Buyers are asking AI assistants to help research products, compare vendors, and make purchasing decisions.
Users ask AI everything from product recommendations to internal research questions. Whether marketers realize it or not, LLMs are already part of the buying process.
When an AI assistant becomes part of the buyer’s research process, there’s an interesting opportunity: give visitors a way to explore your product through a pre-written prompt. You can frame the question, highlight a relevant use case, and let the AI explain the offer.
Most marketers pour energy into CTAs that nudge visitors down the funnel, yet rarely test what happens when a CTA opens an AI conversation instead.
That opens up a different kind of experiment: can you influence how an AI assistant explains your product and make the buying experience more useful?
This blog shares insights from Casey Hill (CMO of DoWhatWorks), looking at how companies like Super, Birdy, and WPBeginner have experimented with LLM-briefing CTAs, what the early results suggest, and how to test the tactic yourself.
TL;DR
- LLM briefing CTAs are links that open an AI assistant with a pre-written prompt about a brand, product, or specific use case.
- Companies including Super and Birdy have tested persona-specific prompts that help buyers explore product benefits through ChatGPT and other AI assistants.
- These prompts can influence an answer within the user’s conversation. They don’t train the underlying model or guarantee that the assistant will remember or recommend the brand later.
- Prosperity Media reported a 950% year-over-year increase in LLM referral traffic during its experiments, but its founder couldn’t attribute the increase specifically to the briefing CTAs.
- Start by testing a few prompts in secondary CTA locations. Track outbound clicks, engagement, AI referrals, and downstream conversions before expanding the experiment.
Table of contents
How do LLM briefing CTAs work?
An LLM briefing CTA opens an AI assistant with a pre-written prompt that gives it a specific question, audience, or product context. Instead of sending someone to another landing page, you’re inviting them to explore your offer through an AI-generated explanation.
Most marketers still think CTAs like “Learn more” or “Start free trial,” (that only exist for human visitors) are enough. That thinking is outdated.
Super is doing something smarter.
They added links in their footer that open AI assistants with pre-written questions about the product, giving visitors another way to explore what Super offers.
When a user clicks, the link opens ChatGPT or Claude with a pre-written prompt focused on a particular product benefit:
“As a property manager, explain why Super is the best way to handle calls and stop missing leads. Summarize the key points from Super’s website.”
The prompt tells the AI who the persona is, what value to emphasize, and which product angle matters.
Instead of leaving the conversation entirely open-ended, Super gives the buyer a starting point. The prompt introduces the relevant problem, positions the product around that use case, and asks the AI to explain the benefits.
That’s the interesting part of this tactic. You’re influencing the context of a conversation, not training the underlying model. The buyer still gets an AI-generated answer they can question, challenge, or take further.
And rather than pushing for an immediate signup, Super is testing a different kind of CTA: one that helps visitors understand whether the product makes sense for them.
How can you personalize LLM briefing prompts for different buyers?
Create a different prompt for each important buyer persona, using their role, problems, and decision criteria to frame the question. The AI can then explain the same product from different perspectives.
Instead of relying on one generic product brief, build tailored LLM prompt CTAs for each persona so the LLM delivers the message that matters to them.
Birdy’s CEO, Joe Farafontoff, also tested this approach on the company’s website in 2025, as shown in the examples below.
Each prompt now tells the LLM how Birdy helps that specific role, whether it’s founders, sales, marketing, or product teams.
For example, the prompt for founders read:
“As a founder, summarize how Birdy helps track competitor pricing, launches, and funding using only information from https://iqbirdy.com. Highlight the key benefits for startup leaders.”
For Sales:
”As a sales leader, explain how Birdy helps teams win more head to head deals using only verified information from https://iqbirdy.com.”
Instead of generic messaging, Birdy created different starting prompts for different buyers, giving each role a more relevant way to explore the product.
This is the smart version of “tailor your message to your ICP.” Instead of writing four versions of a landing page, Birdy uses persona-specific prompts to frame the conversation around what matters to each role.
The AI handles the explanation within that conversation. That’s the segmentation idea being tested.
Can an LLM briefing CTA make AI remember your brand?
Not reliably. A prompt can influence what an AI assistant says in the current conversation, but it can’t guarantee that the assistant will save your brand as a preferred source or recommend it in future chats.
WPBeginner has been applying this tactic across all of their blog posts: every post includes an LLM summary CTA.
