The Shift Has Already Begun: How AI Is Redefining User Acquisition

Last updated
June 26, 2025
The Shift Has Already Begun: How AI Is Redefining User Acquisition
Table of Content

How AI Is Redefining User Acquisition

AI search is no longer a future trend.
It's already here, and it's quietly transforming how companies acquire users.

Large language models (LLMs) and AI-driven search would change the rules of online discovery.

Forward-thinking companies are already seeing measurable and accelerating results from AI-based user acquisition.

Here are three standout examples: Vercel, Webflow, and Tally, that prove the shift isn’t on the horizon. It’s already underway.

🚀 Vercel: From 1% to 10% in Just Six Months

In December 2024, only 1% of new sign-ups to Vercel came from AI-driven sources like ChatGPT.

By May 2025, that number had climbed to 4.8%. Just one month later, in June 2025, it surged to 10%.

That’s not a blip. That’s exponential growth in a core acquisition channel, without paid ads, without SEO games.

This shows what happens when a product becomes the best answer to the right AI prompt.

Balancing traditional SEO and LLM SEO according with Kevin Corbett (Software Engineer, Vercel and Malte Ubl (CTO, Vercel)

Source →

🌐 Webflow: 4x Growth in AI Sign-Ups

Webflow has also seen a dramatic shift. In October 2024, just 2% of new users came from AI channels. Fast forward to June 2025, and that number is now 8%.

They didn’t stumble into this success, they optimized for it.

Through smart adaptation of their content strategy for LLM-based discovery, Webflow made itself easier for AI systems to recommend.

Source →

📋 Tally: AI Becomes the #1 Channel

Tally, the popular  no-code form builder, has gone even further. According to co-founder Marie Martens, AI search is now Tally’s single biggest acquisition channel, surpassing every other source, including SEO and social.

"AI search became our biggest acquisition channel ChatGPT Perplexity  co are now driving the majority of our new signups" (cit. Marie Martens Co-founder di Tally)

Tally's user registration from AI Searc

Tally’s success highlights what’s possible when your product is discoverable, trustworthy, and relevant enough to be surfaced consistently in LLM responses.

Source →

Why This Matters

These are not isolated success stories. They are early signs of a major shift: AI is becoming the new front door to the internet.

More users are asking tools like ChatGPT for product recommendations. And LLMs are responding with answers that shape real decisions.

If your product isn’t optimized to be found and recommended by AI, you're missing out on one of the fastest-growing acquisition channels.

Now is the time to make your product LLM-discoverable.

At AI Finds You, We're Helping You Catch the Wave

We built AI Finds You for this moment.

Our platform helps make your product more discoverable and recommendable by AI agents and LLMs—ensuring you're part of the answers users are already asking for.

The shift is happening. Vercel, Webflow, and Tally are riding it.

Are you?

Key Related Questions
How can I optimize for GEO?

GEO requires a shift in strategy from traditional SEO. Instead of focusing solely on how search engines crawl and rank pages, Generative Engine Optimization (GEO) focuses on how Large Language Models (LLMs) like ChatGPT, Gemini, or Claude understand, retrieve, and reproduce information in their answers.

To make this easier to implement, we can apply the three classic pillars of SEO—Semantic, Technical, and Authority/Links—reinterpreted through the lens of GEO.

1. Semantic Optimization (Text & Content Layer)

This refers to the language, structure, and clarity of the content itself—what you write and how you write it.

🧠 GEO Tactics:

  • Conversational Clarity: Use natural, question-answer formats that match how users interact with LLMs.
  • RAG-Friendly Layouts: Structure content so that models using Retrieval-Augmented Generation can easily locate and summarize it.
  • Authoritative Tone: Avoid vague or overly promotional language—LLMs favor clear, factual statements.
  • Structured Headers: Use H2s and H3s to define sections. LLMs rely heavily on this hierarchy for context segmentation.

🔍 Compared to Traditional SEO:

  • Similarity: Both value clarity, keyword-rich subheadings, and topic coverage.
  • Difference: GEO prioritizes contextual relevance and direct answers over keyword stuffing or search volume targeting.

2. Technical Optimization

This pillar deals with how your content is coded, delivered, and accessed—not just by humans, but by AI models too.

⚙️ GEO Tactics:

  • Structured Data (Schema Markup): Clearly define entities and relationships so LLMs can understand context.
  • Crawlability & Load Time: Still important, especially when LLMs like ChatGPT or Perplexity use live browsing.
  • Model-Friendly Formats: Prefer clean HTML, markdown, or plaintext—avoid heavy JavaScript that can block content visibility.
  • Zero-Click Readiness: Craft summaries and paragraphs that can stand alone, knowing the user may never visit your site.

🔍 Compared to Traditional SEO:

  • Similarity: Both benefit from clean code, fast performance, and schema markup.
  • Difference: GEO focuses on how readable and usable your content is for AI, not just browsers.

3. Authority & Link Strategy

This refers to the signals of trust that tell a model—or a search engine—that your content is reliable.

🔗 GEO Tactics:

  • Credible Sources: Reference reliable, third-party data (.gov, .edu, research papers). LLMs often echo content from trusted domains.
  • Internal Linking: Connect related content pieces to help LLMs understand topic depth and relationships.
  • Brand Mentions: Even unlinked brand citations across the web may boost your perceived credibility in LLMs’ training and inference models.

🔍 Compared to Traditional SEO:

  • Similarity: Both reward strong domain reputation and high-quality references.
  • Difference: GEO may rely more on accuracy and perceived authority across training data than on backlink volume or anchor text.

What is AI Search Optimization and why is it important?

AI Search Optimization refers to the practice of structuring, formatting, and presenting digital content to ensure it is surfaced by AI systems—particularly large language models (LLMs)—in response to user queries.Choosing a clear, unified name for this emerging field is crucial because it shapes professional standards, guides tool development, informs marketing strategies, and fosters a cohesive community of practice. Without a consistent term, the industry risks fragmentation and inefficiency, much like early digital marketing faced before "SEO" was widely adopted.

How is GEO different from SEO?

GEO (Generative Engine Optimization) is not a rebrand of SEO—it’s a response to an entirely new environment. SEO optimizes for bots that crawl, index, and rank. GEO optimizes for large language models (LLMs) that read, learn, and generate human-like answers.

While SEO is built around keywords and backlinks, GEO is about semantic clarity, contextual authority, and conversational structuring. You're not trying to please an algorithm—you’re helping an AI understand and echo your ideas accurately in its responses. It's not just about being found—it's about being spoken for.