Conversion Rate Advantage: Do Discovered Labs and Growthx Both Deliver 2.4x Higher Conversions?

Updated January 20, 2026

If you've seen the stat that AI-sourced traffic converts 2.4x better than traditional organic search, you've probably asked: does this apply to every AI marketing tool, or just specific channels?

The answer determines where you invest your limited marketing budget. Ahrefs analyzed nearly 82,000 websites and found AI search visitors convert at 2.3x higher rates on average, while Webflow saw 6x higher conversion rates from ChatGPT traffic compared to traditional search. But these numbers specifically measure inbound traffic from AI answer engines like ChatGPT, Perplexity, and Claude, not outbound automation platforms.

I'm breaking down whether Discovered Labs' Answer Engine Optimization (AEO) and Growthx both deliver this conversion advantage, what drives the difference, and how to capture high-converting AI traffic for your B2B pipeline.

Understanding the 2.4x conversion advantage in AI search

The conversion advantage from AI traffic isn't universal to all AI marketing tools. It's a specific outcome of how buyers use AI search platforms to research vendors.

Ahrefs found that AI search traffic converts 2.3 times better than traditional organic search in their internal analysis, with AI platforms generating 12.1% of signups despite accounting for only 0.5% of overall traffic. The study examined traffic patterns using Ahrefs Web Analytics over a 30-day period across nearly 82,000 websites between May and June 2025.

Webflow reported similar results. ChatGPT traffic converts at 24%, which is 6x higher than Google's 4% non-brand search conversion rate. As of June 2025, 8% of Webflow's total new signups came from AI platforms, compared to just 2% in October 2024.

Here's the key distinction: these conversion advantages apply to traffic referred by AI answer engines, not traffic generated by outbound tools.

Answer Engine Optimization (AEO) is the practice of optimizing content so AI-powered search engines like ChatGPT, Perplexity, and Bing Copilot can directly cite your brand when users ask for vendor recommendations.

Generative Engine Optimization (GEO) describes strategies to influence how large language models retrieve, summarize, and present information in response to user queries, specifically addressing platforms that use generative AI to create conversational responses.

Why AI-sourced leads convert higher than traditional organic traffic

Three mechanisms drive the superior conversion rates of AI search traffic:

1. High intent and pre-qualification: Buyers who click through from AI search platforms arrive further along in their decision journey. Instead of generic keywords like "CRM software," they ask specific questions: "What's the best HIPAA-compliant CRM for a 50-person healthcare tech company with Salesforce integration?" AI search queries now average 23 words compared to Google's 4-word standard. The AI filters recommendations based on context before users click. By the time someone arrives from ChatGPT, they've been pre-qualified against their stated requirements.

2. Trust by proxy through AI endorsement: When an AI assistant recommends your product, it functions as a trusted advisor rather than a neutral directory. Most AI traffic comes directly from ChatGPT, suggesting platforms like ChatGPT aren't just research tools but trusted recommenders. Buyers treat AI recommendations like advice from a consultant who synthesized multiple sources on their behalf. Research from Responsive shows one in four B2B buyers now use GenAI more often than conventional search when researching suppliers.

3. Longer consideration before clicking: Traditional organic search involves rapid click behavior. Users scan a SERP, click results, bounce back, and try another link. AI search users spend time in conversation with the AI before clicking anything. They ask follow-up questions, request comparisons, and dig into specific features. Ahrefs observed that users from AI search click links 75% less than they do in traditional search. When buyers finally click through, it's a deliberate choice based on synthesized information, not exploratory browsing.

Discovered Labs vs Growthx: Comparing conversion mechanisms

The critical distinction: Discovered Labs and Growthx operate in fundamentally different channels with different buyer states.

Discovered Labs: Capturing inbound intent through AEO

We engineer B2B companies into the recommendation layer of AI assistants through Answer Engine Optimization services. We use proprietary technology and the CITABLE framework to ensure your brand gets cited when prospects actively ask ChatGPT, Perplexity, Claude, or Gemini for vendor recommendations.

The mechanism: Buyers initiate the conversation. They're actively researching solutions, comparing alternatives, and looking for expert guidance. When the AI cites your brand as a recommended solution with specific reasons why you're a good fit, that's an inbound lead with high intent.

Conversion advantage: This is where the 2.3x to 6x conversion multiplier lives. You're capturing demand that already exists, with AI endorsement, from buyers who've pre-qualified themselves through detailed questions.

Case study evidence: We helped a B2B SaaS company increase AI-referred trials from 550 to 2,300+ in four weeks, representing a 4x growth in high-intent inbound leads.

Growthx: Scaling outbound efficiency

Growthx generates highly targeted B2B leads using LinkedIn automation with ongoing work from Growth Experts, providing collaboration and advice on targeting, messaging, campaign strategy, and A/B testing to boost conversions.

The mechanism: Your team initiates the conversation. You're interrupting prospects who may or may not be actively looking for your solution. AI helps you target better and personalize at scale, but you're still operating in an outbound channel.

Conversion advantage: Outbound tools can improve targeting efficiency and response rates. However, this is improving the effectiveness of an outbound channel, not capturing the high-intent inbound traffic that drives the documented 2.3x to 6x advantage.

Side-by-side comparison

The documented 2.3x to 6x conversion advantage lives in the inbound column.

Both approaches deliver value for different goals. If prospects are already using AI to research vendors in your category and you're not being cited, you're losing high-intent pipeline before your sales team ever gets a chance.

How to capture high-converting AI traffic with the CITABLE framework

To capture the conversion advantage from inbound AI search, you need to get cited by AI assistants. Traditional SEO won't get you there.

