微信小店带货联盟

Platform introduction:

The WeChat Store Alliance's goods delivery agency search platform is an ecological docking hub built by WeChat to solve the pain points of "WeChat store merchants having difficulty finding goods resources, Twitter users having difficulty finding reliable institutions, and institutional docking needs scattered", positioning it as "WeChat e-commerce Cooperation Match Assistant". Relying on the linkage ecosystem of WeChat stores and video accounts, the platform gathers MCN organizations and delivery teams (i.e.,"delivery organizations") with talent resources and the ability to deliver goods, and breaks the information barrier between "merchants, institutions and pushers" through standardized data display (number of partners/merchants, commission rate). Whether small and medium-sized businesses want to reach more people and bring goods through the organization, or tweets want to join the organization to obtain high-quality supply and commissions, or the organization wants to demonstrate its strength to attract cooperation, they can achieve efficient docking through the platform, which is the key link of "resource integration-cooperation and matchmaking" in the WeChat e-commerce ecosystem.

Core functions:

1. ** Panoramic display of core data of cargo carrying institutions ***

   • Transparency of basic information : Clearly present key information of each institution, including institution names (such as hands-on shopkeeper, star-seeking and strict selection, and easy-to-select), the number of cooperative merchants (reflecting the scale of the organization's talent resources, such as 52 talented people in easy-to-select cooperation), the number of cooperative merchants (reflecting the organization's ability to serve merchants, such as easy-to-select 37 merchants in cooperation), average commission rate (showing benefit distribution strategies, such as easy-to-select average commission rate of 38.0% and easy-to-select shopkeeper 0.0%), helping users quickly determine the strength and adaptability of the organization;
   • Standardization of data dimensions : Unify the statistical standards of data (for example,"cooperative talents" refer to video accounts/WeChat ecosystem talents who have signed contracts or long-term cooperation with institutions, and "average commission rate" is the average proportion of the institutions 'cooperation products), avoid information Confusion and ensure that data from different institutions can be compared horizontally (such as comparing the commission rates of institutions A and B, and selecting partners that are more in line with their own income expectations).

2. Accurate institutional search and screening

   • Keyword search : Support directly locating target institutions by institution name (such as searching for "hands-on shopkeeper"), quickly view their detailed data, and adapt to the precise query needs of users with known institution names;
   • Multi-conditional screening : Presumed support is based on "cooperation to reach the number of people"(such as less than 10 people, 10-50 people, and more than 50 people),"range of number of cooperative merchants"(such as 1-10 companies, 10-50 companies), and "average commission rate range"(such as 0%-10%, 10%-30%, and above 30%) Set filtering conditions to help users narrow down the scope (such as a merchant wants to find an organization with a "commission rate of 20%-30%, and more than 50 people cooperating", you can quickly filter out matching results).

3. Two-way matching support between merchants and tweets

   • Merchants find institutions : Merchants can judge the size of the group covered by the organization based on the "number of people cooperating"(if they want to reach a large number of users, give priority to the organization with a large number of partners), and evaluate the cost through the "average commission rate"(such as small and medium-sized merchants may tend to institutions with moderate commission rates), and finally choose institutions that can match their own products (such as food and clothing) to cooperate and bring goods to solve the problem of "no talent resources and low efficiency in bringing goods";
   • Tweeters find agencies : Tweeters can judge the richness of the agency's supply through the "number of cooperative merchants"(for example, more cooperative merchants means more products to choose from), and judge the revenue space through the "average commission rate"(for example, prioritizing commission rates). Institutions with high rates), get high-quality product links and support for bringing goods after joining the organization, and avoid the problem of "difficulty in finding goods and insecure commissions".

Usage scenarios:

• Small and medium-sized merchants are looking for agencies to bring goods : A WeChat store apparel merchant wants to expand sales through talent but does not have its own talent resources. Through the platform, it selects organizations that "cooperate with more than 50 people and have an average commission rate of 25%-35%"(such as Yidai and Strict Selection), check their partner merchants to confirm their service capabilities, and finally reach a cooperation. Sales growth of 40% will be achieved within one month through agency talent to bring goods;
• Cooperation with agencies : Individual tweets of a certain video account want to obtain stable supply and high commissions. They search for organizations with "an average commission rate of more than 30% and more than 30 cooperative merchants" through the platform. After comparison, they choose Yidai Strictly select, and after joining, get links to beauty and household products. The commission for bringing goods is 20% higher than that for individuals seeking goods;
• Institutions demonstrate their strength and gain customers : A newly established carry-carrying organization improved the data of cooperative talents/merchants through the platform, demonstrated the advantage of "cooperating with 30 people and an average commission rate of 28%", and attracted 5 local food businesses Actively cooperate to quickly open up the business situation.

Applicable population:

• WeChat store merchants : Individual industrial and commercial households, small and micro brand merchants (such as clothing, food, and home furnishing) need to find goods delivery agencies to connect with people and increase product sales;
• WeChat ecosystem tweets : Video number celebrities, bloggers with goods in the circle of friends, community leaders, etc. need to join reliable institutions to obtain high-quality supply, commission guarantee and support for goods delivery;
• Delivery organization/MCN: MCN organization and delivery team with talent resources need to demonstrate their own strength (number of partners/merchants, commission rate) to attract merchants to cooperate with Twitter;
• E-commerce operators : Enterprise WeChat store operators need to select matching partners for the store, formulate cooperation strategies for bringing goods, and improve the efficiency of e-commerce business.

Unique advantages:

1. Closed-loop adaptation of WeChat ecosystem : Only focus on the delivery agencies linked to WeChat stores and video numbers. Institutions, merchants, and tweets are all within the WeChat e-commerce ecosystem, and the cooperation links are short (for example, organizations can directly mount merchants 'stores' products on video numbers) to avoid cross-platform docking losses;
2. Data is transparent and trustworthy : All institutional data is officially integrated and presented by WeChat, and the authenticity of the data is guaranteed. It is different from unofficial information on third-party platforms and reduces the risk of cooperation between merchants and tweets;
3. High efficiency of accurate matching : Through standardized data and multi-conditional screening, the scope of cooperation can be quickly narrowed down and the time cost of "blindly looking for institutions" can be avoided, especially suitable for the efficient docking needs of small and medium-sized businesses and tweets;
4. Free without threshold : Basic query and filtering functions are free and open, and there are no registration or payment thresholds. Small and medium-sized businesses and individual tweets can obtain cooperation information at a low cost, lowering the WeChat e-commerce cooperation threshold.