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A lead fills in your contact form at 4:50 on a Friday. It lands in a shared inbox. The first person to open it is you, on Monday, after coffee. By then the prospect has heard back from two of your competitors, and the one who replied first is the one they're talking to.
This is the n8n workflow we build to stop that happening, written up the way you'd want it if you were paying for it. What it does. What each step costs you. Where the model is allowed to decide and where it isn't. And the actual template you can paste into your own n8n. It's the same shape as the pipeline we migrated for a client from Make, where the bill went from about $109 a month to about $12. It uses only what you already have: a form, a CRM, Slack, and one API key.
What the workflow does, in one screen
Thirteen working nodes, six stages. Every stage writes what it found onto the lead, so nothing downstream has to guess, and you can see at any node exactly what the next one will receive.
That's the whole thing. If you've read our breakdown of the five processes worth automating first, this is process one built out in full, with the parts that post could only sketch for you.
Why speed is the whole point
You'll be sold lead scoring as an intelligence feature. It's a clock feature. The intelligence is nice. The minutes are your money.
In 2011, Harvard Business Review published an audit of 2,241 US companies, each sent a web-generated test lead. Only 37% responded within an hour. Another 16% took between one and 24 hours, 24% took more than a day, and 23% never responded at all. Among the companies that did respond within 30 days, the average first response took 42 hours. The same authors then looked at 1.25 million leads across 42 companies. Firms that tried to contact a prospect within an hour of the enquiry were nearly seven times as likely to qualify the lead as those that tried even an hour later. They were more than 60 times as likely as companies that waited a day or more.
Fifteen years on, the queue in most small businesses looks the same: a submissions folder someone checks two or three times a day. Every lead in that folder crosses HBR's one-hour line. If your pipeline acknowledges, scores and routes in under a minute, none of them do, including the ones that arrive at 4:50 on a Friday.
What one lead costs to score
Here's the arithmetic on a single inbound lead, using the same $22 loaded hour we use across the agent cost article. Handling one lead by hand means reading the form, looking the company up, deciding who should have it, creating the record and telling the rep. We take that as eight minutes. That's our working assumption, and you should substitute yours.
Notice what the table doesn't say. It doesn't say the pipeline saves you $1,467 a month, because the eight minutes don't disappear. Your salesperson still reads the brief and still makes the call. What changes for you is that the reading happens within a minute of the form arriving, and it starts with a summary instead of a blank record.
What the model decides, and what it doesn't
This is the part the template libraries skip, so we'll be precise about it for you, because it's what makes the workflow safe to leave running.
The model gets the form, the page text and your ideal-customer paragraph. It returns exactly one thing: a JSON object that matches a schema you set. A score from 0 to 100, up to three fit reasons citing evidence, up to three concerns, a recommended first step, and a two-sentence summary. The request uses the API's structured-output format, so the answer is valid JSON that fits the schema or it isn't returned at all. That matters in a pipeline. A free-text answer with a stray sentence in it breaks your next node at 2am.
Then the model's job ends. A few lines of code decide the tier by comparing the score with the two thresholds in your Settings node. A Switch node decides the route by reading the tier. The CRM write is a fixed field mapping. The acknowledgement email is a template with three substitutions: first name, your company name, and your reply promise. Nothing the model wrote reaches your prospect.
The same logic covers the model declining to answer. If the API returns a refusal, or anything that isn't a clean integer score, the Code node doesn't guess. It marks the lead "review" and sends you a Slack message saying why. Silent failure is the one thing your lead pipeline must never do, because a lead that vanishes looks exactly like a quiet week.
The template, node by node
Thirteen working nodes plus four sticky notes with the setup instructions. You edit one node; the rest run as they are.
The scoring call is deliberately a plain HTTP Request node rather than a vendor node. Two reasons. It survives n8n upgrades, because the HTTP node's shape hasn't changed in years while the AI nodes get rewritten every few months. And it's provider-neutral. To use a different model you change a URL, two headers and a body, and you keep the JSON schema so the tier code still works.
Get the template
Copy the JSON below, open a new workflow in n8n, and paste it onto the canvas. n8n creates all seventeen nodes with the connections and the sticky notes. Then follow the yellow overview note. Edit Settings, add a Header Auth credential named x-api-key for the scoring node, select your Slack, HubSpot and Gmail credentials, and click Test workflow. The pinned sample lead runs the whole thing end to end before you've connected a real form.
We validate the file the way you'd want any template validated. Every node type and version is checked against the n8n package it will run in. Every parameter name is checked against what that node actually declares. Every connection is checked against a node that exists. That doesn't prove the workflow will do what you want with your data. It proves it will load and run without you debugging our typos first. The same treatment for an online store's support inbox is in our Shopify customer support workflow.
Where the platform bill lands
You don't need a big volume for the economics to matter, and you don't need to self-host on day one. But the shape of the bill is worth knowing before you pick a platform, because this pipeline is exactly the kind that per-step billing punishes you for.
Each lead through this template is one n8n execution. On a per-operation platform it's about thirteen credits, one per node. At 500 leads a month that's 6,500 credits against 500 executions. At 2,000 leads it's 26,000 against 2,000. The client pipeline we migrated had this shape, with a lead-scoring model call in the middle. At around 90,000 operations a month its Make bill had reached about $109 with extra credit packs. Rebuilt in self-hosted n8n, it ran on a $12 VPS with unlimited executions, plus about two hours a month of maintenance we told the client to budget for. The full comparison has the numbers and the honest caveat: at a few hundred leads a month, managed and zero-maintenance is often the better deal.
Where it goes wrong
The same rules hold for every agent we build for you. The handoff article is the longer version of why the "Needs a human look" node exists and what your Slack message should contain.
What to require from whoever builds it
Whether that's us or anyone else, this is what you should see before a lead pipeline goes live.