Only 12% of URLs cited by ChatGPT, Gemini, and Copilot appear in Google's top 10 SERP positions for the same query, according to Ahrefs' analysis. Perplexity shows slightly better alignment at 28%, but the fundamental insight holds: ranking in Google doesn't guarantee AI citations.

A comprehensive study by Search Atlas analyzing over 18,000 queries found that nearly 9 out of 10 AI-cited sources are outside what Google deems most relevant.

AI models look for different signals than traditional search algorithms. This is where the CITABLE framework comes in.

The CITABLE framework explained

The CITABLE framework structures content specifically for LLM retrieval:

Clear entity and structure: AI models need to immediately understand what entity you are and what you do. Every piece of content should open with a Bottom Line Up Front statement that clearly identifies your company, category, and core capability.

Intent architecture: Structure content to answer the primary question plus the 3-5 follow-up questions buyers ask next. AI models prefer sources that comprehensively address a topic.

Third-party validation: AI models trust external validation more than your marketing claims. Mentions on Reddit, G2 reviews, and news coverage increase citation likelihood. This is why we offer Reddit marketing services as part of our AEO approach.

Answer grounding: Every claim needs to be verifiable. AI models skip content with unsubstantiated assertions, especially in regulated industries like healthcare and fintech.

Block-structured for RAG: Structure content in discrete 200-400 word sections with clear headings, bulleted lists, comparison tables, and FAQ sections that AI can extract and quote directly.

Latest and consistent: AI models prefer recent information and consistent facts across sources. If your pricing differs across pages, the AI may skip citing you entirely.

Entity graph and schema: Use structured data markup (Organization, Product, FAQ schemas) and explicitly state relationships. "Company X integrates with Salesforce, HubSpot, and Zendesk" beats vague "integrates with leading CRM platforms."

The CITABLE framework only works with consistent content production. Our packages start at 20 pieces per month and can reach 2-3 pieces daily for larger clients. This volume matters because AI models continuously update their knowledge bases, with initial citations appearing within 4-8 weeks of publishing optimized content.

Measuring the impact: AEO metrics that matter for pipeline

If you're investing in AEO to capture the conversion advantage, you need to measure whether it's working. Traditional SEO metrics like domain authority and keyword rankings don't tell you anything about AI citations.

Three core AEO metrics

Citation rate: The proportion of queries where AI engines cite your domain. Track it across ChatGPT, Perplexity, Claude, Google AI Overviews, and Microsoft Copilot for 50-100 buyer-intent queries in your category.

Share of voice in AI answers: How often your brand is mentioned inside AI search results compared to competitors. This is the ultimate competitive metric. If ChatGPT recommends three competitors but never mentions you, your AI Share of Voice is 0% for that query.

AI-sourced pipeline contribution: Connect AI visibility to revenue by tracking AI-sourced traffic and conversions separately from traditional organic search. Use UTM parameters, referral tracking, and CRM attribution to identify which opportunities came from prospects who researched using AI platforms.

Early indicators can appear within 2-4 weeks, while substantial visibility improvements typically take 3-6 months. Unlike traditional SEO which can take 6-9 months for meaningful movement, AEO's faster feedback loop makes results more predictable.

The choice depends on your pipeline problem

For data-driven marketing leaders evaluating where to invest, the question isn't "Should I use AI?" The question is "Where are my buyers using AI, and am I visible there?"

If buyers are using ChatGPT, Perplexity, and Claude to research vendors and you're not being cited, you're losing pipeline before your sales team gets a chance to compete. That's the problem we solve through AEO services, using the CITABLE framework to ensure your brand becomes the answer AI systems recommend to high-intent buyers.

Unlike agencies that lock you into 12-month contracts, we offer month-to-month terms so you can evaluate ROI based on measurable citation rate improvements and AI-referred MQLs.

Request an AI Visibility Audit to see where you're currently cited across AI platforms compared to competitors, or explore our approach to comparing AEO agencies to find the right partner for your pipeline goals.

FAQ

What is the difference between AEO and GEO?
Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) both describe optimizing content for AI-powered search platforms. GEO specifically emphasizes optimization for generative AI systems like ChatGPT and Claude.

Does the 2.4x conversion rate apply to all AI marketing tools?
No, the 2.3x to 6x conversion advantage applies specifically to inbound traffic from AI search platforms, not to leads generated through outbound automation tools.

How long does it take to see results from AEO?
Initial AI citations typically appear within 4-8 weeks of publishing optimized content. Perplexity shows results fastest at 1-2 weeks, followed by Google AI Overviews at 2-4 weeks.

Can traditional SEO rankings help me get cited by AI?
Only 12% of URLs cited by AI assistants appear in Google's top 10 search results for the same query. Traditional SEO optimization alone won't guarantee AI citations.

What metrics should I track for AEO success?
Track citation rate (percentage of buyer queries where AI cites your brand), AI Share of Voice (your citations vs competitors), and AI-sourced pipeline contribution (revenue attributed to AI platform referrals).

Key terms glossary

Answer Engine Optimization (AEO): The practice of optimizing content so AI-powered search engines like ChatGPT and Perplexity cite your brand when users ask for vendor recommendations.

Citation rate: The percentage of AI-generated answers that mention your brand or link to your content as a source when users ask relevant buyer-intent questions.

CITABLE framework: Our proprietary methodology for structuring content to maximize AI citation likelihood through Clear entity structure, Intent architecture, Third-party validation, Answer grounding, Block structure, Latest information, and Entity relationships.

Share of voice (AI SOV): The percentage of AI-generated answers that mention your brand compared to competitors across a defined set of buyer-intent queries.