Market Research Report Generator
Daily automated market research that scrapes news and competitors, analyzes trends with AI.
What it does
Receive daily automated market briefs that save you from manual research by scraping industry news and competitor sites. The workflow analyzes these sources with AI to generate structured reports containing trends and SWOT insights directly in your Notion database. You get executive summaries posted instantly to Slack so stakeholders stay informed without lifting a finger.
Step by step
- Configure scheduled triggers to initiate the workflow at defined intervals
- Set up parallel HTTP requests for NewsAPI and competitor website scraping
- Map LLM output fields to specific Notion database properties
- Format Slack messages using predefined template structures
Where the LLM does the work
- Generate SWOT analysis insights from unstructured web content
- Summarize key market trends into concise executive briefs
- Structure raw scraped data into coherent Markdown report sections
Watch out for
Tools that fit
The agent brief
You are helping me build the following AI agent workflow. ## Goal Market Research Report Generator: Daily automated market research that scrapes news and competitors, analyzes trends with AI. ## Specification - What it does: Receive daily automated market briefs that save you from manual research by scraping industry news and competitor sites. The workflow analyzes these sources with AI to generate structured reports containing trends and SWOT insights directly in your Notion database. You get executive summaries posted instantly to Slack so stakeholders stay informed without lifting a finger. - Trigger: On a schedule (Scheduled · daily) - Autonomy: Fully hands-off - Expected setup effort: about an afternoon - Tools/services involved: - NewsAPI: Fetching industry news - HTTP Request: Scraping competitor websites - LLM: Analyzing content and generating insights - Notion: Saving structured reports - Slack: Posting executive summaries and errors ## Known pitfalls, handle each one explicitly in your implementation 1. Competitor websites may block automated scrapers so use rotating user agents and respect robots.txt rules. 2. Notion API requires specific database IDs so verify property types match the LLM output format exactly. 3. Slack message length limits can truncate summaries so add character count checks before posting. ## Reference implementation https://n8n.io/workflows/12581 (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/automated-market-research-report-generator/ via usecasesforagents.com
Frequently asked questions
Can I use a different Search than NewsAPI?
Yes. NewsAPI is only the example search in this recipe. The same flow works with GNews, InfraNodus, Jina AI and SerpApi. Swap the search connection and keep the rest of the setup as written.
Want this running in your business?
Who it's for
Built for founders and execs who need research handled without hiring for it.
Marketers can point this at their own content pipeline with no changes to the pattern.
Analysts get a ready-made pattern for turning raw numbers into a report someone will actually read.