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Aswin Behera
Aswin Behera

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How I Automated Competitor Intel for My Indie Game Using n8n, Bright Data, and Notion

#devchallenge #n8nbrightdatachallenge #ai #webdev

n8n and Bright Challenge: Unstoppable Workflow

This is a submission for the AI Agents Challenge powered by n8n and Bright Data

What I Built

As a solo indie developer working on my game serverBound, I often felt lost in the noise:

  • How do I know what players are saying about games similar to mine?
  • Which new releases on Steam are resonating, and why?
  • How do I keep track of this without burning all my creative energy on spreadsheets and manual browsing?

So I built an automated Competitor Intelligence Agent.

This workflow pulls in popular new releases from Steam, enriches them with player counts and review data, sends them to an AI agent for analysis, and finally saves everything neatly into Notion pages — one per competitor game.

The result: a live “Competitor Radar” that tells me what people are praising, what they’re complaining about, and why certain games are hot right now — all without me having to trawl through reviews manually.

Demo

Here’s a snapshot of what lands in my Notion workspace:
Workspace live at: GameDevKernel

  • Game Page Title: e.g. PEAK
  • Metadata: Steam App ID, release date, player count, review score, popularity rank.
  • AI Analyst Summary:
    1. What players are most likely talking about
    2. Risks/complaints surfacing in reviews
    3. Why the game resonates now

n8n Workflow

I published my workflow JSON as a Gist here:

👉 GitHub Gist: Competitor Radar Workflow

Technical Implementation

Step 1 — Fetch new releases

Using the Bright Data Verified Node, I scraped the Popular New Releases section on Steam. This gave me a JSON of games with title, steamAppId, releaseDate, and steamLink.

Step 2 — Enrich with player + review data

For each game, I fanned out two HTTP requests:

  • Steam’s GetNumberOfCurrentPlayers endpoint → current player count
  • Steam’s appreviews endpoint → review totals, positives/negatives, and score descriptors

I then merged these by array position into one clean JSON per game.

Step 3 — Rank games by popularity

I wrote a Function node to compute a custom popularity score (player count × log(review volume)) and sorted games into a ranked list.

Step 4 — AI Agent Analysis

Each game summary was piped into an AI Agent Node (Gemini 1.5/2.5 Flash) with this prompt:

“As an AI analyst, tell me: 1. What are players most likely talking about? 2. Any risks or complaints? 3. Why is this game resonating right now?”

The AI produced Markdown-formatted competitive insights.

Step 5 — Save to Notion

Using Notion’s API:

  • Each game becomes its own page under a parent “Competitor Radar” page.
  • The page includes all metadata at the top.
  • The AI’s markdown is split into multiple paragraph blocks (to avoid Notion’s 2000-char limit).

This means I can browse competitor insights directly in my Notion hub alongside my own dev notes.

Bright Data Verified Node

The Bright Data Verified Node was critical here:

  • SteamDB and some other sources blocked requests outright.
  • With Bright Data, I could scrape Steam’s “Popular New Releases” reliably.
  • I also used it to pull game listings from ThinkyGames.com (to expand my competitor pool beyond AAA).

Without Bright Data’s reliability, this workflow wouldn’t have worked.

Journey

I started this project thinking it would just be a quick “scrape Steam reviews” experiment. It ballooned into a full Notion-powered competitor radar.

Challenges I ran into:

  • Notion API quirks: Had to split large AI outputs into multiple paragraph blocks due to the 2000-character limit.
  • Merging API results: Steam’s APIs return data in different shapes, so I had to align everything via Merge nodes.
  • Old model hallucinations: Gemini sometimes assumed release dates were in the future, so I had to post-process context in my Function node.
  • Staying indie-lean: I resisted the temptation to over-engineer and focused on one high-ROI workflow.

What I learned:

  • As a solo dev, automation is a force multiplier. I now get daily competitive insights while focusing my energy on making my game.
  • Notion as a control tower is underrated. It’s not just notes; it can be a living database of competitor intel, player sentiment, and creative research.
  • n8n + Bright Data + AI is basically a Swiss army knife for game developers.

Why This Matters

For me, this workflow is like having a personal market analyst who works 24/7:

  • I know exactly what’s resonating with players.
  • I see early warnings of complaints or pitfalls.
  • I can benchmark ServerBound against current trends on Steam.

As a single dev, this saves me dozens of hours each week and keeps me focused on what matters: building a game players will love.

✨ That’s my submission! Indie game dev is already hard — but with the right automations, you don’t have to fight blind.

Notion

A tool that connects everyday work into one space. It gives you and your teams AI tools—search, writing, note-taking—inside an all-in-one, flexible workspace.

favicon healthy-surfboard-e7c.notion.site

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