The Challenge
Since 2022, Graphite and Webflow have partnered to drive SEO growth, achieving 3M nonbrand clicks and a 2.5x ROI in 2024.
In Q1 2025, both teams saw an exciting opportunity to take advantage of a new channel, LLMs, to continue driving conversions and revenue through AEO.
Between January and July 2025, Graphite clients experienced increases in LLM traffic ranging from 100 to 300% on average, while Webflow saw 4% of signups coming from LLMs.
AEO was still a black box for marketers, so Webflow and Graphite set out to build an AEO roadmap of experiments to identify high-impact strategies that they could repeat and scale to win in AI search.
The Solution
What Webflow and Graphite did know was that LLM answers were heavily influenced by citations and that there were two ways to appear in the list of citations in AI chat - onsite (i.e. Webflow’s website) and offsite (i.e. organic influencer mentions, YouTube, and Reddit).
Graphite’s AI team analyzed citations at scale and found that Reddit was a top-five source for AEO questions, appearing in 10% of ChatGPT citations. YouTube was also a major source, cited in 5% of ChatGPT responses and 32% of Perplexity responses.
The next step was to identify what onsite and offsite content the Webflow team could create and/or optimize to increase both share of voice and conversions from LLMs.
Onsite Content
- Webflow’s template pages (highest converting page type)
- Webflow’s blog pages
Offsite Content
- Affiliate publications
- Webflow’s Youtube
- Webflow’s Reddit
- Influencer YouTube Channels
The Results
Webflow was able to drive:
- 94% share of voice* growth from LLMs (increase from 33% to 64%)
- 2x the amount of sign-ups* coming from LLMs (increase from 4% to 8%)
- 24% Signup CVR (vs. 4% for non-brand SEO)
*Share of Voice (SoV) is the main metric Graphite uses to track visibility in Answer Engines. It’s calculated by analyzing all the answers retrieved and checking for exact matches with terms added to Graphite’s internal tooling.
*A sign-up refers to when a user signs up for a free Webflow account.
The Strategy
The strategies that drove real results:
Answering Long Tail Questions
To boost ChatGPT recommendations of Webflow as the top CMS for popular app integrations, the teams published a blog page answering AEO-style questions (more specific, long tail queries). Instead of only targeting the head question ‘what is the best CMS?’, the team answered 10 long tail questions structured to include the type of team and the tool to be integrated.
Example:
- Head question + [teams] + [tool]
- [What is the best CMS] for [in-house teams] that use [ReviewsJet?]
Result:
- Before: 38% SoV
- After: 100% SoV
After three weeks of publishing, SoV increased for 70% of questions.
AEO Optimization of Template Pages
Templates are one of Webflow’s highest traffic-driving page types, so optimizing them for LLMs was a clear next step. Both teams conducted AI question-and-answer research relevant to template pages and created a list of 1.5k pages to optimize. This effort required adding unique above-the-fold copy optimized for answer engines and customized to the specific user needs. Every optimized copy included a head question, branded terms, target user, and pain point or solution.
For example, on the Real Estate Website Templates page, the following elements were added:
- Head question = real estate website templates
- Branded money term = in Webflow
- Specific target user = agents and realty firms
- Solution to specific pain point = help connect potential buyers with available listings
Showcase prime properties with [real estate website templates in Webflow], [ideal for agents and realty firms]. Featuring property tours, advanced search filters, and contact forms, these templates [help connect potential buyers with available listings].
Previously, these pages had no optimized copy above the fold outside of the H1.
Results: This change increased LLM signups by 485% QoQ
- Q1 168 signups
- Q2 983 signups
Transparent, Value-focused Reddit Strategy
Graphite and Webflow’s cross-functional team launched a Reddit optimization strategy based on transparent, value-focused communication.
They analyzed citations across 100 priority head, midtail, and longtail queries and built a monitoring workflow to identify relevant threads and comments.
Then they engaged in those threads with non-promotional, helpful responses aligned to user needs. This created more opportunities for Webflow to be referenced in organic community conversations.
