How can a wireless side bring more traffic

　　Now the proportion of wireless transactions has reached 90% or even higher, and the wireless side has brought more accurate traffic. Because the mobile phone is more "private", it can effectively record personal consumption browsing and other behaviors, providing greater possibilities for system algorithms to mark people and recommend content targetedly.

　　1. The background of thousands of people and thousands of people in public domain traffic

　　Taobao universal formula: transaction amount = number of visitors * conversion rate * unit price. Now everyone knows that it is becoming increasingly difficult to obtain traffic. In this context, we need to find ways to improve the conversion rate, and the same is true for Taobao platform. A unique face to face and personalization is actually to recommend the products that consumers are most likely to trade to consumers. The advantage of doing this is that it can make full use of every traffic and improve traffic efficiency to the limit.

　　2. The main channels and methods for affecting public domain traffic from thousands of people and thousands of people

　　First, let’s sort out the common channels that are currently affected by thousands of people, mainly the system recommends thousands of people: Taobao homepage (you may like, must buy a list, and there are good products); search for thousands of people (the comprehensive sort will be affected by the factors of thousands of people); the venue will have thousands of people (in most cases, the floor arrangement will have thousands of people), so the impact of thousands of people on our overall store traffic is becoming more and more obvious.

　　3. How to recommend logic and targeted strategies and methods for improving traffic in thousands of people

　　1. First of all, you need to know what is the personalized recommendation logic of Taobao's thousands of people and thousands of faces.

　　The fundamental logic of Taobao’s recommendations for thousands of people is correlation, that is, the strength of the relationship between the visitor group and the store and the strength of the relationship with the baby. Personalized recommendations are made based on the strength relationship between the visitors and the store. The specific correlation can be understood from the following aspects.

　　Relevance 1: People who have had marketing relationships (personalized relationships)

　　For people who have had marketing relationships with stores or products, such as stores and products that have purchased, purchased, purchased, and collected, Taobao will default to being a strongly relevant group, especially some categories with a relatively high repurchase rate, which will be given priority to you in the Thousand People and Thousand People channels, such as if you like, search priority sorting, and venues with Thousand People and Thousand People. What is particularly obvious here is the recommendation from the search side. The personalized relationship is very obvious. There were signs such as shops that have been purchased, collected shops, etc. before. Now this sign has been cancelled, but the logic has not changed.

　　Relevance 2: Recommend similar products and stores based on your marketing relationship path

　　Sometimes we will find that after searching for something, browsing something, and collecting and purchasing something, you will see similar categories on the homepage of Taobao to display it. This is Taobao recording your browsing traces and recommending targeted recommendations, and recommending high-quality babies in the same category to you.

　　Relevance 3: Targeted recommendations based on consumer visitor portraits

　　After a period of time, each visitor will form a crowd portrait, such as 90 mothers, middle-income, Virgo, travel-loving, etc.... The Taobao system will analyze your crowd label portraits, and then analyze the tag portraits of these stores and crowds on Taobao. Which store labels meet these characteristics, and then recommend the most matching store products to similar consumers first. If the portrait of the store crowd is accurate enough, the conversion of recommended visitors will be relatively high. Otherwise, the matching crowd will not be accurate enough, and the conversion brought by thousands of people will be relatively low.

　　Correlation 4: Make correlation judgment and match based on high probability

　　As mentioned earlier, each of our visitors will form their own label portrait after a period of browsing, purchasing, collecting, purchasing, etc., but if they are a newly registered user, the group label portrait is relatively empty. What should we do at this time? Because in addition to having some basic crowd attributes, this buyer is vacant in terms of shopping behavior and shopping preferences, and at this time, the search engine will match according to the probability. The system will recommend products with a well-known possibility of purchasing products from similar products based on your search intention.

　　2. How to use the recommendation logic of thousands of people and thousands of people to improve the system's recommended traffic

　　After understanding the basic logic of recommendations from thousands of people through the above analysis, let’s discuss how to use rules to increase traffic. In fact, the key to the problem is how to strengthen the store’s personalized labels and product personalized labels, and then let the search engines determine that your product is matched with consumers. Next, let me share with you how to quickly strengthen store labels and product labels.

　　(1) New store attributes, categories, and keywords to strengthen store labels.

　　There are no consumers who browse new products and new stores, so at this time your store label mainly depends on your category, attribute, and keyword. You must not fill in the attributes incorrectly or miss the attributes, and you cannot put categories incorrectly. You must choose the most accurate keywords for the keywords. For example, in terms of attributes, keywords, and categories, you are 18-25 denim clothes, slim-fit trends, men, etc., then your store will be labeled as 18-25 denim clothes, slim-fits, etc. (because you will focus on browsing in the future). Consumers who meet these labels will be given priority to match your store. Another thing is the writing of the title. If your title contains attribute words such as denim clothes, slim-fitting trends, it is easier to be labeled with stronger attributes of such tags.

　　(2) Strengthen labels through consumer behavior

　　The main tags of stores and products are of course from consumers' behavior. The logic is as follows: consumers have clear population characteristics (such as age, gender, income, preferences, etc.) - and then consumers leave traces in your store (browse, collect, purchase, etc.) - and then the tags on the consumer will be left in your store as a statistical basis - when the data is sufficient, the probability of counting your store tags. Your crowd characteristics can be seen from the path of "Business Consultant-Market Quotes-Crowd Portraits-Buyer Crowd Portraits". The order of label weights for consumer behavior reinforcement is: purchase, purchase, collection, consultation, and browsing. In addition, you should also pay attention to this phenomenon:

　　- Buyers with high credit ratings bring higher personalized label weight than buyers with lower credit ratings;

　　- Buyers with clear labels (always prefer a certain type of product) have higher label weight than buyers with unclear labels;

　　- Blacklisted buyer numbers cannot bring label weight.

　　(3) Old customers purchase reinforced labels

　　The weighting effect of old customers is the most obvious, especially an old customer with very clear labels. We can influence and promote repurchase through old customers to achieve the strengthening effect of old customers’ labels on store labels and product labels.

　　(4) The direct train is accurate to strengthen the store labels

　　The direct train accurately plans to mark the store quickly. Almost all categories can use this method, only precise keywords are opened and not broad matches are made. As long as your product is not a problem, this direct train development can weight your personalized recommendations and bring accurate traffic at the beginning.

Thank you for your attention and support to Laogao Crown Club . Please indicate the source of the reprinting website www.shxuanming.net

 Click to register to apply to join the well-known e-commerce network - Laogao Crown Club. Any merchants from all over the country, Tmall merchants, Taobao Crown Stores, Jinguan Stores, and other e-commerce platform merchants can apply to join!