B2B Services · Consultative Sales & Front-Desk Teams

AI New Customer Questionnaire Agent

Capture a profile you can actually act on — how they want to be contacted, what constrains them, what they care about — not a name and a phone number.

Start from this template
Edit it — the agent is built from this briefBuild this agent
How it works
1 Step
Ask at first contact
2 Step
Write it as fields
3 Step
Keep it current
The agent collects the profile during the first real conversation, when the customer is already engaged, rather than sending a form later that nobody completes.

Overview

Every business collects a new customer’s name. Almost none collect anything they can use.

The record says Sarah, a mobile number and an email. It does not say she prefers text, cannot take calls before eleven, has a second decision-maker, is working to a date in April, or has asked twice not to be added to the newsletter. Every one of those facts changes how the next twenty messages should go, and none of them are ever asked. This agent asks them once, at first contact, and writes them where the team will see them. Built on Agentplace: the agent runs on its own page, so a visitor finishes the whole request in the conversation.


Capabilities

What this agent does

Collects the profile the rest of the relationship depends on.

01

Establishes the preferred contact channel and the hours that actually work, then respects both.

02

Records who else is involved in decisions, so nothing is agreed with only half the household.

03

Captures the constraint that governs everything — a date, a budget ceiling, an access restriction.

04

Asks how they found you, in a way that produces a usable answer rather than a dropdown guess.

05

Takes marketing consent explicitly, separately from service messages, and records when.

06

Writes it all to the customer record as fields, not as a paragraph in a notes box.

Why you should use an AI agent for new customer questionnaires

Calling someone who only answers texts, emailing at a time they never read, or agreeing a date with the partner who does not decide — these are not big failures. They are small ones repeated across every customer, and they all trace to a profile that was never collected.

Before
The customer record is a name, a number and a free-text note.
Nobody knows which channel this person actually replies on.
A second decision-maker surfaces after something has been agreed.
Marketing consent is assumed, or buried in a checkbox nobody can evidence.
Attribution is a guess because nobody asked how they found you.
After
The record has fields the team can act on from day one.
Messages go to the channel and the hours the customer named.
Everyone who has to agree is known before anything is agreed.
Consent is explicit, separate from service messages, and timestamped.
Attribution comes from the customer rather than from a form default.
Process

How it works

Ask once, write properly, use everywhere.

Step 01

Ask at first contact

The agent collects the profile during the first real conversation, when the customer is already engaged, rather than sending a form later that nobody completes.

Step 02

Write it as fields

It maps every answer to a structured field on the customer record — channel, hours, decision-makers, constraint, consent — so downstream systems can act on it.

Step 03

Keep it current

It re-confirms preferences at natural moments and updates the record when something changes, so the profile does not quietly go stale.


Example

Example workflow

The customer who was contacted the way she asked.

Scenario: A new customer inquires on a Thursday. The agent captures that she prefers text over phone, that calls before 11:00 do not work because of shift patterns, that her partner has to be present for any decision over 2,000 dollars, that the work needs to be done before a family event on 18 May, and that she found the business through a neighbor rather than the ad campaign the form would have credited. She consents to service messages and declines marketing. Every subsequent message goes by text after eleven, the consultation is booked for an evening both partners can attend, and the May date drives the scheduling. Nothing about that required a person to remember it.

Consultation Intake & Qualification HubSpotSalesforcePipedriveKlaviyo AI Agent flow

Audience

Who can benefit

Anyone whose first contact currently collects a name.

✍️ Business owners

A thin record costs a little on every interaction for the life of the customer.

💼 Front-desk and reception teams

Preferences are learned by trial and error, then forgotten when staff change.

🧠 Sales teams

Knowing the decision-maker at first contact prevents most repeat meetings.

Marketing managers

Consent and attribution are only reliable when they are asked for directly.

🎯 Customer service teams

Contact preference is the difference between resolving and chasing.

📋 Operations managers

Structured fields are the only version of this that survives staff turnover.

Integrations

The customer record and everything reading from it.

HubSpot

Writes preferences, consent and decision-makers as properties on the contact record.

Salesforce

Maps each answer to a field so reports and automation can use it.

Pipedrive

Keeps the profile on the person record alongside the deal.

Klaviyo

Respects the channel and consent captured, rather than a blanket subscription.

Twilio

Uses the stated channel and hours for every subsequent message.

Gmail

Runs the conversation in the thread and records the address that is actually read.

Airtable

Holds the profile where a small team can query and update it easily.

Google Sheets

Keeps a simple structured record for teams without a CRM.

Applications

Best use cases

Where a real profile pays for itself.

Businesses whose staff turn over and take customer knowledge with them.
Service businesses where access, hours and channel preference govern scheduling.
Any decision involving more than one person in a household or a company.
Marketing consent that has to be evidenced rather than assumed.
Attribution that is currently guessed from form defaults.
Long relationships where a preference recorded once saves dozens of failed contacts.

Choosing

Which customer-record agent to use

A thin customer record is a tax paid on every message afterwards. This agent collects the profile once, at the only moment the customer is willing to give it.

Our pick for this

Use the AI New Customer Questionnaire Agent when your records are a name and a number

  • It collects during the first conversation, when completion rates are many times higher than a form sent later.
  • It captures preferred channel and hours, so subsequent messages reach the person.
  • It identifies other decision-makers before anything is agreed with half the household.
  • It takes marketing consent explicitly and timestamps it, separately from service messages.
  • It writes structured fields your systems can act on, not a paragraph in a notes box.
Choose something else if
  • AI Lead Qualification Agent When the problem is filtering leads rather than knowing your customers.
  • AI Needs Assessment Agent When you need to understand the requirement, not the person.
  • AI Pre-Appointment Questionnaire Agent When the gap is preparation for a booked appointment.

FAQ

FAQ

Fields, consent and keeping it current.

Run qualification if the problem is too many leads and not enough filtering. Run the customer questionnaire if the leads are fine and the problem is that you know nothing usable about the people who become customers.

An AI agent for new customer questionnaires collects a usable profile at first contact — preferred channel and hours, other decision-makers, the governing constraint, how they found you, and explicit marketing consent — and writes each answer as a structured field on the customer record.

Because almost nobody completes it. Response rates on a form sent after the conversation are a fraction of answers given during one, which is why the profile has to be collected while the customer is already engaged.

It separates service messages from marketing, asks for each explicitly, records the timestamp and the wording shown, and writes the result where your messaging tools read it — so nothing sends against a preference.

It asks the ones that change behavior later and skips the rest. A profile with five fields the team uses beats one with twenty nobody reads, and the agent is configured around what your systems actually act on.

It re-confirms at natural moments — a new booking, a long gap, a bounced message — and updates the record. A profile collected once and never revisited is stale within a year.

Yes. It writes to Airtable or a spreadsheet just as readily. The value is in the fields being structured, not in which system holds them.

It runs on Agentplace. Agentplace is an AI agent platform where the agent gets its own page, talks to your visitors there, and carries the request through to the end instead of handing it to a form. You can open this template and change any step before you publish it.


AI New Customer Questionnaire Agent

Capture a profile you can actually act on — how they want to be contacted, what constrains them, what they care about — not a name and a phone number. Open it in Agentplace and change any step before you publish.

Start from this template
Edit it — the agent is built from this briefBuild this agent