Jungle Scout — Historical Keyword Search Volume
This skill queries the historical exact search volume for Amazon keywords via the Jungle Scout data source, returning weekly search volume data points over a specified date range across 10 Amazon marketplaces.
Core Concepts
The Jungle Scout Historical Keyword Search Volume tool provides historical data on weekly exact-match search volume for keywords across Amazon marketplaces. Sellers can determine the following by querying search volume changes within a specified time range:
- Seasonal patterns: Which months are peak/off-peak seasons for the keyword
- Trend direction: Whether search volume is continuously rising, falling, or stable
- Fluctuation range: Judge the stability of market demand
- Holiday effect: Surge in search volume before and after major promotions/festivals
Data granularity: Each record represents a 7-day cycle, containing the estimated exact-match search volume for that week.
Data Fields
Output Fields
| Field | API Name | Description | Example |
|---|
| Cycle ID | id | Data cycle identifier (marketplace/keyword/date range) | us_sushi_20250105_20250111 |
| Cycle Start Date | estimateStartDate | Start of the 7-day statistical cycle | 2025-01-05 |
| Cycle End Date | estimateEndDate | End of the 7-day statistical cycle | 2025-01-11 |
| Exact Search Volume | estimatedExactSearchVolume | Exact-match search volume within the cycle (times/week) | 12500 |
| Resource Type | type | Fixed value | historical_keyword_search_volume |
| Token Cost | costToken | Number of tokens consumed for this call | 1 |
Supported Marketplaces
| Marketplace | marketplace Value | Description |
|---|
| United States | us | Amazon.com |
| United Kingdom | uk | Amazon.co.uk |
| Germany | de | Amazon.de |
| India | in | Amazon.in |
| Canada | ca | Amazon.ca |
| France | fr | Amazon.fr |
| Italy | it | Amazon.it |
| Spain | es | Amazon.es |
| Mexico | mx | Amazon.com.mx |
| Japan | jp | Amazon.co.jp |
The default marketplace is us. If users do not specify a marketplace, use us.
API Usage
This tool calls the LinkFox tool gateway API. See
for calling conventions, request parameters, and response structure. You can also execute
scripts/junglescout_keyword_history.py
directly to run queries.
How to Build Queries
All four parameters are
required:
,
,
,
.
Principles for Building API Calls
- Marketplace Mapping: When users say "US marketplace" → , "Japan marketplace" → , "Germany marketplace" → ; use by default if not specified
- Date Format: Must be , e.g.,
- Time Span: The maximum span from to is 366 days; split into multiple requests if exceeded
- Keyword: Pass the user-provided keyword as-is (preferably in lowercase English)
- Common Time Calculations:
- "Past 3 months" → set endDate to today, startDate to approximately 90 days ago
- "Whole last year" → to
- "Peak season" → Determine based on category, e.g., Q4 is to
Common Query Scenarios
1. View search trend of a keyword in the past six months
json
{
"marketplace": "us",
"keyword": "yoga mat",
"startDate": "2025-10-01",
"endDate": "2026-03-31"
}
2. Determine keyword seasonality (query annual data)
json
{
"marketplace": "us",
"keyword": "christmas decorations",
"startDate": "2025-01-01",
"endDate": "2025-12-31"
}
3. Compare search volume between peak and off-peak seasons
Call twice:
- Off-peak season: ,
- Peak season: ,
4. Multi-marketplace comparison
Query the same keyword across different marketplaces (e.g.,
,
,
) to compare search volume scales across each marketplace.
5. Verify if market demand is growing
json
{
"marketplace": "de",
"keyword": "luftreiniger",
"startDate": "2025-04-01",
"endDate": "2026-03-31"
}
Display Rules
- Prioritize trend visualization: It is recommended to display search volume changes in a timeline/line chart, with the horizontal axis representing date cycles and the vertical axis representing search volume
- Table assistance: Provide a data table for precise reference at the same time, including columns: Cycle Start Date, Cycle End Date, Search Volume
- Trend summary: Briefly summarize the trend direction (rising/falling/stable/periodic fluctuation) after the data, and mark peak and trough cycles
- Peak marking: Highlight the cycles with the highest and lowest search volume to help users quickly identify peak and off-peak seasons
- Error handling: When a query fails, explain the reason based on the error response and suggest adjusting parameters (e.g., date range exceeds 366 days)
Important Limitations
- Time span limit: The maximum span from to for a single query is 366 days; split into multiple queries if exceeded
- Data granularity: Weekly (one data point per 7 days), not daily
- Search volume type: Exact Match search volume, not Broad Match
- All parameters required: , , , are all mandatory
User Expression & Scenario Quick Reference
Applicable - Historical trend analysis of keyword search volume:
| User Says | Scenario |
|---|
| "How has the search volume of this keyword changed?" | Search volume trend query |
| "Does this category have seasonality?" | Judge seasonal patterns with annual data |
| "Is the search volume rising or falling recently?" | Recent trend judgment |
| "When is the peak season?" | Peak cycle identification |
| "What was the search volume in Q4 last year?" | Search volume query for a specified time period |
| "Is this keyword popular on the German marketplace?" | Search volume query for non-US marketplace |
| "Compare search volumes of two time periods" | Peak/off-peak season/year-over-year comparison |
Not applicable - Beyond the scope of historical keyword search volume:
- Keyword suggestions/expansion (requires keyword research tools)
- Real-time/current search volume ranking (requires ABA or SIF tools)
- Keyword competitiveness, CPC bidding
- Product sales, listing analysis
- Search volume on non-Amazon platforms
Boundary judgment: When users say "search volume", "keyword popularity", or "market demand trend", if they specifically want to see how a keyword's search volume changes over a period of time (historical trend), this skill applies. If they want the current ranking or a list of trending keywords, it does not apply.
Feedback:
Auto-detect and report feedback via the Feedback API when any of the following apply:
- The functionality or purpose described in this skill does not match actual behavior
- The skill's results do not match the user's intent
- The user expresses dissatisfaction or praise about this skill
- Anything you believe could be improved
Call the feedback API as specified in
. Do not interrupt the user's flow.
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