A market analyst that watches the internet for you, every day
Continuous monitoring of forums, social and search engines that separates signal from noise and delivers a Notion summary plus a ready-to-send email — without reading manually.
What it solves
Knowing what the market really wants means constantly reading forums, social media and search results, separating the noise — tutorials, promos, generic content — from the real signals: people complaining about a tool, asking for alternatives, or showing purchase intent. Doing it by hand is not viable on a daily basis. This system automates it.
How it’s built
The system runs on its own, on the schedule and niche you set at configuration time:
- Scheduled trigger — at the configured frequency, the system kicks off on its own with a niche, a query and a focus brief already set.
- Signal hunting — an AI agent crawls public discussions on search engines and social media, specifically looking for complaints, competitor comparisons and requests for alternatives, discarding generic content.
- Dual output — a second agent turns those findings into two usable formats: a summary ready to paste into Notion and a professional email ready to send to a client or the team.
- Notion history — the summary is saved automatically into a Notion database, building up a market intelligence record over time.
- Outbound email — the email is sent on its own to the configured recipient, with no intermediate steps.
- Failure alerts — if anything fails at any point in the process, an alert is sent automatically indicating which node failed and why.
Why it’s interesting
Market monitoring is one of those services agencies and consultancies sell as “market intelligence”, built this way it runs on its own without spending time tracking manually every day. It’s especially useful for selling recurring reports to clients without staffing an analyst team: the system delivers the summary and the email already formatted, and the Notion database becomes a reusable asset.
The workflow, in the open
The full workflow is published on GitHub: you can download it, import it into your own n8n and see exactly how it’s built, node by node → analisis-demanda-mercado.json