The process workflow is as follows:
- Identify threads
- Comment Suggestion
- Track Sentiment
- Review Contribution Type
- Comment
- Tracking
Results:
- 98% of Webflow engagement is met with a positive or neutral response
- r/Webflow grew substantially YoY
- Views: +135%
- Members: +12%
- Published posts + comments: +145%
Table of Contents for Answer Engine Visibility
A table of contents was added to help answer engines identify and serve the most relevant section quickly, enhancing chances of being selected for direct answers. The Table of Contents improves navigability, clarifies topical hierarchy, and aligns with search intent.
For example, in the Landing pages vs. websites blog post, the table of contents was updated to outline the following structure:
Table of contents
- Websites: An overview
- Landing pages explained
- The key differences between websites and landing pages
- 3 reasons to differentiate between websites and landing pages
- When do you need a website?
- When do you need a landing page?
- 3 examples of effective websites and landing pages
- Landing page or full website? Choose wisely
In this specific example, Webflow is able to target the head question (landing pages vs websites), but the LLM is able to continue the conversation with long-tail queries, such as when do you need a website? or when do you need a landing page?. It enhances the conversational aspect of the AI chat while also aiding the LLM in building a more structured answer. This increases the likelihood that the specific section answering the user’s query is pulled into AI search results.
Results:
- 23% growth in clicks in over 4 weeks after implementation (increase from an average of 191 to 220 with control-adjusted uplift).
- 60% growth in AI visits* in over 4 weeks after implementation (increase from an average of 119 to 127 with control-adjusted uplift).
* The 60% comes from comparing the Table of Contents improvement relative to the drop in the control group, which is why the uplift is much higher than the raw 119 to 127 change.
.png)
Headers as Questions
The teams reformatted blog page headers into question-based phrasing to help answer engines match content with real user intent.
For example, in the 12 useful AI design tools for web designers blog, all headers were updated into the following questions:
- What are AI design tools and how do they work?
- What are the advantages of using AI-powered design tools?
- What are the limitations of AI in web design?
- Which AI tools are most useful for web designers?
By phrasing headers as questions users commonly ask in AI chat, the model can easily identify which section holds the answer. This increases the probability that Webflow’s content will be cited in multiple parts of an AI conversation or across multiple different conversations on the same topic.
Results: 58% uplift after adjusting for control in AI visits in over 4 weeks after implementation (increase from an average of 41 to 70).
Methodology Overview
To test and validate results for the last two initiatives (Table of Contents and Headers as Questions), we implemented a T-test methodology with test and control groups.
To create the pre/post test groups, the teams selected 10 test URLs and paired them with a 10 URL control group with similar traffic and impressions. After applying changes to the test group, they measured performance over a five-week period.
P Value:
- Headers as Questions - 0.001
- ToC - 0.002
The T-test incorporated:
- Differences in means
- Variance within each group
- Sample size
This allowed us to account for:
- Weekly fluctuation
- Noise
- Seasonality (insofar as it appears as variance)
To calculate the pre and post-test averages, the standard experiment method was used:
- Average of the pre-implementation weeks
- Average of the post-implementation weeks
- Calculate the % change between averages
- Adjust the change against the control group to isolate the real uplift
This method avoids volatility from single high/low weeks and provides the experiment-level impact.
As seen in the results above, both tests had significant data after week 4.
From SEO to AEO
The ultimate goal was to create and optimize content tailored for both traditional SEO and AI answers. To do this, Webflow and Graphite made sure every SEO topic answered the matching AEO questions.
This content foundation would establish Webflow as the authoritative source that AI systems trust and recommend. Every piece of content should serve two purposes: answering user questions comprehensively while being structured for AI extraction and citation.
By the Numbers
Conclusion
- LLMs can drive brand visibility and increase conversions.
- AI Chat users can be higher intent (6x conversion rate of SEO) due to longtail user behavior / conversational element.
- SEO and AEO have a lot of similarities - good, useful content still wins.
