Using Kayse AI Data to Improve Ad Platform Performance

If your leads come from Meta, Google Ads, or another ad platform, you can use Kayse AI outcomes to help those platforms learn which leads are worth finding again.

The key is to send lead outcomes back through your CRM so your ad platform gets better feedback over time.

Why This Helps

When your ad platform only knows that a lead filled out a form, it has very little context. It does not know whether that lead was a good fit, a bad fit, or someone who never engaged.

Kayse AI adds that missing layer by tracking what happened after outreach:

• Was the lead disqualified?
• Did the lead convert?
• Was the interaction successful?
• Did the case move to a meaningful status?

That feedback can then be sent back to your ad platform so it can optimize for better leads.

The Supported Workflow

The correct setup is:

Ad Platform → CRM → Kayse AI → CRM → Ad Platform

Here is what that means in practice:

1. A lead comes in from Meta, Google Ads, or another ad platform.
2. The lead is stored in your CRM, such as GoHighLevel, Law Ruler, SmartAdvocate, or another system.
3. Your CRM sends that lead to Kayse AI for calls, messages, or both.
4. Kayse AI records the outcome and sends it back through webhooks or synced status changes.
5. Your CRM, Zapier, or another integration sends the final conversion signal back to the ad platform.

What Not to Do

Which Kayse Events Are Useful for Ad Optimization

The most common signals are webhook events and case status updates.

Negative vs. Positive Feedback

For disqualified leads

Use these when you want the ad platform to stop finding similar leads:

• DQ Message Intent
• Disqualified Call Outcome

These can be sent to systems like Meta Conversions API or Google Ads as negative or low-value conversion signals, depending on how your tracking is configured.

For qualified or converted leads

Use these when you want the ad platform to find more leads like the ones that worked:

• Converted
• Successful

These are your strongest positive signals because they tell the ad platform what a good lead looks like after Kayse AI outreach.

Using Status Changes Instead of Webhooks

If your team does not want to build around webhooks right away, you can also base feedback on case status changes.

For example:

• Won or Qualified can map to a positive signal
• Lost or Disqualified can map to a negative signal

This is simpler, but it is usually less precise than webhooks because it depends on your CRM sync and your internal status process.

Step-by-Step Setup

1. Set up webhooks in Kayse AI

1. Go to Settings → Webhooks in Kayse AI.
2. Click Add Webhook.
3. Enter the destination URL for your CRM, Zapier, or custom endpoint.
4. Choose the events you want to send, such as:
   • DQ Message Intent
   • Disqualified
   • Converted
   • Successful
5. Add security if needed, such as API key, bearer token, or HMAC.
6. Save and test the webhook.

2. Map Kayse events inside your CRM or Zapier

When a webhook arrives, your receiving system should:

• Store the event type
• Store the timestamp
• Update the lead or case record
• Decide whether the event is a positive or negative signal

Examples:

• DQ Message Intent → mark lead as disqualified
• Converted → mark lead as qualified or converted
• Successful → mark lead as engaged or successful

3. Send the final signal to your ad platform

Once your CRM has the Kayse outcome, send that feedback to your ad platform:

• Meta: usually through Conversions API (CAPI)
• Google Ads: usually through offline conversion imports or the Google Ads API

At that point, your ad platform can use the signal to improve future ad delivery.

4. Test the full loop

Before going live, test the complete path:

1. Ad click
2. Lead enters CRM
3. Lead is sent to Kayse AI
4. Kayse AI triggers the webhook or status change
5. CRM or Zapier receives it
6. CRM sends the right signal to Meta or Google

If one step is missing, the optimization loop breaks.

How Kayse AI Fits Into This Workflow

Kayse AI supports this loop in a few different ways:

Voice AI

Voice AI can:

• Call leads from a list
• Answer inbound calls
• Collect information during calls
• Transfer calls when needed
• Run post-call analysis
• Record outcomes like successful, disqualified, or converted

AI Messaging

AI Messaging can:

• Reply to leads across SMS, email, and portal messaging
• Track message engagement
• Trigger webhook events based on intent
• Flag disqualifying responses that should feed back into ad optimization

Webhooks

Webhooks make the connection possible by sending Kayse events to your CRM or middleware in real time.

Key Reminders

• Keep the workflow as Ad Platform → CRM → Kayse AI → CRM → Ad Platform
• Do not use Kayse AI as a replacement for your CRM
• Use DQ outcomes as negative feedback
• Use Converted and Successful outcomes as positive feedback
• Status changes can work, but webhooks are usually more precise
• Test the full loop before relying on it for campaign optimization

Related Docs

• Webhooks & Enrichment
• Webhooks API Reference
• Integrations Overview
• AI Features Overview

If you need help choosing which events to send first, start with Disqualified, Converted, and Successful. Those usually give the clearest feedback loop with the least setup complexity.