How to improve app keyword coverage? Get acquainted with the routines first!

First or the introduction of the application of keywords to optimize the selection of the general flow of words, the general idea is to first "coarse select", after the "fine selection", gradually narrow the scope of the selection of words.

The first step is to first determine the "effective keywords", mainly for the basic heat filter. Because 4605 of the heat of the word, the average day of the search, the choice of words, the general election is greater than or equal to 4605 of the words, as for other low-heat words, most of them are keywords covered by long-tail search words, do not deliberately consider. There are about 46,000 words in AppStore greater than 4605 (note: After mid-July, the number of words dropped to less than 30,000), which equals 4605 of about 60,000, commonly referred to as "valid keywords".

Coarse selection

Based mainly on the relevance of words, 100 to 200 words are extracted from "valid keywords". Rough selection process is generally referred to as "extension words", commonly used methods have the following several, to obtain the relevance of keywords decreased in turn, but the expansion in order to improve:

1. Extraction in the introduction. is to analyze the keywords in the introduction of the app, find the Heat >=4605 words, generally need to introduce the word segmentation, and then extract the higher heat words.

2. Category words. is to look at a category under, such as "weather" under the keyword, a keyword category, is determined by its search hit the first app main category. If your app is very high-level, then just choose the hottest word in the category. There are some machine brush apps that also choose the categories of popular words and then brush them again.

3. Competitive selection of words. This is a relatively good understanding, is to look at the use of competing products which keywords.

4. With CI words. Familiar with the Baidu advertising platform of the child boots may have used a similar tool. This kind of choice method, generally is to fill in a batch of seed words, and then expand through different methods. There are 3 types of common extension methods:

A. The words used by the relevant app. This method is the most commonly recommended method, similar to buying a book on Amazon, will recommend to you, "buy this product customers, also bought * * *". The words used by the app are similar, that is, "the app uses these seed words, and also uses the keyword * * *".

B. Include words. It is the word that contains the seed word, such as the seed word fills in "the rook", in this way can expand the "every day rook" and so on.

C. Related words. Typical as synonyms, such as "moving" synonyms "housewarming". There are some more generalized, such as "beauty" can be extended out of "handsome", "Chinese" can expand the "mathematics", these words have a certain correlation relationship. Like Apple search ads, this "related word" extension is specifically introduced, such as "Photo Filters" to expand the words "picture editor" and "Light right".

Fine Selection

When the app starts, there is no online information, so the main goal of the choice of words should be to test the app's choice of word positioning, if it is unpopular app, it is best to choose some low-heat words, but if you are recommended, then the heap of hot words good. But before the line, these are unknown, so it is best to try as many, different heat words, in order to achieve the purpose of "ofspecialty".

Because only 100 characters, roughly 30 words, so the best strategy is based on the heat distribution of keywords, inter-partition selection of words, such as the heat is more than 5000 of the words only about 3000, and between 4605 and 5000 there are about 43,000 words. Therefore, when choosing a word, more than 5000 can choose 10 words to test, and 5000 or less, you can choose more, choose the number of words as far as possible with the heat distribution, so that it is easier to find the choice of word positioning.

According to the heat distribution of the choice of words, can be briefly described as "division of Choice", we appbk do the first choice of words, the general use of the following zoning strategy, for reference only:

When selecting a specific word, follow these steps:

1. From the high heat interval to the low heat interval (G5 to G0), select the words in turn, the number of characters per interval should be greater than or equal to the preset number of characters, subsequent can be uniformly truncated.

2. The selection of words in each heat interval, mainly by competition, from low to high, and then select from the candidate words, until more than the preset number of characters. If there are not enough words to choose from within the interval, select all the candidates. The degree of competition we appbk is mainly based on the number of app reviews.

3. After selecting the 130-character words, adjust the ratio of "competing words" and "industry words" according to the characteristics of the products. If we do not make adjustments, the proportion of "competing words" and "industry words" in the choice of words should be roughly 15%:75%, that is, the proportion of the market, which can generally be appropriately increased by the proportion of "industry words".

4. According to the terms of the group, appropriate deletion, to ensure 100 characters.

Choosing high-quality keywords for apps is the first step in the ASO keyword optimization, welcome to ASOTOP1 official Website "No.: ASOtop1", together to learn more about ASO optimization knowledge, to bring more natural download for the app!

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How to improve app keyword coverage? Get acquainted with the routines first!