How to optimize Wish seller data to increase product exposure

During the operation of the Wish platform, the integration and analysis of seller data is crucial to increasing product exposure. The Wish platform optimizes its product exposure algorithm by collecting user data and merchant data. This data will not only affect the seller’s product exposure, but also affect the seller’s overall operating results.

1. The importance of data integration and analysis

• Online duration: The Wish platform will detect the online duration of the seller’s account. Stores that are frequently offline will be considered inactive, resulting in reduced exposure.
• Violation rate: Including the proportion of counterfeit products, customer complaint rate, etc. The higher the violation rate, the lower the exposure. For serious cases, the account will be banned.
• Late delivery rate: The Wish platform will monitor the seller’s late delivery rate, including whether orders are shipped in time and whether order logistics information is updated in a timely manner.
• Cancellation rate: If a seller cancels too many orders, the store will be blocked. Therefore, the seller should try to contact the consumer first and request the consumer to cancel the order.
• Effective tracking rate: Poor logistics experience and untimely update of order logistics status will be recorded, affecting the seller’s exposure on the Wish platform.

2. Key indicator analysis

• Sign-in rate: Reflects the delivery status of the seller’s orders. If the seller can ensure that most orders can be signed for within the specified time, the Wish platform will give the seller’s store higher exposure.
• Order defect rate: The order defect rate within a certain assessment period is directly related to issues such as neutral reviews, negative reviews, complaints, and user disputes received by the seller. Orders with three stars or above are evaluated Only if it meets the standards required by Wish.
• Refund rate (rejection rate): When the buyer applies for a refund or refuses to pay due to quality, logistics timeliness, parameter mismatch, etc., the Wish platform will also Will be recorded.
• Return rate: Like the refund rate, the Wish platform will also record when consumers apply for returns due to product problems.
• Timely rate of feedback: When sellers receive feedback from consumers, they must process it in the shortest possible time.
• Push conversion rate: The Wish platform will push every newly launched product that does not have homogeneous competition issues for 3 to 7 days. When the conversion rate does not meet the standard requirements , Wish will stop pushing the product.
• Store level: Store level is directly related to transaction volume and user reviews. The store level in the Wish platform adopts a points system. In order to obtain higher exposure, sellers need to increase the level as much as possible. own score.
• Product homogeneity: Products with prominent homogeneity problems will not be pushed by the Wish platform. When this happens, you can find the manufacturer for further processing, or use it as a set Product portfolio sales.
• Enterprise: Sellers who operate as an enterprise will receive more resource support from the Wish platform, so qualified sellers can choose to register in the name of a company.
• Product Features: Wish will provide more exposure for products that have certain characteristics and are in line with market trends, such as drones and twist cars that were very popular on the Wish platform in 2015. (a balancing car) etc.

3. Data collection and organization

• Data sources: Data acquisition sources include other cross-border e-commerce platforms, search data, bidding data and other information provided by search engines, third-party websites such as Haiying Data, Miku, etc.
• Data Cleaning: Clean and preprocess the collected data, including removing missing values, processing outliers, standardizing data formats, etc.
• Define indicators: Determine the indicators or sets of indicators you want to analyze, which may involve sales growth rate, product quality score, market share, etc.
• Data analysis: Use appropriate data analysis methods and tools to conduct exploratory analysis and statistical analysis of data, which can include data visualization, trend analysis, comparative analysis, etc.

4. Conclusion

Through in-depth analysis of Wish seller data, sellers can better understand market trends and discover new opportunities; at the same time, by analyzing competitor and product data, they can continuously optimize their operations and base their operations on market trends. Find new opportunities. Through the above measures, sellers can significantly increase the exposure of their products on the Wish platform, thereby promoting sales growth.