The Competitor Intel Playbook: Turn n8n Ad Monitoring Into a Recurring Agency Service

Introduction

This week two posts crossed my feed that, on the surface, have nothing in common. One founder over on r/SaaS shared that their software is finally making money. Another operator on r/n8n shared a workflow that automatically spies on competitor Facebook ads every week.

To me, these are the same post. The first proves that small, focused automation can create real revenue. The second shows exactly how to apply that mindset to sales and marketing. If you run an agency, a B2B service team, or any business that competes on speed and insight, you should steal both ideas—especially the second one.

This is the playbook I use when a client asks, 'What should we automate first?' It turns competitor ads into a structured intel feed that your team reads once a week, and it can become a paid deliverable you sell to clients.

The Problem

Most service businesses operate in the dark. They know their own messaging, but they don't know what the market keeps getting hit with. Competitors rotate offers, run promotions, change positioning, and test new hooks. By the time you notice, they've already owned the conversation for weeks.

Manually checking the Facebook Ad Library is possible, but nobody does it consistently. It's a boring, repetitive task. So it doesn't get done. The result: your team pitches without knowing how your competitor framed their last three offers.

The Solution

Build a small n8n workflow that collects competitor Facebook ads on a schedule, summarizes them, and sends the digest to Slack or Notion before you start your week.

This is not a hypothetical workflow. The r/n8n post I referenced is proof that real operators are already running this. The workflow is simple enough to build in an afternoon, and it scales across industries. Once it runs, you have something most agencies don't: a repeatable process for watching the market.

Playbook: Build Your Own Competitor Intel Loop

Step 1: Pick Your Targets

Don't monitor everyone. Pick the five competitors whose customers you actually want. For each competitor, save their Facebook page. Decide what matters: their active ads, ad copy, landing page approach, special offers, and how long a campaign runs.

Step 2: Use Meta Ad Library as the Source

Facebook ads are public by design. Use the Meta Ad Library to search ads from a specific page. In n8n, this becomes a scheduled API call. The key is to store the list of competitor Facebook page IDs and loop through them each time the workflow runs.

Step 3: Let n8n Pull and Normalize

Set up a Schedule Trigger. For an agency, Monday at 6 a.m. works well. The trigger hits the Meta Ad Library API for each competitor, pulls the latest ad creative, and drops the results into a common dataset. No manual copy-paste. No spreadsheet.

Step 4: Add an AI Summarizer

Raw ad copy is noisy. The real value is pattern detection. Add an LLM node in n8n—OpenAI, Claude, or the model you already use—and instruct it to output a short battle card for each competitor. Include what the offer is, who it's targeting, the emotional hook, and any call-to-action pattern.

The AI layer is what separates a data dump from an intel report.

Step 5: Push to Your Team

Send the finished digest to Slack, Discord, or Notion. If you want client-ready output, format it as a markdown summary and email it from the same workflow. Keep the output short. Five competitors, one paragraph each, plus one 'what changed this week' note.

Turning This Into a Client Offer

Here's where the r/SaaS signal becomes relevant. If the founder posting on r/SaaS taught us anything, it's that a small tool doesn't need to be huge to make money. The same applies to a service offer.

A competitor ad intel dashboard is a natural monthly retainer for agencies that manage lead gen for B2B clients. Set up the workflow once per client, then deliver a short weekly report. The client gets a feeling of control over their market. You get recurring revenue without daily manual effort.

The actual build is not the moat. The moat is knowing which competitors matter to each client, what 'winning' looks like in their niche, and how to translate a raw ad into a recommendation. That's your expertise. n8n just does the boring part.

If you're not ready to sell this yet, run it internally for your own agency. Use the digest to prepare for pitches, review your positioning, and steal good offer structures. Once you've seen it work, package it.

Implementation Notes

Build it in this order:

• Create a folder in n8n for 'Competitor Intel.'
• Store competitor page IDs in a database collection or a simple JSON node so you don't hardcode them.
• Add a Schedule Trigger first, then the HTTP Request node for Meta Ad Library.
• Map the response fields: page name, ad headline, body text, link description, date.
• Add your LLM node after the aggregation. One summary per competitor is better than one giant raw export.
• Connect Notification nodes last so you don't spam yourself while testing.

A few practical warnings. Respect Meta's rate limits. Keep your access token secure. Don't include internal client names in a shared workflow if you're repurposing this across accounts. And remember: this is public ad data, not dark-pattern snooping. You're looking at the same ad library every person with a Facebook account can open.

Results

What changes when you run this for a month? You stop being surprised by competitor offers. You walk into a pitch knowing whether the incumbent is running a discount, pushing a free trial, or leaning into a fear-based message. Your own ad testing becomes more deliberate because you can see what theme is saturated.

You also buy back time. One person no longer has to manually check ad libraries every week. The workflow runs itself. That is the leverage every service business should be selling.

I don't have a dashboard full of numbers from this exact workflow to show you. What I know from the two posts that inspired this playbook is that the market is already moving in this direction. Founders are shipping small tools that make money. Operators are building automations that feel unfair. The smart play is to combine the two.

Key Takeaways

• Competitor Facebook ads are public intelligence, and n8n can turn them into a weekly report automatically.
• The hard part is not the API call. It's the prompt, the target list, and the recommendation layer.
• Agency owners can package this as a monthly retainer, not just an internal tool.
• Start with two or three competitors. Perfection kills speed.
• Use AI to summarize, not to invent strategy. The workflow informs decisions; you still make them.

Sources

• Reddit r/SaaS: My software is finally making money
• Reddit r/n8n: I built an n8n workflow that automatically spies on competitor Facebook ads every week