Explanation of Data Update Frequency

This section explains the data update policy of the FoxData API (external specifications) to help callers properly configure caching, refresh cycles, and fault-tolerance logic.

1. Basic Principles of Update Frequency (External Specifications)

Data update frequency is influenced by the following factors:

Module Differences: Different functional modules have varying data sources and calculation methods, resulting in differences in update frequency.

Regional Differences: Data volume and source coverage vary across different countries/regions, which may lead to different update frequencies.

Data Activity: When an application exhibits higher traceable signals in a specific market (e.g., chart visibility, active comments, search activity), related data is typically updated more promptly; conversely, the refresh frequency may be reduced.

2. Update Frequency List (by Module)

The table below describes “typical” scenarios. Actual frequencies may vary due to region coverage, API parameters (time range/pagination), data source fluctuations, etc.

Module/Capability	Example Data Scope	Update Frequency (Typical)	Notes
App Basic Information	Title/Icon/Description/Category, etc.	Low frequency (hourly to daily)	Metadata changes infrequently; suitable for caching
App Extended Information	Developer/Price/In-App Purchases/Size/Language, etc.	Low frequency (hourly to daily)	May be more frequent when prices or in-app purchases change
Charts and Rankings	Real-time charts/historical charts/ranking sequences	Medium-to-high frequency (minutes to hours)	Typically more timely for mainstream markets and trending apps
Rating Trends	Average rating/star distribution trends	Medium frequency (hours to days)	Related to review volume and activity
Review Details	Review List/Developer Replies	Medium-to-High Frequency (Minute-to-Hourly)	May be affected by pagination and task processing
Keyword-Related	Rankings/Indexes/Result Counts/Opportunities, etc.	Medium Frequency (Hourly to Daily)	Affected by region and keyword popularity
Visibility/Trend-Related	Visibility Scores/Trend Sequences	Medium Frequency (Hourly to Daily)	Metrics-based data is typically not real-time
Download/Revenue Estimates	Estimated Downloads/Estimated Revenue	Low-frequency (primarily daily)	Estimation models/statistical metrics; update frequency is relatively lower
ASA/Advertising-related (Task-based)	Monitoring tasks and results	Task-driven (generated per task)	“No data available/Task not completed” may occur; handle according to API documentation

3. Relationship Between “Region” and “Popularity” in External Documentation

To assist callers in understanding, the platform recommends managing data timeliness based on the following expectations:

Mainstream Markets (e.g., the U.S., China, the U.K., Japan, South Korea, and other countries/regions): Updates are typically more timely.

Non-mainstream Markets: Update frequency may be lower, and delays may be more pronounced.

Trending Applications: Updates are generally more timely within relevant modules.

Long-tail Applications: Update frequency may be lower.

Recommendation: If your business relies heavily on minute-level timeliness, please prioritize validation in mainstream markets and align expectations regarding timeliness and coverage with the support team before launch.

4. Explanation of Data Update Frequency

Explanation of Data Update Frequency#

1. Basic Principles of Update Frequency (External Specifications)#

2. Update Frequency List (by Module)#

3. Relationship Between “Region” and “Popularity” in External Documentation#

Explanation of Data Update Frequency

1. Basic Principles of Update Frequency (External Specifications)

2. Update Frequency List (by Module)

3. Relationship Between “Region” and “Popularity” in External Documentation