Guangda's big data cross-border product selection solution covers multiple global e-commerce platforms such as Amazon, Shopify and AliExpress. It provides a comprehensive cross-border e-commerce product selection strategy from multi-dimensional data such as competitor data monitoring, hot-selling category selection and advertising material analysis to help you connect with the world! English SocialPeta Nature Product Selection Tool Basic IntroductionGuangda provides you with massive data from 73 channels and powerful search methods to enable you to play with advertising creativity, market, cost, APP, audience, e-commerce and brand analysis, which can help you develop your business in all aspects. Function Introduction1. Advertising creativity A massive library of creative materials to meet the creative needs of all types of users 2. Advertising Intelligence Detailed advertising intelligence analysis, daily data volume changes, and more than one year of data trend coverage 3. Apply Intelligence App Store and Google Play Store charts are updated daily, supporting 38 countries and 20 sub-categories of app categories 4. E-commerce Intelligence AliExpress, Shopify and Amazon product selection analysis to help you discover hot-selling products 5. Brand Intelligence Analyze the brand's influence on social media from the perspectives of fans, interactions, etc. 6. Advertising Cost Intelligence Analyze global advertising costs and trends, identify market gaps and opportunities, and continuously update your marketing strategy Product Advantages1. Product selection database It contains nearly 30 million Amazon listing data, nearly 30,000 niche data, and over 900 million advertising creative data covering 46 countries and regions. Most product selection tools on the market select products based on keywords, competitor monitoring, and e-commerce platform data. Guangda's hot-selling product selection tool is upgraded on this basis, combining the advantages of the platform's over 900 million advertising material data, and using advertising data to select products in multiple dimensions. After choosing Guangda, the success rate of hot-selling selection increased by 85%, and advertising traffic optimization increased by 130%, saving sellers 80% of operating time! 2. Advertising data selection Using over 900 million advertising creative data, we can derive a list of creatives in different categories, discover the hottest products on the market, or directly search for advertising data on competitor websites. Based on the frequency of advertising, display volume, and popularity of creatives, we can search for related ads by product name and check the advertising display effect to confirm the hottest products. 3. Amazon platform competitive product monitoring and product selection All categories available for sale by third-party sellers on Amazon, with full data as a sample. Through a powerful product monitoring system, we have obtained most of the active products in all categories available for sale by Amazon third-party sellers. By integrating and analyzing these products, we have obtained an active map of the entire Amazon market. You can use nearly twenty different dimensions of screening conditions to define the path you want to achieve, helping you find the market segment that can help you increase your profits more quickly! At the same time, you can also easily customize the sample space and freely view the head, waist or overall market data of the sub-categories, helping you make more accurate decisions! 4. Diverse market analysis dimensions Through precise data capture capabilities, we can show you more secrets of subdivided categories and accurately locate all the paths and basic information of the category for you. 5. Activity monitoring By monitoring the changes in reviews of all products in a category over a long period of time, we can clearly understand the activity of the category and whether there are frequent order-padding incidents in the category. By analyzing the daily growth of category reviews and the proportion of the total number of reviews in the category, we can easily determine the market saturation of the category! 6. Price monitoring By comparing the monthly increase in reviews and prices, we can better provide a reference for our pricing strategy and try to set product prices within a range with higher review growth: 7. Analysis of the time of listing By analyzing the distribution of different listing times, we can more clearly view the recent situation of other friendly competitors in the category. If there is a sudden and severe drop in the number of listed products, it means that the activity of the category has been poor recently, and it is not suitable to select products in this category. 8. Category Health Analysis By analyzing the distribution of all product ratings and reviews in the category, we can clearly understand the health of the category. If there are more products with low ratings, it means that the health of the category is poor. If there are more products with fewer reviews, it also reflects that the health of the category is poor, but it also reflects that there are more opportunities for sellers. References |
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