Build an n8n AI Agent That Turns Showing Feedback into a Seller Update

Step 1: Go to n8n.io

Every showing ends with feedback from the buyer's agent, in a text, an email or a quick call. By Friday your seller wants to know what people are saying, and the one comment that matters most, a buyer about to make an offer, is easy to lose. We are going to build an AI agent that logs every showing in a spreadsheet for you. First, you need an n8n account.

Step 2: Enter your email

This is just practice, so anything works — it won't actually send anything.

Step 3: Sign up

In the real n8n, it sends you a six digit code, then asks for a name, a password, and an account name. Go do that in your own browser later, then come back and we will build.

Step 4: Add credit first

Your agent needs a brain, and that means an API key from OpenAI. Go to platform dot openai dot com — that is the developer side, not ChatGPT, and it bills completely separately. Before you make a key, put some money on the account. A brand new key with a zero balance just returns errors. If you would rather not spend anything yet, n8n gives every new account free credits. In your own n8n, you can pick gateway credits on the model step and skip the key.

Step 5: Ten dollars is plenty

Ten dollars goes a very long way. You are charged per request, not per month, and logging a week of showings costs fractions of a cent.

Step 6: Now the key

Balance sorted. Now go to API keys in the left menu.

Step 7: Create a secret key

Step 8: Name the key

Name it after whatever is going to use it. Future you, staring at a list of forty keys, will thank you. I am calling this one n8n agent.

Step 9: Create it

Default project, all permissions — that is fine for this. Create the key.

Step 10: Copy it now

Now pay attention, because this is the only time you will ever see this key. Copy it and paste it into n8n, or into your password manager. If you lose it, you do not get it back — you delete it and make another.

Step 11: Back to n8n

One last warning — this key can spend your money. Never commit it to code, never paste it into a chat, and if it ever shows up on screen while you are recording, revoke it before you publish.

Step 12: Start a new workflow

Now you are inside n8n. This overview page lists every workflow you have. Top right, click create workflow, and you land on an empty canvas.

Step 13: Add the first step

Every workflow needs a trigger — the thing that kicks it off. We want a chat trigger so you can paste in the week's showing feedback.

Step 14: Trigger on a chat message

A panel slides in with every way a workflow can start — manually, on a schedule, on a webhook. We want on chat message, so we can have a conversation with the agent.

Step 15: Back to the canvas

n8n opens the node so you can configure it. There is nothing we need to change here, so close it with the X in the top right and get back to the canvas.

Step 16: Add the next node

Now we decide what happens when a message comes in.

Step 17: Open the AI nodes

A panel opens and asks what happens next. The agent lives under AI, right at the top.

Step 18: Add the AI Agent

There it is — AI Agent. This is the piece that can plan and then carry out actions using whatever tools you give it. You give it the feedback, and it can sort each showing and save it to a spreadsheet — all in one step.

Step 19: Open the options

Right now this agent has no personality and no orders. It does not know it works for Meridian Realty, or what a showing entry looks like.

Step 20: Add a system message

Pick system message. This is the standing instruction the agent reads before every request. It is where we tell it who Meridian is, how to log a showing, and what it must never do.

Step 21: Write the system prompt

Here is the actual prompt. It tells the agent what each entry needs: the date, the buyer's agent, an interest level, the price feedback in the agent's own words, and the next step. Vague feedback gets marked unclear. And two rules matter most: record only what was said, and never recommend a price change. That's your call, with your seller.

You are the showing feedback assistant for Meridian Realty Group.

Meridian Realty Group is a small residential brokerage. Its listing agents send sellers a feedback update every week while a home is on the market.

The audience is the listing agent, who reads every entry before sharing anything with the seller.

The tone should be plain, neutral and factual.

Your job is to turn each piece of showing feedback the user gives you into one entry.

For each showing, return:
- Date
- Buyer's agent (name and brokerage only)
- Interest: High, Some, None, or Unclear
- Price feedback: what the buyer's agent said about the price, in their words, or "None given"
- Follow-up: one sentence on what the listing agent should do next, like answer a question or expect an offer

If the feedback is vague or mixed, use Unclear and say why.

When the user asks you to save the feedback, use the Google Sheets tool to store each entry.

Record only what was said. Do not guess what a buyer will offer, and do not recommend a price change; the listing agent and the seller decide that. Never include buyers' names, phone numbers or personal details.

Step 22: Back to the canvas

That gives the agent everything it needs to know about logging showings for Meridian. Close the node.

Step 23: Give the agent a brain

See that red triangle on the agent? It is complaining because it has no model. An agent can plan, but it cannot think without a language model underneath it.

Step 24: Pick OpenAI

OpenAI chat model. This is where that API key finally gets used.

Step 25: Open the credentials

And here is where that key you copied finally goes.

Step 26: Create a new credential

You want create new credential, right at the bottom. In your own n8n, if you skipped the key, you would pick gateway credits here instead.

Step 27: Paste the key

This is the one moment it matters that you copied it — remember, OpenAI never shows it to you again.

Step 28: Save the credential

n8n tests the connection straight away, and from now on this credential is available to every node in every workflow — you only do this once.

Step 29: Open the model list

Now the model dropdown.

