抖音搜索場(chǎng)景化的展示有哪些？

想要做好抖音搜索，我們首先要知道，用戶為什么會(huì)進(jìn)行搜索呢？一般會(huì)有以下幾種情況：

To do a good job of Tiktok search, we must first know why users search? There are generally several situations:

用戶自身產(chǎn)生需求，主動(dòng)進(jìn)行搜索

Users generate their own needs and actively conduct searches

視頻上方的搜索欄里面主動(dòng)彈出的內(nèi)容，用戶感興趣進(jìn)行搜索

The active pop-up content in the search bar above the video, which users are interested in searching for

評(píng)論區(qū)頂部的“大家都在搜”

"Everyone is searching" at the top of the comment section

評(píng)論區(qū)中的一些評(píng)論的關(guān)鍵詞可以點(diǎn)擊跳轉(zhuǎn)

Some keywords in the comments section can be clicked to jump to

所以其實(shí)抖音搜索的很大一部分流量，是基于這個(gè)視頻本身所聯(lián)想出來或者引發(fā)的周圍相關(guān)的東西，或者是平臺(tái)去引導(dǎo)用戶做的搜索，而用戶自身產(chǎn)生需求進(jìn)行搜索的流量占比其實(shí)很少。

So in fact, a large part of the traffic of Tiktok search is based on the relevant things around the video itself, or the platform to guide users to do the search, while the traffic of users' own demand for search accounts for very little.

不過系統(tǒng)引導(dǎo)用戶去進(jìn)行搜索，對(duì)于我們的賬號(hào)來說，就又變成了推薦流量。

However, when the system guides users to search, it becomes recommended traffic for our account.

了解用戶的搜索場(chǎng)景后，我們?cè)賮眍A(yù)測(cè)一下，用戶可能會(huì)搜哪些內(nèi)容?

After understanding the user's search scenario, let's predict what content the user may search for?




用戶搜索的內(nèi)容，有很大一部分，也和平臺(tái)的推薦有關(guān)：

A large portion of the content searched by users is also related to platform recommendations:

1、用戶自身的問題與需求

1. User's own problems and needs

2、上方搜索框里面的內(nèi)容

2. The content in the search box above

3、猜你想看有哪些關(guān)鍵詞

3. Guess what keywords you want to see

4、評(píng)論區(qū)可以直接跳轉(zhuǎn)的內(nèi)容

4. Content that can be directly redirected to the comment section

所以建議大家在平時(shí)要多刷一下同行，我們可以多看，多去了解一下搜索框、猜你想看以及評(píng)論區(qū)中出現(xiàn)最多的內(nèi)容是什么，就可以推斷并且預(yù)測(cè)用戶平時(shí)可能會(huì)搜索的內(nèi)容，我們可以針對(duì)用戶可能搜索的內(nèi)容去做內(nèi)容輸出，提高自己賬號(hào)或視頻在搜索結(jié)果中的排名。

So it is recommended that everyone should browse their peers more in their daily lives. We can read more and understand the search box, guess what you want to see, and what content appears most in the comment section, so as to infer and predict the content that users may search for in their daily lives. We can output content based on the content that users may search for, and improve the ranking of our account or video in search results.

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