I keep running into “Paired item data is unavailable” errors in n8n and I’m never 100 % sure when to merge, reduce, split in batches, or just reference .first() instead of .item. If you’ve got a go-to checklist or best practices for: - Merging branches that output different item counts - Keeping indexes aligned after a Reduce / Aggregate - Avoiding nulls when a branch returns zero items …I’d really appreciate the guidance (and any sample screenshots)! What rules do you follow to decide which merge strategy to use and where to stick Item Lists or SplitInBatches nodes? Thanks a ton 🙏 – hoping to make these “paired item” headaches a thing of the past.

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Hey folks! 👋 Just wanted to share a wild client story that perfectly shows the power of thinking bigger with AI... THE ORIGINAL ASK: Client reached out for a "simple N8N automation" to sync their CRM data. Standard 5-figure automation project, nothing fancy. THE OPPORTUNITY I SAW: During discovery, I realized they were manually hunting for upsell opportunities, wasting 80+ hours/month, and had customers dropping off after random sales pitches. That's when it clicked: Why automate data sync when we could automate revenue growth? WHAT I PROPOSED INSTEAD: An internal AI engine for their CS team that: - Predicts upsell opportunities in real-time - Scores customer "temperature" for readiness - Triggers automated playbooks at the perfect moment - Prevents churn by protecting vulnerable accounts THE RESULTS: - Upgraded from 5-figure automation to 6-figure AI system - Discovered $1M+ in expansion revenue hiding in their CRM - 47% of customers were qualified but never approached - Projected $1.47M+ impact in Year 1 THE TWIST: I actually built this system 3 different times using Claude, OpenAI, and Gemini to see which AI could handle the complexity. One scored 92/100, others failed hard. The full breakdown (with scores, failures, and exact revenue calculations) is in my Twitter thread if you want to see how each AI performed. KEY TAKEAWAY: Sometimes the biggest opportunity isn't automating what they asked for—it's automating what they didn't know they needed. Anyone else had success upselling from basic automation to AI-powered business intelligence?

For a deeper discussion on optimizing this workflow, let's chat here. In this video, I break down how I built the most in-depth AI research system in n8n—capable of generating detailed research reports with all sources linked for just $0.50 per report! 🚀 You'll see: ✅ How the system gathers and analyzes data ✅ How it compiles a PDF research report ✅ Key optimizations to make it even more efficient Everything you need to set up this workflow is linked in the template that's attached to this post! Google Sheet Template Tavily PDF API OpenRouter