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At the end of February, the algorithm of App Store underwent a major change: many products did not optimize rankings or updated versions, etc, but the keyword data fluctuated significantly (increased or decreased). I believe that many operators had perceived it.



This phenomenon occurred on February 22. Through data analysis and comparison, we can find that its fluctuation range was very wide, the coverage and ranking data of a large number of keywords in the App Store in China were affected to varying degrees.



Qimai Research Institute once compared more than 31,000 apps in all categories on February 22, and found that the change rate of keyword coverage accounted for more than 82.41% compared with February 21. Among them, the proportion of keyword coverage increased by 60.82%, and the decrease rate was 21.59%.







(2) The number of keywords of Main Page View and Acquisition Range of PV (Top10 keywords and Top3 keywords), also increased significantly, among which, the number of Top10 keywords increased by 7701, accounting for 22.60%, and the number of reduced apps was 8389, accounting for 24.62%. The number of Top3 keywords increased to 6066, accounting for 17.80%. And the number of apps decreased to 5,154, accounting for 15.12%.



Presently, the phenomenon has not recovered significantly, and there are still signs of continuous adjustment. So far, what are the trends in this algorithm adjustment? What factors should we focus on? In the following passage, we will have a more detailed discussion.





1. The company’s developer account has become a major factor affecting the weight of the App



According to the comparison of the types of more than 31,000 apps and the changes in the number of keyword coverage mentioned above, it is found that: in this adjustment, the keyword coverage and ranking of apps under the company's developer account have increased more. Compared to individual developer accounts, keyword coverage and rankings are more negatively affected. In the algorithm change, the company's developer account has become a major factor affecting the weight of the App, and indirectly affects the ranking optimization.



The sample apps were divided into company’s developer accounts and individual developer accounts (Among more than 34,000 samples,16,266company’s developer accounts, accounting for 47.73%. There were 17811 individual developer accounts, accounting for 52.27%）， After distinguishing, they were compared and analyzed from the three dimensions of "all keywords", "Top10 keywords" and "Top3 keywords".



(1) From the perspective of the total number of keywords: As shown in the figure below, compared with February 21, the number of apps under the individual developer account is significantly higher than the number of apps under the company's developer account in the total keyword coverage reduction range. And the proportion of apps under the individual developer account is larger than the total keyword coverage reduction of more than 11.







(2) From the total number of Top3 and Top10 keywords: If you feel that the comparison above is not obvious, you can look at the detailed chart of the change in the total number of Top3 and Top10 keywords below. In the reduction range (-1 or less), the number of apps under the personal account and the number of apps under the company account are very different.



A. From the total number of Top3 keywords:



Among the apps with a keyword increase greater than 11, the number of apps under the company's developer account is higher than the number of apps under the individual developer account. Besides, the number of keyword increases is less than 0, that is, among the apps with a keyword reduction range of 1~100, the apps under the individual developer accounts are relatively large. As shown in the following figure.









2. The number of downloads still accounts for an important proportion of the algorithm



In addition, we also analyzed the data of sample apps from the dimensions of "entering the overall list" and "not in the overall list but entering the classification list", and found that the ranking of the app list is a factor that cannot be ignored in this adjustment by calculating the proportion of the two types of apps in different growth ranges.



For example, in several intervals where the total coverage changes, the proportion of App keyword coverage that only enters the classification list decreases, remains unchanged, and increases slightly （1~10）. The total keyword coverage of the total number of apps in the overall list increased by more than 10, and the proportion of apps gradually increased.







What’s more, the overall list also had a better positive impact than the category list in several intervals where the coverage of the Top 10/Top 3 keywords changed.







As we all know, downloads, comments, DAU, retention, etc. are important factors affecting the ranking of the App list, and the number of downloads is the main factor. The apps that rank better on this list have a greater positive impact, which actually proves that App downloads, or naturally new products, have been positively affected in this algorithm adjustment, and downloads account for an important proportion of this algorithm adjustment.





3. The weight of comment optimization has increased



In the process of data statistics and analysis, it was found that many apps in the same dimension in this adjustment had better reviews of products with better optimization, and the number of keywords and rankings increased more obviously.



Here's an obvious example, you can take a look at the change in the number of reviews and keyword coverage of this product.







Maintaining a stable periodically do some praise optimization of the product by real users, which is more conducive to increasing the weight of the product, and when encountering an algorithm adjustment similar to this algorithm, the probability of positive impact on the product will be greater, and the probability of negative impact will be smaller.





4. The investigation time of Apple Store on magnitude (CPSA) has become longer, and the delivery effect has been delayed



Recently, there has been a delay in keyword ranking optimization, and the rate of results within 12 hours has decreased. Many app optimizations appear on the second or third day after launch, and some have longer delay time!



We conduct statistics and analysis according to the extracted samples, and after keyword ranking optimization, the effect is concentrated in 20~28 hours.







The delay of keyword ranking optimization effect is likely to be growth of inspected time for search downloads. Facing such a situation, it is recommended to optimize a keyword ranking, the observation time is best delayed by 1～2 days, and then adjust the next optimization strategy according to the actual situation.

For example:



(1) In the early stage of ASO optimization of products, it is recommended to test multiple keywords in small quantities every day, shorten the keyword placement test cycle, extend the observation time after keyword optimization, and extend the test time for key keywords to 2-3 days;



(2) After the keyword ranking has been significantly improved, the next stage of optimization will be carried out to improve the keyword ranking to the target ranking;



(3) Keywords with no obvious ranking improvement are temporarily abandoned, or tested at intervals.



Finally, there is the solution for Clause 4.3



Basics:



1. Apple Store's audit, divided into machine audit and manual review. Most of the apps with this problem are rejected in the stage of machine audit.

2. Apple Store will manage the weight of developer accounts: the lower the weight, the stricter the audit. The same vest package may be passed on accounts with high weight, on the contrary, may be rejected on accounts with low weight.



Tips to circumvent the problem of Clause 4.3:



Cut off all similarity between the current vest bag and the previous vest bag;



Similarity associations include: 1. IPA package features; 2. Developer Account; 3. Computer; 4. Upload IP; 5. Similar materials



Itemized details: 1. IPA package features: Include code similarity and resource similarity;



Workaround of code similarity: a. Confusion of existing code (class name, function name) b. Add some useless code;

Workaround of resource similarity: a. Renaming of resources; b. Add some useless resources as appropriate;



2. Developer Account: Information that two vest packs should not be linked to the same developer account.



3. Computer: If conditional, it is best to upload



with different MACs (it is best to upload vest bag no more than 5 vest bags on each MAC)



4. Upload IP: When uploading a vest bag, the IP address should not be the same as that of other vest bags



5. Similar materials: ITU background materials such as promotional images, ICON, copyright owners do not be same



[Note: Even if the vest package has not been audited before, do not associate with them, especially the vest bags that were rejected in the front with the problem of the Clause 4.3.]