Building an AI-Powered Lead Nurture Sequence with Make + OpenAI
Traditional email nurture sequences send the same message to every lead. AI-powered nurture adapts the content, timing, and message to each lead’s profile and behaviour — significantly improving conversion rates.
The Core Upgrade
| Dimension | Traditional Sequence | AI-Powered Sequence |
|---|---|---|
| Content | Same email for every lead | Personalised to industry, role, and behaviour |
| Timing | Fixed schedule (Day 1, Day 3, Day 7) | Adaptive — triggered by engagement signals |
| Tone | One voice for everyone | Adjusted to lead’s communication style |
| Subject lines | A/B tested manually | AI-generated variants per lead segment |
| Call to action | Same CTA for all leads | CTA matched to lead’s stage and interest signals |
| Follow-up | Sequence ends regardless of engagement | Continues adapting based on opens, clicks, replies |
How the System Works
Four connected components that make personalised nurture at scale possible.
Lead Database (Airtable, Bubble, or HubSpot)
Stores lead profile data: company, role, industry, ICP score, lead source, pages visited, content downloaded. The richer this data, the more personalised the AI’s output.
Make.com — Orchestration Layer
Watches for trigger events (new lead, email opened, link clicked, day X in sequence), runs the scenario, calls OpenAI, and dispatches the personalised email via your email platform.
OpenAI GPT — Personalisation Engine
Receives the lead’s profile data and sequence context. Generates a personalised email subject line and body tailored to that specific lead’s industry, role, and behaviour signals.
Email Platform (SendGrid, Mailchimp, ActiveCampaign)
Sends the AI-generated email and reports back engagement data (opens, clicks) to Make via webhook — feeding the next personalisation decision.
Setting Up the Complete System
Configure your lead data model
Ensure your lead database has: first name, company name, job title, industry, lead source, ICP score, and a sequence_stage field (values: new / nurture_1 / nurture_2 / nurture_3 / qualified / unsubscribed). This stage field controls where each lead is in the sequence.
Create the Make scenario for Nurture Email 1
Trigger: Watch Records in your lead database where sequence_stage = new. For each new lead, call OpenAI with their profile data. Prompt: ‘Write a personalised nurture email for a [job title] at a [industry] company called [company name]. Our product helps [value prop]. The lead came from [lead source]. Write a subject line and 3-paragraph email body. Be specific to their industry. Do not sound like a template.’
Map AI output to email fields
Parse the OpenAI response to extract the subject line and body (use json_object response format for clean parsing). Map to your email platform’s send module. Update the lead’s sequence_stage to nurture_1 after sending.
Build the engagement-triggered follow-up
Create a second scenario triggered by email open webhook: if a lead opens Nurture Email 1 within 48 hours, send a follow-up that references the first email’s topic and adds a case study. If they click a link, trigger an immediate high-intent follow-up offering a call.
Build the time-based fallback
Create a third scenario triggered by schedule: if 5 days pass and the lead has not opened Nurture Email 1, send a different subject line variant. If they do not open Nurture Email 2 either, move to sequence_stage = low_engagement and reduce frequency.
Add the qualification trigger
When a lead clicks a high-intent link (pricing page, case study, schedule a call), trigger an immediate Make scenario: update sequence_stage to qualified, create a task in your CRM for the sales team, and send a personalised email with a direct meeting booking link.
Writing the Nurture Email Prompt
The quality of your nurture sequence depends entirely on your prompt. Here is a template that works.
System prompt stored in Make as a text variable:
You write personalised B2B nurture emails for SA Solutions, a software development agency
specialising in Bubble.io applications and AI automation.
Our ideal customers are: founders and product managers at growing startups who need
to build web applications without large engineering teams.
Writing rules:
- Maximum 150 words for the email body
- One specific, relevant call to action per email
- Reference the lead's specific industry in the first sentence
- Never use filler phrases: 'I hope this email finds you well', 'touching base', 'reaching out'
- Sound like a knowledgeable peer, not a sales rep
Return as JSON only: {subject: string, body: string}
📌 Store this system prompt in a Make data store or a configuration record in your Bubble database — not hardcoded in the scenario. This lets you update it without rebuilding the scenario.
Want an AI Nurture Sequence Built for Your Business?
SA Solutions builds complete AI-powered sales automation systems — from lead capture through nurture to qualified opportunity. Fully automated, personalised at scale.