E-commerce Product Research and Market Report
Send a product query and budget to get a structured market report with pricing, reviews.
E-commerce Operatorfreelancers and consultants
What it does
Get a structured market report with pricing, reviews, and complaints by simply sending your product query and budget. This process analyzes data from platforms like Amazon and Noon to provide you with buying insights and gap analysis for sellers.
Step by step
- Configure the n8n HTTP Request nodes to call the Firecrawl API endpoints for search and scrape operations.
- Define the JSON schema in the AI Agent node to enforce a consistent output structure for the final report.
- Set up environment variables for the Firecrawl API key and OpenRouter API key within the n8n workflow settings.
Where the LLM does the work
- Generate natural language summaries of common customer complaints extracted from scraped review text.
- Perform gap analysis by comparing competitor features against user requirements to identify market opportunities.
- Synthesize raw pricing data into a coherent buying insight narrative that highlights value propositions.
Watch out for
Firecrawl may block requests if you exceed their rate limits, so implement retry logic with exponential backoff in your workflow.
Scraped review text often contains noise or irrelevant content, so add a preprocessing step to clean the data before sending it to the LLM.
OpenRouter models can hallucinate specific product details not present in the source, so instruct the model to only use provided context for factual claims.
Regional pricing differences might be missed if you do not explicitly pass the target region parameter to the Firecrawl search query.
Tools that fit
n8n AI Agent node Service Orchestrating the workflow and planning search strategy
OpenRouter Chat Model LLM Analyzing data and generating the structured report
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal E-commerce Product Research and Market Report: Send a product query and budget to get a structured market report with pricing, reviews. ## Specification - What it does: Get a structured market report with pricing, reviews, and complaints by simply sending your product query and budget. This process analyzes data from platforms like Amazon and Noon to provide you with buying insights and gap analysis for sellers. - Trigger: Run manually (Manual · on demand) - Autonomy: You stay in control - Expected setup effort: under an hour - Tools/services involved: - n8n AI Agent node: Orchestrating the workflow and planning search strategy - Firecrawl: Searching and scraping product pages across marketplaces - OpenRouter Chat Model: Analyzing data and generating the structured report ## Known pitfalls, handle each one explicitly in your implementation 1. Firecrawl may block requests if you exceed their rate limits, so implement retry logic with exponential backoff in your workflow. 2. Scraped review text often contains noise or irrelevant content, so add a preprocessing step to clean the data before sending it to the LLM. 3. OpenRouter models can hallucinate specific product details not present in the source, so instruct the model to only use provided context for factual claims. 4. Regional pricing differences might be missed if you do not explicitly pass the target region parameter to the Firecrawl search query. ## Reference implementation https://n8n.io/workflows/14405 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/e-commerce-product-research-and-market-report/ via usecasesforagents.com
Frequently asked questions
Can I use a different Web Scraping than Firecrawl?
Yes. Firecrawl is only the example web scraping in this recipe. The same flow works with Airtop, Apify, Bright Data and Decodo. Swap the web scraping connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Also fits E-commerce Operator.
Freelancers and consultants can run this per-client with no changes beyond the source data.