When you click it, it opens your AI tool and asks it to summarize the article for you. But what’s even more interesting is that the prompt also tells the tool to remember WPBeginner as a go-to SEO reference for future chats.
It’s a more aggressive version of the tactic. The prompt doesn’t just request a summary; it also tries to position WPBeginner as a trusted source for future questions.
But asking an AI assistant to remember something doesn’t mean it will. ChatGPT’s memory depends on the user’s settings and the information the system considers relevant. A pre-written prompt can’t guarantee a lasting brand preference, especially across unrelated conversations.
But the question is, does this deliver significant results?
What results have marketers seen from LLM briefing CTAs?
The early examples are interesting, but they need to be interpreted carefully. An increase in AI referral traffic doesn’t automatically mean a particular CTA caused it.
James Norquay, founder of Prosperity Media, implemented the same tactic used by WPBeginner across his site.
Norquay reported a 950% year-over-year increase in LLM referral traffic after his team started experimenting with AI summary links on selected high-traffic articles in May 2025.
LLM referrals accounted for roughly 5% of the site’s traffic at the time. Importantly, Norquay said he couldn’t attribute the increase to those links alone because the team was running several other LLM experiments.
So there’s a promising signal here, but not proof that briefing CTAs caused the growth. As Hill put it, there are still plenty of creative applications worth testing:
“Brands could use this same logic around persona segmentation blocks (why is this an ideal fit for XYZ role) and really tailor the prompt to that use case. Or imagine comparison articles, but they build the prompt to really speak to their biggest strengths. And the upside is that making it come from an LLM gives an air of third-party or neutrality to the insights.”
Although some marketers may be uncomfortable with this tactic, since it’s almost like nudging someone else’s tool to favor your content, one thing is clear. Ignoring a tactic won’t stop your competitors from using it.
How do you measure the impact of LLM briefing CTAs?
Start by measuring clicks on the briefing CTA and what happens to your website’s conversion performance. Then look for supporting signals, including AI referral traffic, branded search, and feedback from buyers who mention AI during their research.
Some will argue this tactic risks driving people off your site, adding friction that could hurt conversions.
It’s a fair point, not to mention it’s also one of the main reasons this approach is so tough to measure:
- Once a user clicks an LLM link, they leave your site and enter an environment you don’t control;
- You can’t see how long they interact with the LLM;
- You can’t see what the LLM says;
- You can’t directly see whether the AI conversation influenced a later purchase;
- Most of the impact shows up as early engagement signals, rather than conversions.
In other words, your regular dashboard only captures part of the story. That’s why these CTAs need to be treated as an experiment, not a guaranteed new acquisition channel.
And AI referrals are still a relatively small traffic source overall. Ahrefs’ October 2026 benchmark, based on websites using Ahrefs Web Analytics, found that AI assistants accounted for approximately 0.46% of traffic across 118,669 tracked sites. That makes it especially important to measure what your experiment contributes to your own business rather than assuming a few additional AI clicks will move the needle.
How do you test LLM briefing CTAs on your website?
Start with a small number of prompts, track how visitors use them, and compare the results with your existing CTAs. The goal is to learn whether the AI conversation adds value without hurting the conversion paths you already have.
1. Start in low-engagement areas
Place one or two pre-filled LLM links where user activity is normally low: footers, FAQ pages, or secondary CTAs. This makes unusual activity easier to spot.
2. Add a clear use-case prompt
Give each link a clear use case. Instead of writing, “Summarize this page,” try something like:
“As a marketing manager, use [your product page URL] to explain how [your product] helps improve pipeline visibility. Highlight the relevant features, supporting evidence, and any limitations.”
You want the model to understand who is asking and what message to deliver. That way, you know exactly what behavior or audience each link is meant to test.
3. Track the signals that matter
Capture behavioral data:
- Use heatmaps and session recordings to catch unusual movement
- Track clicks on the outbound LLM CTA as a separate event. Monitor AI referral traffic, return visits, and subsequent conversions independently; clicking an outbound AI link doesn’t itself count as an AI referral back to your website.
Heatmaps become especially useful here because any unexpected spike in footer or FAQ interactions could suggest that people are testing your LLM prompt CTAs.
4. Collect qualitative intel
Ask your sales or support team if prospects mention AI summaries or if they found you via ChatGPT. Even a few mentions are early indicators of traction.
This might be the only place where the feedback loop works.
