Measuring Results
How do you know if karmafarm.co is working? This guide covers multiple ways to measure your AI visibility and track leads from AI recommendations.Method 1: Track AI Traffic in Google Analytics
AI tools like ChatGPT, Claude, and Perplexity send traffic to websites when they recommend products. You can track this in GA4.Set Up an AI Traffic Channel
By default, GA4 hides AI traffic in the “Referral” or “Direct” channels. Create a custom channel to separate it:- In GA4, go to Admin → Data Display → Channel Groups
- Create a new channel group or edit the default
- Add a new channel called “AI Referral”
- Set the condition to match session source using this regex:
- Important: Drag your AI channel above the Referral channel. GA4 checks from top to bottom.
For a detailed walkthrough, see How to Track AI Traffic in GA4 by Orbit Media.
What to Expect
AI traffic is still small but growing fast:- ChatGPT drives ~78% of AI referral traffic
- Perplexity drives ~15%
- Claude users have the highest session value ($4.56/visit)
- AI visitors stay ~10 minutes per session on average
Limitations
Some AI traffic won’t be trackable:- ChatGPT’s mobile app often appears as “Direct” traffic
- Users who copy/paste URLs lose referrer data
- Some AI tools strip referrer headers
Method 2: Ask Users During Onboarding
The most reliable way to track AI-driven signups is to ask directly.Add a “How did you hear about us?” Step
During onboarding, add an optional question: “How did you discover [Product]?” Options:- ChatGPT / Claude / AI assistant
- Google search
- Twitter/X
- Friend or colleague
- Other: [text field]
Why This Works
- Captures attribution that analytics miss
- Users who come from AI are often happy to say so
- Gives you qualitative data on which AI tools drive signups
Implementation Tips
- Make it optional (don’t block signups)
- Keep options short (5-7 max)
- Include “AI assistant” as a clear option
- Track responses in your database for analysis
Companies like Writingmate.ai use this approach successfully in their onboarding flow.
Method 3: Customer Interviews
For deeper insights, ask new customers directly.Questions to Ask
- “When you were researching solutions, what tools did you use?”
- “Did you ask ChatGPT or another AI for recommendations?”
- “Where did you first hear about us?”
- “What made you choose us over alternatives?”
What You’ll Learn
- Which AI tools your audience actually uses
- What prompts lead to your product being recommended
- How AI recommendations compare to other channels
- Objections or concerns that came up
Method 4: Monitor AI Recommendations Directly
Periodically test whether AI tools recommend your product.Manual Testing
Ask AI tools questions your target audience would ask:- “What’s the best tool for [your category]?”
- “What are alternatives to [competitor]?”
- “[Problem you solve] - any recommendations?”
Automated Monitoring
Tools exist to automate this monitoring at scale. Search for “AI brand monitoring” or “LLM mention tracking” solutions.Connecting the Dots
Combine these methods for a complete picture:| Method | Measures | Reliability |
|---|---|---|
| GA4 AI Channel | Website visits from AI | Medium (some traffic hidden) |
| Onboarding Question | Signups attributed to AI | High (self-reported) |
| Customer Interviews | Qualitative insights | High (but small sample) |
| Direct AI Testing | Whether you’re recommended | High (but point-in-time) |
Leading vs Lagging Indicators
Leading indicators (track weekly):- Number of Reddit posts responded to
- Share of voice vs competitors
- Posting streak and consistency
- AI traffic in GA4
- “AI” responses in onboarding attribution
- Mention rate in direct AI testing
Setting Expectations
AI visibility builds over time. Expect:- Week 1-4: Building presence, minimal measurable impact
- Month 2-3: Starting to appear in some AI recommendations
- Month 4+: Consistent AI traffic and attribution