captured the Amazon app (I had 5 years of IT experience before doing cross-border business), and found that the main information Amazon obtained from us included: device model, system version, IP, DNS, location, network operator, system cache, device name, UDID, iMEI, MAC address, IDFA, etc.
 
If we completely simulate these data, can we virtualize countless evaluators?
 
Combining all the above conditions, a perfect evaluation method is available:
 
Compared with PC and Android, iPhone is the best environment, no doubt about it (because Apple prohibits apps from obtaining basic hardware parameters, we can use tools to disguise all the parameters obtained by Amazon)

Using Luminati, we can connect to the home IP of the country to be evaluated (IP address and DNS are country-specific)

The speed is fast, you only need to log in for the first time, and you can enter directly without logging in afterwards. With the fixed IP of luminati, the account is invincible.

The total cost is low, and a 64G iPhone can install more than 1,000 environments.