Pinduoduo’s overseas version Temu has been launched in the United States for more than two months, and it has delivered an impressive result. Relying on low prices, free shipping for new users, and no threshold discounts throughout the process, Temu topped the list of shopping app downloads in the United States on October 17, with an average daily GMV exceeding US$1.5 million.
If you carefully browse the website of the cross-border "rolling king" Pinduoduo Temu, you will find that there are often other product recommendations below the product detail page, such as " frequently bought together" and "customers who bought this product also bought at the same time" . This method of combined sales is a common method used by major e-commerce platforms. It can not only improve the GMV of the store, but also improve the consumer experience, which is the best of both worlds.
(Picture | Temu official website)
Many independent website sellers also use combination sales on their websites. However, the promotion effect of different stores is different for the same use of combined sales. Some stores have a significant increase in GMV after using it, and some stores have almost no effect after using it.
Where is the problem? After research by SHOPLINE, it is found that the product association rate is the key influencing factor, and most sellers only rely on experience to combine, lacking the reference of relevant data.
To this end, the SHOPLINE technical team has developed an exclusive artifact – product insight report function to help sellers gain insight into the correlation rate between products, allowing sellers to increase store GMV through more accurate combined sales.
Do you want your combined sales to drive the sales of the entire store? Then don't miss this feature!
1. How important is the commodity correlation rate?
Commodity correlation rate refers to the strength of the relationship between two commodities. In e-commerce, products that are often visited and purchased together have a strong correlation rate.
The combination of products with a high correlation rate can bring higher unit price and GMV, such as bohemian dresses and beach hats, which are often purchased together by women who plan to go to the beach for vacation. Sellers often recommend products with a high correlation rate to consumers, which can improve consumers' shopping experience, allow them to continue browsing in the store, and increase store stickiness.
Figure | SHOPLINE front desk combination sales sample
Combining products with low correlation rates will waste the exposure opportunities of the page and shorten the length of time consumers stay on the page. Now that the cost of traffic is getting more and more expensive, sellers need to avoid this situation as much as possible.
Therefore, when doing combined sales, it is very important to grasp the correlation rate between different commodities.
2. How to grasp the data of product association rate?
Although the product association rate is very important for combined sales, most independent website sellers can only judge the product association rate based on experience, lack of data reference , it is difficult to find hidden product combination opportunities, and it is impossible to achieve the optimal product combination .
Which beach hat has the highest correlation rate between bohemian dress type A? How to find out the products with high correlation rate in the store for combined sales? Which products have a better drainage effect on the main products of the store?
If you want to solve these problems, you can't do it by experience alone, and the seller needs to have detailed data as a reference. However, the product insight report launched by SHOPLINE in the merchant management background data analysis report solves these problems.
3. Commodity insight report
How to help sellers combine sales?
The SHOPLINE product insight report provides sellers with accurate and detailed product insight data, including related insight reports and joint insight reports. How does it do it? Let's take a look at the principle behind it.
Correlation Insights Report
View products that are accessed at the same time period and purchased at the same time period.
★Principle of Judgment
Products that have been visited and purchased by the same user in the past 7 days. For example, Alice has visited the product detail pages of product A, product B, and product C in the past 7 days, or purchased additional product A, product B, and product C (there is no requirement for the order in which the consumer jumps to the page).
Figure | Commodity related insights
Associated Insights Report
Check how many users who have visited product A will then visit or purchase product B, so as to judge which products have a high drainage effect on high-traffic products.
★Principle of Judgment
Products that have been visited and added to by the same user in the past 7 days. For example, in the past 7 days, Alice first visited the product details page of product A, and then jumped from the product details page of product A to the product details page of product B to visit or make additional purchases (there are requirements for the order of pages that consumers jump to) ).
Figure | Commodity related insights
After understanding the principle, let's look at the application. Using the analysis results of the product association insight report can bring a lot of help to sellers, including:
(1) Email marketing
Gain insight into users' preferences for products, and provide targeted email recommendations to users to improve user return visits and repurchase rates.
(2) Combined sales
In marketing activities (such as buy X and get Y free), and product applications (such as style combinations, combined sales, etc.), set binding settings for products with high relevance to increase conversion rates and achieve sales.
(3) Commodity delivery
Monitor the drainage effect of the launched products, and focus on using the products with high drainage effect in advertising, landing pages and marketing activities to promote joint sales.
How about it? Isn't this feature very useful! Currently, this function is SHOPLINE's exclusive data analysis tool, applicable to clothing, 3c, home furnishing, pet products and other categories.
Seeing that the Black Friday promotion is coming, sellers who want to increase the GMV of the store, go to the data analysis column of the SHOPLINE management background to optimize the combined sales according to the product insight report!