Many sellers lack ideas when selecting products. They either think they are familiar with a certain type of product and sell it directly, or they start to select products for themselves from the products listed in a certain seller’s successful case, or they feel that a certain product should be easy to sell, so they start selling it. These product selection methods lack rational goals and thinking, and the final result can be imagined. The selection of products in a store cannot be decided by slapping your head, but you must have ideas and principles, so that you can be targeted.
Product selection requires clear ideas, starting from the six steps of extensive, professional, selected, persistent, repeated and data analysis, rationally and logically select the products that suit you.
1. Extensive
For cross-border e-commerce sellers, having a wide range and multi-category thinking is the first step in product selection, rather than limiting your vision to a certain category. This requires sellers to expand their thinking in the initial product selection and widely explore multiple categories of products, so that they can choose the most suitable categories and products from many categories as their future development direction.
2. Professional
Through comparative analysis of multiple categories, sellers have found categories that they are interested in, have sources of goods, and have good sales and profits. At this time, sellers need to work towards professionalism. As a seller, if you simply understand the goods you sell without professional and comprehensive knowledge, it is difficult to make a difference. Therefore, in order to outperform competitors in the current nearly transparent market state, you should first surpass your competitors in professional knowledge of the goods.
3. Selection
With the accumulation of professional knowledge of the categories you operate, sellers have a deeper understanding of the goods. On this basis, sellers should be selective and repeatedly screen in product selection. In the business world, 20% of the goods always bring 80% of the profits. Sellers need to try their best to dig out the 20% of goods that can bring high profits.
4. Persistence
Product selection is a long-term process that runs through the operation of the store. Therefore, in the process of product selection, sellers should not have the idea of once and for all. The success of product selection today does not mean that this product will also bring large sales tomorrow. Sellers should insist on doing some product selection activities regularly, so that they can develop potential trend models while having hot-selling “explosive models” to prepare for tomorrow.
5. Repetition
The process of persistence is a repetitive process in other words. In the process of repetition, many people will gradually get bored and lose their passion and fighting spirit. This is why some sellers often become sales stars by detonating the market with a certain product, but then quickly become silent and eventually disappear.
In order to maintain long-term stability of operations, sellers must always maintain their enthusiasm for work. Product selection is a boring process, but if sellers persist for a long time and repeatedly select products, they will definitely make new discoveries.
6. Data analysis
In the early stage of product selection, sellers may rely largely on intuitive feelings or relatively basic analysis. When the store’s specifications develop to a certain stage, sellers have also accumulated certain experience, have a certain degree of professionalism, and have sufficient knowledge of the industry. In this case, sellers may have a certain understanding of all products. At this time, in the selection of products, sellers will be affected by their own cognition and prejudice. In order to avoid missing out on good products due to cognition and bias, sellers need to combine big data analysis as much as possible to assist in product selection, and use big data analysis tools to collect relevant sales data in multiple dimensions. Compared with personal cognition, big data can reflect more objective content, and sellers can dig out some information and products that they have not been aware of before.