How GEO helped Webflow double its sign-ups from LLMs

Webflow doubled the share of its sign-ups coming from LLMs, from 4% to 8%, and grew its LLM share of voice from 33% to 64%. It got there with a run of small, measured experiments on its own pages and on the third-party sources AI engines already cite, including Reddit and YouTube.

The challenge

Webflow already had a strong SEO engine. In 2024 its organic program delivered 3M non-brand clicks and a 2.5x ROI. In Q1 2025 the team saw a new channel forming: people asking ChatGPT, Perplexity and other answer engines which website builder or CMS to use.

At the start, 4% of Webflow sign-ups came from LLMs. The problem was that nobody knew which levers actually moved that number. AI search was still a black box for marketers, so the goal was not a single campaign. It was a roadmap of experiments that could show what works, then repeat and scale it.

What they changed

The starting insight was simple. LLM answers lean heavily on citations, and there are two ways into that citation list: your own site, and the offsite places AI trusts. Citation analysis at scale showed Reddit was a top-five source for these questions, appearing in 10% of ChatGPT citations. YouTube was cited in 5% of ChatGPT responses and 32% of Perplexity responses.

So the work split into onsite and offsite tracks.

Long-tail answer pages. Instead of only chasing "what is the best CMS?", the team published a page answering 10 long-tail questions that combined a team type and a tool to integrate, such as the best CMS for in-house teams using a specific app. Share of voice on one example question went from 38% to 100%, and within three weeks of publishing it rose for 70% of the questions.

Answer-ready template pages. Templates are one of Webflow's highest-converting page types, yet they had no optimized copy above the fold beyond the H1. The team researched the AI questions behind these pages and picked 1.5k pages to optimize. Each got unique above-the-fold copy built from four parts: the head question, a branded term, the specific target user, and the pain point it solves.

Helpful, non-promotional Reddit. The team analyzed citations across 100 priority queries, built a workflow to find relevant threads, and replied with useful answers aligned to what users needed, while tracking sentiment.

Structure AI can lift. Blog posts got clearer tables of contents, and headers were rewritten as the questions people actually type into AI chat. Both changes were tested against matched control groups of 10 URLs each.

The results

• LLM share of voice grew 94%, from 33% to 64%.
• Sign-ups from LLMs doubled, from 4% to 8% of all sign-ups.
• LLM visitors converted to sign-up at 24%, versus 4% for non-brand SEO.
• Template page copy lifted LLM sign-ups 485% quarter over quarter, from 168 in Q1 to 983 in Q2.
• 98% of Webflow's Reddit engagement drew a positive or neutral response. r/Webflow views rose 135% year over year.
• Tables of contents drove a 60% control-adjusted lift in AI visits over four weeks. Question-style headers drove a 58% lift.

What you can copy

1. Find your citation sources first. Before writing anything, learn which domains AI engines cite for your category. For Webflow that meant Reddit and YouTube, not just its own blog.
2. Answer the long tail, not only the head term. Pair your category question with a specific audience and use case. Narrow questions are easier to win outright.
3. Put the answer above the fold on money pages. A short paragraph naming the query, your brand, the user and the outcome gives AI a clean passage to quote.
4. Write headers as questions. It helps the model match a section to a prompt and cite you across more of the conversation.
5. Show up where the conversation already is. Helpful replies in the threads AI quotes beat promotional posts.
6. Test against a control. Pair changed pages with similar unchanged ones so you can separate real lift from noise.

SEO and GEO overlap heavily. Good, useful content still wins, as long as AI can find the answer.