Seller rating is a system used by ecommerce platforms to rank sellers based on their past performance. The purpose of seller rating is to provide buyers with an indication of which sellers are more likely to provide a good customer experience, and to encourage sellers to improve. Seller ratings are typically made up of two components: customer feedback and transaction data.
How Seller Rating Works
When a buyer searches for a product on an ecommerce platform, they’re presented with a list of sellers who sell that particular product. The order in which these sellers are listed is determined by their seller ratings. Sellers with a higher rating are more likely to be listed at the top of the search results, while those with a lower rating are more likely to be listed further down.
Seller rating is constantly changing, as new customer feedback and transaction data is collected. This means a seller’s position in the search results can change over time.
How to Calculate Detailed Seller Rating
The algorithm used to calculate detailed seller ratings and the final score varies depending on the platform. However, they all typically use some combination of customer feedback rating and transaction data, including:
|Customer feedback rating||Transaction data|
|Seller’s order quality score|
Return dissatisfaction rate
Negative feedback rate
Perfect order percentage
Order defect rate
The weight given to each type of data varies depending on the platform.
Capitalise on Long-Tail Keywords
Drive higher ROI by targeting high-converting long-tail keywords and optimising ad spend. Sign up for a 14-day free demo now.
History of Seller Rating
Early Ecommerce Platforms
The first ecommerce platforms did not have seller rating systems. Sellers were simply listed in alphabetical order, or in the order in which they joined the platform. This made it difficult for buyers to know which sellers were more reputable, and led to a lot of scams and fraud.
In response to this, some platforms began to allow buyers to leave detailed feedback for sellers. This was the first incarnation of seller ratings. However, this system was easily gamed by sellers, who would ask their friends and family to leave positive feedback, or pay people for good reviews. As a result, buyer confidence in seller rating remained low.
The Introduction of Schema
In order to combat false and misleading feedback, ecommerce platforms began to use schema. Schema is a system of tags and code that helps search engines understand the content of a website. By adding schema to their feedback pages, ecommerce platforms were able to specify which feedback was real and which was fake. This helped to improve the accuracy of seller ratings, and increased buyer confidence in the system.
The Introduction of Transaction Data
In addition to customer feedback, transaction data is also used in seller ratings. Transaction data includes information such as order history, return rate, and shipping times. This data is used to get a more complete picture of a seller’s performance.
Its use has led to some criticism of seller rating, as it can be difficult to obtain truly accurate data. For example, a seller who ships orders quickly may have a lower return rate – customers who order products for presents will receive them on time, which would lead to a higher rating. However, this does not necessarily mean that the seller is providing quality services.
Despite its shortcomings, transaction data is still used in almost all seller ratings, as it provides a more complete picture of a seller’s performance than customer feedback alone.
eBay was one of the first ecommerce platforms to introduce seller rating. eBay’s rating system is based on customer feedback. Buyers are asked to rate their experience with the seller on a scale of 1 to 5, with 5 being the best. This feedback is then used to calculate the seller’s feedback score, which is displayed next to the seller’s name on their profile page.
eBay also uses transaction data to calculate seller rating. However, this data is not made public. Instead, it is used internally by eBay to determine which sellers are eligible for “top seller” status.
Amazon introduced its own version of seller rating, called Amazon Seller Rating (ASR), in 2009. ASR is similar to eBay’s feedback score, but also takes into account transaction data, such as order cancellations and returns. Amazon rating is displayed as a star rating on a scale of 1 to 5, with 5 stars being the highest rating.
The use of transaction data has led to some criticism of Amazon’s system. Critics argue that the system favours sellers who ship orders quickly, even if they have a high return rate.
The Importance of Seller Rating
Seller rating is important for two main reasons: visibility and sales.
The higher a seller’s rating, the more visible their products will be. This is because they’re more likely to be listed at the top of the search results. Being visible on an ecommerce platform is vitally important, as it increases the chances of buyers seeing (and then buying) a product.
Seller rating also affects sales. Studies have shown that buyers are more likely to buy from sellers with higher ratings. This is because buyers trust sellers with good ratings, and feel that they are more likely to get a good product or service.
Uses and Applications
Consumer Decision Making
Seller rating is often used by consumers to make decisions about which sellers to buy from. Studies have shown that customers are more likely to purchase from a seller with a higher rating, and are also willing to pay more for products from high-rated sellers.
Seller rating is also used by businesses to improve their performance. Many businesses use it as a metric to track their progress and compare their performance to that of their competitors. Some businesses may use seller ratings to inform their marketing and customer service strategies.
Improving Seller Rating
Customer feedback can be improved by providing a good customer experience. This includes things like responding quickly to customer inquiries, shipping orders on time, issuing refunds, responding quickly, and providing good customer service.
Transaction data can be improved by ensuring that orders are shipped quickly and accurately, and that returns are processed efficiently.
Frequently Asked Questions
Which is more important: customer feedback or transaction data?
The weight given to each type of data varies depending on the platform. For example, Amazon gives more weight to transaction data than customer feedback when calculating ASR.
Where can you find seller rating data?
Seller rating data is typically available on the platform where the seller is rated. For example, Amazon provides ASR data on its seller dashboard.
Does the seller rating show in google search?
Yes, the seller rating may show up in a Google search if the platform on which the seller is rated has implemented schema.org markup.