(I) Lazada’s traffic composition
Lazada currently has two types of traffic: search traffic and promotional traffic, both of which are free traffic.
(II) Lazada search traffic entrance
1. Category search
Category search is divided into category keyword search and category direct search.
In category keyword search, consumer behavior and seller action are as follows:
(1) Consumer behavior: Consumers search by entering keywords in the search bar (web version or mobile app); when there is no clear shopping intention, most consumers will only enter short keywords (for example, Earphone, Shoes).
(2) Seller action: For example, in the “Headphones & Headphone Accessories” category, the visibility of products is higher than in the “In-ear Headphones” category. Therefore, sellers need to consider: Have you selected the most accurate underlying category? Do you have products that can be uploaded to categories with higher exposure?
In direct category search, consumer behavior and seller actions are as follows:
(1) Consumer behavior: Consumers search through the category column.
(2) Seller action: Sellers must select the correct bottom-level category to create SKUs, otherwise the exposure rate is basically zero. To select an accurate category, you can search according to the category tree file.
2. Keyword search
Most consumers tend to search for specific preferences, so that the search results page will display more accurate search results. For example, when searching for earphone products, if you just search for “earphone”, there will be 98,706 search results; if you specifically search for “in-ear earphone white bluetooth for Samsung”, there will be 11,229 search results; so the product is displayed in a more accurate search results page, and the product traffic may increase by nearly 9 times.
Therefore, when sellers fill in product keywords, they need to focus on the key attributes of the product and high-frequency search keywords, which can bring a higher ranking for the product. If you just stack synonyms and illogical titles, the conversion rate will be very low.
3. Attribute Filtering
When buyers enter the web platform, they are likely to only browse the first few pages. In order to more quickly select the products they are interested in, they usually filter by attributes. For example, there are 25,312 search results before filtering. At this time, in order to find the products they want to buy more quickly, after 4 filters, the number of search results has been reduced from 25,312 to 246! Due to the different screen sizes of the PC and mobile versions, the selection results will also be different.
Therefore, when sellers fill in product attributes, they must fill in the correct attribute values in the required attributes and optional attributes columns.