Competitor Analysis

Competitor Analysis

Analyze a company's e-commerce presence, product catalog, marketing activity, and sales performance using Particl data.

When to use

When the user wants to research a specific company or brand — their products, pricing, bestsellers, marketing strategy, or overall performance.

Workflow

1. Find the company using search_companies with the company name or domain. This is FREE.

   • Extract the company_id from the results

2. Get company details using get_company_details with the company_id. Costs 1 credit.

   • Shows company profile: name, domain, country, vertical, product count, top categories
   • Check has_product_data — if false, skip product tools (no data available)

3. Discover categories using get_product_types (FREE) to find valid product_type filter values.

   • Call with no args for root categories, then drill into subcategories with parent_product_type_id

4. Analyze their product catalog using get_company_products with the company_id. Costs 1 credit per product returned.

   • Default sort is by sales_revenue descending (bestsellers first)
   • Use page_size to control how many products (default 25, max 100)
   • Use product_type or keyword filters to narrow by category
   • Use title_search to search by product name (e.g., 'tank top', 'winter jacket')
   • Use start_date and end_date to control the sales data window
   • Paginate with page parameter for deeper exploration

5. Review their marketing using get_company_marketing_assets for emails, social posts, and ads. Costs 1 credit/row.

   • Filter by asset_types: 'email', 'instagram_post', 'facebook_ads', 'sms', 'homepage_screenshot'
   • Use get_company_marketing_stats for aggregated engagement metrics (1 credit)

6. Check promotional events using get_company_events for launches, sales, restocks. Costs 1 credit/row.

7. Present findings with:

   • Company overview (vertical, product count, top categories)
   • Top products by revenue
   • Price range analysis
   • Marketing activity and engagement
   • Notable patterns (new launches, discounting, promotional events)

Tips

• Always check credits first with get_credit_balance if doing a large analysis
• Start with a small page_size (10-15) to get an overview before going deeper
• Use sort_by: "launch_date" with sort_direction: "desc" to find newest products
• Use sort_by: "price" to understand pricing tiers
• Use title_search instead of keyword when searching for product names