The indicators can be sufficiently explanatory only when the quantity of goods reaches a certain amount. You can clearly calculate where your shop is not doing well through these indicators. You can also use some free tools, such as "free gift upon reaching a certain amount" or "discount for matching purchase", to make buyers want to buy more items. These four indicators are based on the number of goods: main image, title, and price. After these are improved, buyers will click. At this point, we find that many people look but leave after viewing without making a purchase. Why? Everyone should follow the order I mentioned. If the order is messed up, it won't explain the problem. Of course, some categories require a higher number of products. You need to first check your IPV_uv. Relying solely on the description of a single product to make buyers purchase one item is not enough. We hope buyers will buy more. IPV: The PV (page views) of the product detail page, also known as Detail PV, for Taobao online stores, the page URL contains the keyword "item-detail". Therefore, what you think looks good, others may not agree, at this moment, data is the most explanatory. When buyers enter the store, it generates store UV. So whether this is done well or not, for online stores, you need to divide your store UV by IPV_UV. From this data, you can see if the following aspects in your single product description are properly handled. The reference value of this ratio is 0.6. First, our number of products should not be less than 100. IPV UV: Visitors who have browsed the product details page (unique visitors). Divide your ipv_uv by your number of products. This is the key to the conversion rate of a single product! This is based on the average value of comprehensive categories, definitely not much. So everyone must not feel tired or hard from writing too much; success or failure depends on these.
PV: Page Views, which is the number of page views, can be added or subtracted cumulatively. Each product in our store is an entry point to our store. Today's topic is about the relationship between various data in the store and the issues behind each data point. It might look beautiful in your eyes, but among the hundreds of millions of buyers on Taobao, how many people have exactly the same taste as you? That's all for today. The value of data is infinite, and one day you will understand. If I don't tell you now, you'll regret it later. pv, uv, ipv, ipv_uv. If this ratio is less than 1, it means your main image, title, and price are not well done, and buyers won't click. At this point, what you need to improve is the main image, title, and price. After successfully guiding buyers into the store, can we know if they basically like the store decoration? If they like the decoration, they will naturally look at our products and buy more.
These reference values are extracted by our very experienced Taobao data analysts from merchants with daily sales of 2000 yuan. If you reach these data points, your store is successful. It's the issue of product description! Therefore, based on having more than 100 products, I mentioned earlier that each product is an entry point to the store, so we need to guide buyers from individual products into the store. UV: Unique Visitors, i.e., visitors (unique visitors), cannot be added or subtracted. How to describe will be explained in future courses, and today I'm teaching you data analysis. Everyone always asks, "I've already listed my products, and the decoration looks good, why is there no traffic?" At this point, you need to divide your PV by store UV. For online stores, if this data is greater than 2, it means each person entering your store clicks at least twice (excluding product paging). If you achieve this data, it means your decoration is great. If you don't understand these data meanings and the issues they indicate while running a Taobao store, you will soon be eliminated.
First, do you all understand the main indicators of Taobao? In the single product description, you need to add some related product information to let buyers see other products in your store and stimulate their desire to buy. Why calculate this way? When you, as a buyer, want to buy something, and a large number of search results come out, which product will you click? Isn't it the product with an attractive main image, a good title, and a reasonable price? Right?