This article explains how to automatically add new leads to FirstQuadrant based on their behavior on your website. There are three common ways new leads enter your pipeline:
  1. Website form submissions
  2. Self-serve product signups
  3. Demo bookings through scheduling tools like Calendly or cal.com
We’ll walk through how to connect each of these to FirstQuadrant in detail.

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1. Website form submissions

If someone fills out a form on your site (e.g. “Contact Us” or “Get a demo”), you can use FirstQuadrant’s webhook integration to automatically import their data.

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How to set it up

  1. Go to Imports in the FirstQuadrant sidebar.
  2. Click New Import and select Webhook/API.
  3. A new webhook URL will be generated. Copy this URL.
  4. Configure your form handler (e.g. Webflow, Typeform, custom backend) to send a POST request to this URL.
  5. The payload should be a JSON object that includes at least the contact’s email. Example:
{
  "contact": {
    "email": "[email protected]"
  }
}
  1. You can also include additional optional fields:
    • note (free-text): e.g. “Filled out website form requesting a demo and said ….”
    • company details: name, domain, location
    • employment: title, job level, etc.
All fields will be enriched by FirstQuadrant where applicable.
Tip: Use the note field to give the AI extra context. For example: “Signed up via contact form. Please follow up with demo scheduling link.”
More on Webhooks: For a complete breakdown of how to send data to FirstQuadrant using webhooks—including supported fields, advanced payload formats, authentication, and retry behavior—refer to our dedicated Webhook Import Documentation.

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2. Self-serve signups

If your product allows users to sign up and onboard without human intervention, you can treat these users the same as website form submissions:

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How to set it up

  1. Create a webhook import under Imports.
  2. Send the same basic JSON payload when a signup is created.
  3. Include a note that reflects their signup behavior. For example:
    • “Signed up for self-serve onboarding”
    • “Signed up but dropped off at step 3”
Providing a note gives the AI important context about what just happened and what should happen next. For example, you could write something like: “Signed up via self-serve, dropped off at step 3 of onboarding.” This allows FirstQuadrant to adapt its actions accordingly—whether that means sending a follow-up email, offering help, or triggering a task. You can resend the webhook multiple times with updated notes if the same contact takes new actions (e.g., progresses further in onboarding).
Tip: You don’t need to build complex workflows. Just describe what happened in plain language, and the AI will figure out the next best steps on its own.

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3. Demo bookings via Calendly, cal.com, or similar

If users book a demo directly through a scheduling link on your website, you can use Zapier to automatically add those contacts to FirstQuadrant.

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How to set it up in Zapier

  1. Go to Zapier and create a new Zap.
  2. Trigger:
    • App: Calendly (or your preferred tool)
    • Event: Invitee Created
  3. Action:
    • App: FirstQuadrant
    • Event: Create Contact
  4. Map at least the email field.
  5. Optionally, add a note: “Booked demo via website scheduling link”
Note: Even without a note, FirstQuadrant can infer context from the calendar integration if the event shows up on your calendar.

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What happens after import: qualification and next steps

Once a contact is successfully imported—whether from a form, a self-serve signup, or a demo booking—FirstQuadrant automatically plans the next steps. This involves determining whether to engage, how to engage, and when. To control and customize this behavior, there are two primary strategies for qualifying and acting on inbound leads:

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Option A: Pre-import qualification

This approach allows you to define upfront rules that filter out low-quality or irrelevant contacts before they are ever added to FirstQuadrant. You set these rules in the Import Settings for each webhook or file upload. There are two layers of filtering available:
  1. Basic filters (checkbox toggles):
    • Company website must be available
    • Email address must be verified
    • Must be a professional (non-free) email
    • Skip importing existing contacts
  2. Qualification questions: You can also ask specific questions to qualify leads more rigorously. For example:
    • Is this company in the software industry?
    • Does this person have a senior-level title?
    These questions work by querying perplexities AI search and can be used to determine whether a lead should be allowed into your workspace. Only leads that pass all criteria will be imported and acted upon by the AI.
If a contact does not meet all criteria, they are ignored completely. This is ideal when you want tight control over what enters your pipeline or want to avoid using up AI credits on unqualified leads.
Keep in mind: Disqualified contacts are never visible in FirstQuadrant. The system does not track or process them. You can check out the qualified/disqualified contacts in the import detailed view, however.
Need help configuring imports? Visit our detailed Import Helpdesk Articles to learn more about the import and qualification process.

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Option B: Post-import qualification

This approach gives you maximum flexibility: you allow all contacts to enter FirstQuadrant without applying any qualification criteria in the import settings. Instead, you enrich and segment the leads after they’re imported using AI-enriched properties and fine-tuning rules.
Important: In this setup, you should leave the qualification section in the import settings blank. All leads will be imported as-is, and qualification will happen entirely through enriched properties and AI-based logic.

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Step-by-step example

Let’s say you want to take different actions based on the company size of the lead—for example, prioritize enterprise leads over small businesses. Here’s how you’d set that up using properties and fine-tuning rules, entirely after the import happens:
  1. Create a custom property
    • Navigate to Settings > Properties
    • Click New Property
    • Choose the Company record type (since headcount is a company-level attribute)
    • Set the property type to Number
    • Name the property (e.g., Company Headcount or Employees)
    • Enable AI enrichment and select Perplexity as the data source Once saved, FirstQuadrant will automatically enrich this property by pulling the company’s headcount from trusted sources via Perplexity, typically within a few seconds after the contact is imported.
Need help creating properties? Learn how to create and configure custom properties, including enabling enrichment with AI and linking to contact or company records in our Properties Help Guide.
  1. Create a fine-tuning rule to act on that property
    • Go to Settings > Fine-tuning
    • Click New Rule and choose General Rule
    • In the “Applies to” section, select only the relevant import segment, such as your specific webhook-based import or form-based signup feed. This ensures the rule only applies to leads coming through that import.
    • In the instruction text, describe what should happen based on the company headcount. For example: 
      When the company has more than 500 employees, send them an email with a direct demo scheduling link immediately.
When the company has less than 500 employees, send them a message offering support during the self-serve setup.
This setup allows FirstQuadrant to interpret real company context and determine the best next step for each lead. You don’t need to pre-filter anything. Every lead comes in, but how FirstQuadrant responds varies based on AI-enriched attributes. New to fine-tuning rules? Learn how to write clear, context-based rules to guide the AI’s behavior in our Fine-Tuning Guide.
Pro tip: This method is especially powerful when your lead pool is diverse. Let the AI sort and adapt the messaging based on the data it enriches. You can also continue layering in additional rules over time as you refine your workflows.
New to fine-tuning rules? Learn how to write clear, context-based rules to guide the AI’s behavior in our Fine-Tuning Guide.
You can combine this with basic import filters (Option A) if you want to pre-gate obviously unqualified leads (e.g., no professional email, no domain), and then use these enriched rules to personalize the response after that.