In fact, it is not difficult to convert on Xiaohongshu. It is divided into three steps: 1. You need to know who your main transaction group isMany brands think they know it, but it is just assumption and has not been verified. Therefore, if you can find experienced purchasing groups, you can target conversions based on the portraits. So how can we find the main transaction group? The answer lies in focusing, which is like an amplifier for the crowd, helping us to accurately portray the portrait of the crowd that makes the transaction. When creating a new advertising plan, we can give priority to "promoting products" to clarify the target audience. Some business friends may ask, why not run the click-through rate of the notes first? Wouldn't this increase the exposure of the notes? But people often overlook: for conversion, the transaction behavior is more important than the seeding behavior. What does it mean? That is to say, there may be many users who are interested in our products, but the people who can actually make transactions are the customers who bring benefits to the brand. We can publish a large number of sales notes through appropriate topics. One week after the release, we can select notes with good natural traffic and high conversion rate, because good natural traffic means that the quality of the notes is higher and the users reached are more accurate. Then we can use the spotlight to reheat the traffic of these notes and continue to attract the target audience. After our advertisements are launched, the spotlight will automatically generate data rankings for these notes in the industry. The notes with high conversion rates indicate that these notes have touched the portraits of people who can really make transactions. This can also help the account quickly pass the early cold start period and accumulate the initial population model. On the second day after the launch is completed, we can intuitively understand our basic portrait, consumption preferences and content preferences by looking at the portrait of the target population. After testing in different directions, the brand can directly obtain accurate population portrait positioning to adjust the content direction and delivery strategy. After obtaining the target population portrait, we can also focus on creating new targeted populations to select industry labels, user attributes, private domain data, etc. to help brands segment population labels. 2. You need to have good contentThe most important thing about advertising is content. A good content communication point can quickly narrow the distance between the brand and the user, but the communication point is not equal to the product selling point. If we want to obtain the communication point that accurately reaches the user, we can also obtain it through focusing. First of all, we need to design possible communication points with users based on product features and user characteristics, such as product functions, user reviews, usage experience, etc. Usually in a specific scenario, the pain points generated by users will become the communication points with the product, so we need to pay more attention to the scenarios in which the product is combined. For example, my product is an acid-brushing product, and its selling points are "oil-soluble - controls skin oil", "strong permeability - can soften keratin", "promotes cell metabolism - improves blackheads", etc. Then we combine salicylic acid with skin care scenarios to extract keywords, and we can get usage scenarios such as "acne removal", "fighting blackheads", "shrinking pores", "natural enemy of oily skin, soothing sensitive skin", etc., to further subdivide and find communication points that are easy to attract users. I don't know if you have discovered that the user's communication point = the solution point and solution in the usage scenario. Focusing on the usage scenario and combining the product characteristics, it is easy to find the user's communication point. To obtain such high-frequency scene words, we can use the built-in keyword planning tool of Juguang, and use tools such as intelligent word recommendation, industry word recommendation, and word recommendation to help us intelligently derive high-frequency scene words. Observing the keyword delivery data - display volume, click volume, click-through rate, etc., can help us intuitively obtain the scene keywords that users are more interested in. The keywords that users are more interested in may be their demand scenarios. 3. Test volumeHowever, with so many selling points, we cannot launch all of them point-to-point on a large scale. The cost is too high and the cycle will be very long. So what we need to do is to combine the selling points by combining the brand's selling points with user demand scenarios to conduct delivery tests on communication points and content selection. For example, we can prepare seed notes of different directions for the same type of products and place them through Juguang. And because Juguang now supports the one-click test of horse racing notes, we only need to check multiple notes under the "Business Content Management" section of Juguang, and build promotion plans in batches with one click. Through the combination of different functional keywords + scene words of different categories; different cover titles and materials; different note types, we can test a content of our communication point selection topic. . After the launch is completed, the standards of the overall market will be used as a reference, and the "key indicators" of the notes will be subdivided into secondary categories according to the industry. The note data of the past 7 days under the same category will be counted in the form of the percentage of the notes in the top of the industry and arranged in descending order. This will show the ranking of our high-quality notes in the same industry. Brands can directly view the test effect of the note launch through the industry data ranking of each note. In addition to using Spotlight to test note content, brands that have opened stores can also use the notes with yellow car links, red stars, and other methods to calculate and obtain more intuitive transaction conversion rate data after obtaining the reading exposure data of Spotlight notes. In summary, we can derive a formula: Main transaction group × correct communication points × tested and verified high-volume content = brand-effect integration If you figure out these three things, it is not difficult to make conversions on Xiaohongshu. Author: Vic's Marketing Thoughts Source: WeChat public account "Vic's Marketing Thinking (ID: Viccps0227)" |
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