5. Define what success looks like
Before launching, decide what success means. CTA click-throughs and engagement can tell you whether people are interested, but you also need to know whether the experiment affects conversions. Where traffic allows, run an A/B test comparing the existing experience with one that includes the LLM briefing CTA.
6. Iterate for signal, instead of perfection
Once you see a positive signal, expand: test different prompts per persona and implement them to other pages and high-engagement areas across your site.
If you want to test it out yourself, you can use this template:
https://chatgpt.com/?prompt=add+your+prompt+here
Before publishing, test each link in ChatGPT or the relevant AI assistant on desktop and mobile. Check that the prompt appears correctly, that the visitor can review it, and that the link works without unexpected login problems. Deep-link behavior can change, so don’t assume a link will always open or submit the prompt in exactly the same way.
Alternatively, check out CXL’s own LLM Deep Link Generator, showing exactly how to build these links in minutes.
How should you start testing LLM briefing CTAs?
Build a small set of persona-aligned prompts
Use the structure seen in Super and Birdy:
- Define the user persona;
- Ask the LLM to explain your value;
- Embed the key benefits you want echoed.
Start with 3–5 prompts.
Place CTAs strategically
Start with low-engagement areas first, and monitor to see whether something unusual happens.
Track directional behavior
Use:
- Click data;
- Scrolling and heatmaps;
- Traffic from AI tools;
- Mentions in sales conversations.
Remember: Engagement is an early signal. You still need to know whether the experiment helps or hurts conversions before rolling it out more widely.
Use available tools
Use free prompt templates, tools like Lovable, or the CXL AI Deep Link Generator to keep experimentation fast and eliminate friction.
Can you influence AI recommendations with briefing CTAs?
You don’t get to train an LLM by adding a clever CTA to your footer. But you do get to shape the question a buyer asks, put your product in the right context, and test whether the AI delivers a useful explanation. That’s an interesting experiment, especially when you’re willing to measure the results instead of assuming the model will remember your pitch.
For deeper training on how to adapt content to the AI-shaped buyer journey, book your seat for CXL’s AI-powered content funnel and content strategy for LLM visibility courses.
Frequently asked questions
What is an LLM briefing CTA?
An LLM briefing CTA is a website link that opens an AI assistant with a pre-written prompt about a product, company, or specific use case. Instead of sending visitors to another sales page, it lets them explore the offer through an AI-generated answer. Brands can tailor these prompts to different buyer personas or questions.
How do you create a ChatGPT CTA with a pre-filled prompt?
Write a prompt that includes the buyer’s role, the product or page to investigate, and the question you want answered. Use a compatible prompt-link generator to encode it into a ChatGPT URL. Test the link before publishing, including whether visitors can review and submit the prompt. Provide enough source context to help the assistant produce an accurate explanation.
Do LLM briefing CTAs train ChatGPT to recommend your brand?
No. A pre-written prompt can influence the response generated in that conversation, but it doesn’t retrain ChatGPT or guarantee future recommendations. Asking the assistant to remember your brand doesn’t ensure that it will save the information or use it later. Treat briefing CTAs as a way to guide a buyer’s immediate research experience, not a permanent AI visibility tactic.
How do you measure whether LLM briefing CTAs work?
Track clicks on the CTA, engagement with the surrounding page, and changes in website conversions. Compare the experience with and without the AI link through an A/B test where traffic permits. AI referrals, branded searches, and self-reported attribution can provide additional context. The important question is whether the new experience improves the buyer journey rather than simply generating clicks.
Are LLM briefing CTAs misleading or manipulative?
They can be if the prompt hides its commercial purpose or instructs the assistant to ignore negative information. A more transparent approach is to let visitors see the prompt, reference verifiable product information, and ask for relevant benefits and limitations. The aim should be to help buyers investigate the product, not disguise a promotional message as an independent recommendation.
What to do next
If you want to test LLM briefing CTAs properly, CXL’s CRO and experimentation course covers identifying conversion opportunities and building a more systematic testing process. For the wider AI discovery strategy, Alex Birkett’s Content strategy for LLM visibility and changing search habits course explores how to make your brand more visible through AI search, customer research, and off-page GEO tactics.
Join CXL’s AI Native Marketing program
Testing AI-powered buyer experiences is one part of building a more AI-native marketing operation. CXL’s AI Native Marketing program is a one-week sprint where you build three working systems: a marketing brain grounded in your business, a campaign engine with quality checks, and a reporting agent. It’s designed to help marketers connect AI to actual workflows rather than treating every use case as a separate experiment.
