Match brands with influencers using GPT‑4.1, Google Sheets and SendGrid
Needs changesWhat this workflow does
This AI workflow has 18 nodes and runs when an HTTP POST request hits its webhook URL (plus 1 other trigger). Along the way it connects OpenAI Chat Model. It also calls sheets.googleapis.com and api.sendgrid.com over HTTP.
How it runs
Trigger: When an HTTP POST request hits its webhook URL (plus 1 other trigger).
- Normalize Brand Requirements (Edit Fields (Set)): sets 12 fields: brandName, industry, targetAgeRange…
- Python - Validate Brand Input (Code): runs custom Python code
- Gate - Valid Request Only (Filter): keeps only the items that match a condition
- Fetch Influencer Roster (HTTP Request): calls sheets.googleapis.com
- Fetch Engagement History (HTTP Request): calls sheets.googleapis.com
- Python - Build Influencer Profiles (Code): runs custom Python code
- Merge Brand + Influencer Context (Edit Fields (Set)): sets 14 fields: influencerProfiles, influencerCount, brandName…
- Python - Score & Rank Influencers (Code): runs custom Python code
- Wait: pauses before continuing
- AI - Generate Match Rationale (AI Agent): runs an AI agent, with model: OpenAI Chat Model
…plus 5 more steps. See the full node list below.
Services it uses
HTTP calls to: sheets.googleapis.com, api.sendgrid.com
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in AI - Generate Match Rationale (v1.6): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) AI - Generate Match Rationale (v1.6) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (10)
- Webhook
n8n-nodes-base.webhook - Schedule Trigger
n8n-nodes-base.scheduleTrigger - Edit Fields (Set)
n8n-nodes-base.set - Code
n8n-nodes-base.code - Filter
n8n-nodes-base.filter - HTTP Request
n8n-nodes-base.httpRequest - Wait
n8n-nodes-base.wait - AI Agent
@n8n/n8n-nodes-langchain.agent - Respond to Webhook
n8n-nodes-base.respondToWebhook - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi
From the author
This workflow automatically matches brands with high-converting influencers by analyzing audience insights, engagement patterns, niche alignment, and historical conversion metrics — then delivers a ranked shortlist with detailed match rationale. Who's it for…