Use Cases for Historical Search Volume Endpoint

Updated July 18, 2025 06:21

The Historical Search Volume endpoint allows you to track keyword search trends over time to identify seasonal patterns and long-term market changes. This endpoint returns historical keyword search volume in seven-day increments, making it excellent for monitoring weekly search volume and trends over time.

Why Use This Endpoint: Understanding how search volume fluctuates helps with inventory planning, seasonal campaigns, identifying emerging or declining trends in your market, and strategizing around consistency or seasonal peaks of search queries. This data is crucial for making informed decisions about when to launch products, ramp up advertising, or adjust inventory levels.

Endpoint Details

Request Type: GET
URL: /api/keywords/historical_search_volume
Available Markets: US, UK, DE, IN, CA, FR, IT, ES, MX, JP

What You Can Input (Per API Call)

Required Parameters

Keyword: Single keyword to search (e.g., "sushi")
Marketplace: Country code (us, uk, de, in, ca, fr, it, es, mx, jp)
Start Date: Start date in yyyy-mm-dd format
End Date: End date in yyyy-mm-dd format

Optional Parameters

Pagination: Page size (max 100 results, default 50) and cursor for additional pages
Sorting: Multiple sort options with default set to highest monthly search volume exact

Sample Request

GET /api/keywords/historical_search_volume?marketplace=us&keyword=sushi&start_date=2025-01-05&end_date=2025-02-01

What You Get Back

Core Data Points

ID: Unique identifier combining marketplace, keyword, and date range (e.g., "us/sushi/2025-01-05/2025-01-11")
Type: "historical_keyword_search_volume"

Time Series Data

Estimate Start Date: Beginning date of the 7-day period (yyyy-mm-dd format)
Estimate End Date: End date of the 7-day period (yyyy-mm-dd format)
Estimated Exact Search Volume: Number of searches for the exact keyword during this 7-day period

Sample Response Output

json

{
  "data": [
    {
      "id": "us/sushi/2025-01-05/2025-01-11",
      "type": "historical_keyword_search_volume",
      "attributes": {
        "estimate_start_date": "2025-01-05",
        "estimate_end_date": "2025-01-11",
        "estimated_exact_search_volume": 38735
      }
    },
    {
      "id": "us/sushi/2025-01-12/2025-01-18",
      "type": "historical_keyword_search_volume",
      "attributes": {
        "estimate_start_date": "2025-01-12",
        "estimate_end_date": "2025-01-18",
        "estimated_exact_search_volume": 38384
      }
    },
    {
      "id": "us/sushi/2025-01-19/2025-01-25",
      "type": "historical_keyword_search_volume",
      "attributes": {
        "estimate_start_date": "2025-01-19",
        "estimate_end_date": "2025-01-25",
        "estimated_exact_search_volume": 36878
      }
    },
    {
      "id": "us/sushi/2025-01-26/2025-02-01",
      "type": "historical_keyword_search_volume",
      "attributes": {
        "estimate_start_date": "2025-01-26",
        "estimate_end_date": "2025-02-01",
        "estimated_exact_search_volume": 35751
      }
    }
  ]
}

Data Highlights

Data Granularity: Weekly increments for up to 1 year of historical data in 1 call
Data Structure: Time series data listed by 7-day periods with exact start/end dates
Search Method: 1-to-1 basis - input one keyword with date range, get weekly data points
Date Range: Can retrieve up to one year's worth of historical data per API call

Use Cases & Applications

1. Analyzing Seasonality Trends in Keywords

Business Goal: Reveal seasonal trends of specific keywords to strategize around consistency or seasonal peaks of search queries.

How to Implement:

Retrieve weekly search volume data for your target keywords
Aggregate weekly data into monthly or quarterly figures for trend analysis
Calculate percentage distribution across time periods to identify seasonality patterns
Apply seasonality scoring to understand keyword behavior patterns

Seasonality Analysis Framework:

Monthly Seasonality Analysis:

Identify the month with the highest percentage of total search volume
Low Seasonality: Under 10% of annual volume in peak month
Moderate Seasonality: 10-15% of annual volume in peak month
High Seasonality: Above 15% of annual volume in peak month

Quarterly Seasonality Analysis:

Determine the quarter with the highest percentage of total search volume
Low Seasonality: Under 30% of annual volume in peak quarter
Moderate Seasonality: 30-35% of annual volume in peak quarter
High Seasonality: Over 35% of annual volume in peak quarter

Key Metrics to Focus On:

Weekly search volume trends over 12-month periods
Month-over-month and quarter-over-quarter percentage changes
Peak and valley periods for inventory and campaign planning
Year-over-year comparisons for growth assessment

Business Impact: Optimize inventory management, advertising spend timing, and product launch schedules based on predictable search patterns. Reduce waste by avoiding heavy investment during low-demand periods.

2. Identifying Top Months and Quarters for Search Volume

Business Goal: Compile weekly search data into comprehensive monthly and quarterly summaries to quickly identify peak performance periods and plan strategic initiatives.