Step 30: Choose the model

GPT five mini. Fast, cheap, and plenty for sorting showing feedback. Do not reach for the expensive model until you have a reason.

Step 31: Back to the canvas

That is the brain wired in. Close it up.

Step 32: Add memory

Next, memory. Without this, every message starts from nothing — you could not say save those, because it would not remember which showings you meant.

Step 33: Simple Memory

Simple memory is fine here — it keeps the recent conversation inside n8n, no database, no extra credentials.

Step 34: Back to the canvas

n8n opens simple memory so you can set it up. The defaults are fine. It keeps the last five messages. Close it with the X.

Step 35: Add a tool

And now the good part — tools. This is what separates an agent from a chatbot. A chatbot just talks. An agent does things. We are going to give it Google Sheets so it can save every showing into a spreadsheet you can go through with your seller.

Step 36: Search for Sheets

Google Sheets is not in the recommended tools, so search for it.

Step 37: Add Google Sheets

Google Sheets tool. Now the agent can write rows into a real spreadsheet, with columns matching what the system prompt tells it to return. When you say save those, each showing becomes a row.

Step 38: Back to the canvas

Before we set this up, we need to actually create the spreadsheet. Close this node for now — we are going to hop over to Google Sheets and make one.

Step 39: Open Google Sheets

Switch to Google Sheets. You need to create the spreadsheet that this node will write to.

Step 40: Name the spreadsheet

First, name it so you can find it later.

Step 41: Type the first column header

Now set up the column headers. These need to match what the system prompt tells the agent to return. In A1, type Date.

Step 42: Buyer's agent

B1 — Buyer's agent.

Step 43: Interest

C1 — Interest.

Step 44: Price feedback

D1 — Price feedback.

Step 45: Follow-up

And E1 — Follow-up. Five columns, matching exactly what the system prompt tells the agent to return. Each showing becomes a row in this sheet.

Step 46: Back to n8n

The spreadsheet is ready. Switch back to n8n and connect the Google Sheets node to it.

Step 47: Open the Sheets node

Double click the Google Sheets node to open it back up. Now we can connect it to the spreadsheet we just made.

Step 48: Add a credential

Now we need to connect this to a real Google account.

Step 49: Create a new credential

Create new credential — this one uses Google OAuth instead of an API key, so it is going to open a sign-in window.

Step 50: Sign in with Google

This opens the Google account chooser so you can pick which account to connect.

Step 51: Choose your account

Pick the Google account you want n8n to use. This is the account that owns the spreadsheet.

Step 52: Allow Sheets access

Google is asking what n8n is allowed to do. Check the first box — this lets n8n read and write your spreadsheets.

Step 53: Allow Drive access

Second box — n8n needs Drive access so it can find your spreadsheets by name.

Step 54: Allow external service

Last one — this lets Google connect to n8n as an external service. Check it.

Step 55: Sign in

All three checked.

Step 56: Pick the operation

Now we tell the node what to do. By default it reads rows, but we want to add rows.

Step 57: Append Row

Append row. Every showing the agent logs gets added as a new row at the bottom of the sheet.

Step 58: Choose the spreadsheet

Now pick the spreadsheet.

Step 59: Showing Feedback Log

Showing Feedback Log — the sheet we set up with columns for the date, the buyer's agent, interest, price feedback, and follow-up.

Step 60: Pick the sheet tab

Now pick which tab inside that spreadsheet.

Step 61: Sheet1

Sheet one — it is the only tab, so this is simple.

Step 62: Map the Date column

Now the columns. Each column has a purple button — click it and the AI agent figures out what data goes there.

Step 63: Map the Buyer's agent column

Buyer's agent. Same thing — click the purple button.

Step 64: Map the Interest column

Interest.

Step 65: Map the Price feedback column

Price feedback.

Step 66: Map the Follow-up column

And follow-up. Each one is now set to defined automatically by the model — the agent reads your column headers and figures out what goes where.

Step 67: Back to the canvas

The sheets tool is fully wired up — credential, operation, spreadsheet, sheet, and column mapping. Close it and let us test this thing.

Step 68: Open the chat

Everything is connected. Time to see if it works.

Step 69: Paste this week's feedback

Give it this week's feedback for 14 Orchard Lane, the way it actually arrives: three buyer's agents, three different messages.

Log this feedback for 14 Orchard Lane: Oct 14, Dana Ruiz of Keystone Homes: buyers loved the kitchen and the yard, worried about road noise, think it is about $15,000 high. Oct 15, Marcus Hill of Hill & Co.: second showing, his buyers plan to write an offer this week and asked how old the roof is. Oct 15, Priya Shah of Open Door Realty: nice house, but her buyers need four bedrooms, so it is not a fit.

Step 70: Send the message

Send it off. The agent reads your system prompt and turns each showing into one entry, with an interest level, the price comment in the agent’s own words, and the next step.

Step 71: Save to the sheet

Three showings: some interest with a price comment, a buyer ready to write an offer, and one that's simply not a fit. The agent flagged the one that needs you today: send Marcus the roof age. And notice it didn't suggest cutting the price. Now tell it to save them. This is where the Google Sheets tool kicks in.

Step 72: Send it

Send it. The agent uses the Google Sheets tool to write each showing as a row — date, buyer's agent, interest, price feedback, and follow-up.