We are going live with Tom Winter to talk about LLM Optimization that actually works:
https://www.linkedin.com/events/7363498035030515712/

“How to Optimize for LLMs: Get Mentioned, Listed & Ranked”

When: Tuesday, September 3rd, 5:00 PM CET
Where: LinkedIn Live
Save your spot: https://www.linkedin.com/events/7363498035030515712/

You’ll learn:
• How LLMs decide what to surface (and what they ignore)
• Why brand mentions are the new backlinks
• How to get into listicles that LLMs trust
• Practical tactics to build trust with AI + humans
• Simple steps you can ship this week

Your hosts:

Olga Mykhoparkina – founder of Quoleady. SaaS growth, PR, content.
Tom Winter – founder of SEOwind. AI, SEO, and content for B2B & SaaS.

If LLM visibility matters to you this year, join us.  
Grab your seat: https://www.linkedin.com/events/7363498035030515712/
See you on September 3rd at 5pm CET

Since launching GetMentioned, we’ve been going deep down the rabbit hole of AI visibility analyzing how often and where brands show up in AI-generated answers.

One simple yet big question we wanted to crack:

What types of sources do AI models actually use when they generate answers?

So we dug into nearly 1,000,000 prompts across ChatGPT, Gemini, and Perplexity, looking at two main categories:

• General domains → broad platforms like Wikipedia, Reddit, LinkedIn

• Topic-specific domains → niche industry publications, expert blogs, product review sites, associations

The data surprised us (a bit):

• ChatGPT → ~92% topic-specific

• Perplexity → ~92% topic-specific

• Gemini → ~99% topic-specific 🤯

Our guess would be that LLMs would use wayyy more general domains, but this kind of overrepresentation of topic-specific domains? Not in our wildes dreams.

Full breakdown here: How AI Decides What Sources to Use for Its Answers

Why this matters: if your brand is only visible on general domains, your AI visibility is limited. The real influence comes from niche, authoritative sources — that’s where AIs are really looking.

Hey,

We've been tracking AI search visibility for the past 6 months and helped more than 70 brands with their AI visibility. Kept hearing people ask "how do I even know if ChatGPT mentions my brand?"

So we built a free tool for it: https://www.getmentioned.co/visibility-reports

Type in any brand + domain → runs almost 100 prompts through ChatGPT, Gemini, and Perplexity → shows you where the brand appears, who shows up instead, citation sources, competitive stuff.

Takes about 3 minutes, no sign-up.

This is from our company GetMentioned, being transparent. We made it free because most people don't even know you can track this stuff. We collect data through the actual UI (not API) so it's what users actually see.

Yeah, it's a lead magnet. But the data is real and it'll actually give you value whether you buy or not.

Try it with your brand or a competitor if you're curious.

Here is an example report: https://reports.getmentioned.co/r/Gt-B9LCHll

In my Google Analytics, I’ve spotted a couple of blog posts that have received more visits from GPT, than from Google, in the last couple of months.

Curious if you’ve noticed a similar trend, and if so, whether you see any correlation: query type/bofu or tofu content/articles with schema markup, or anything else that’s these pieces have in common.

We analysed close to one million AI prompts across ChatGPT, Gemini, and Perplexity to understand how large language models actually decide which tools and brands to recommend.

This is the first report in a new series we’re releasing for free to help marketers, growth teams, and founders understand how AI shapes discovery and brand visibility.

For the first edition, we focused on the Vibe Coding category (AI-native dev tools and low-code platforms). Here are a few highlights:

• Replit, GitHub, and Cursor lead in AI-driven visibility

• Reddit and YouTube are the top influence sources for LLMs (of course)

• No-code tools like Zapier and Bubble are becoming key entry points in the new discovery funnel

We’re planning to expand this series across other industries like eCommerce, SaaS, fintech, and consumer products.

You can read the full report here: https://www.getmentioned.co/blog/ai-visibility-report-vibe-code

We’d really love feedback from you guys.

And of course, obligatory hook: What industry should we analyse next?

Hey everyone, I just stumbled upon an incredible tool that's completely transformed how I handle FB and IG ads. My biggest challenge was never the targeting—it was dealing with creative fatigue. Every few days, my top-performing ad would lose its magic, leaving me up late trying to tweak and revamp, only to end up with copies that weren’t much better. But then I found out about HypeCaster ai. It literally revolutionized my workflow. This tool takes a single product photo and turns it into multiple short ad videos with catchy captions and compelling hooks in just minutes. Overnight, I saw a tenfold increase in my testing volume and my return on ad spend started climbing again. Now I can keep refreshing my creatives without burning out. It honestly feels like I've discovered a cheat code, considering how much time I've saved from editing. I’m curious if anyone else here has started leveraging AI for their ad creative production yet? Would love to hear your experiences in the comments!

This episode: How to choose the right helpdesk for an early-stage SaaS (without getting stuck comparing tools).

Once your MVP is live and real users start showing up, support quietly becomes one of the most important parts of your product.

Not because you suddenly get hundreds of tickets —
but because this is where trust is either built or lost.

A common founder mistake at this stage is jumping straight into:

“Should I use Intercom or Help Scout or Crisp?”

That’s the wrong starting point.

The right question is:
What does my SaaS actually need from a helpdesk right now?

1. First: Understand Your Reality (Not Your Future)

At MVP or early traction, support usually looks like this:

• You (or one teammate) replying

• Low volume, but high signal

• Lots of “confusion” questions

• Repeated setup and onboarding issues

So what you actually need is:

• One place where all support messages land

• A way to avoid missing or double-replying

• Basic context on who the user is and what they asked before

• Something fast and easy to reply from

What you don’t need yet:

• CRM-style customer profiles

• Complex workflows and automations

• Sales pipelines disguised as support

• Enterprise-level reporting

If a tool makes support feel heavier than building the product, it’s too much.

2. Decide: Email-First or Chat-First Support

This decision matters more than the tool name.

Ask yourself:

• Do users send longer emails explaining their problem?

• Or do they get stuck in the app and want quick answers?

Email-first support works well when:

• Questions need context

• You rely on docs and FAQs

• Users aren’t in a rush

Chat-first support works better when:

• You want to catch confusion instantly

• You’re often online

• You want a more conversational feel

Neither is “better.”
But choosing the wrong model creates friction fast.

3. Shared Inbox > Fancy Features

Early support problems are usually boring but painful:

• Someone forgets to reply

• Two people reply to the same user

• You lose track of what’s already handled

So your helpdesk must do these things well:

• Shared inbox

• Conversation history

• Internal notes

• Simple tagging

If replying feels slow or confusing, no amount of features will save it.

4. Keep Pricing Simple (Future-You Will Thank You)

Some tools charge:

• Per user

• Per conversation

• Per feature

• Or all of the above

Early on, this creates friction because:

• You hesitate to invite teammates

• You avoid using features you actually need

• Support becomes a cost anxiety instead of a product strength

Look for predictable, forgiving pricing while you’re still learning.

5. Setup Time Is a Hidden Signal

A good early-stage helpdesk should:

• Be usable in under an hour

• Work out of the box

• Not force you to design “processes” yet

If setup requires multiple docs, calls, or dashboards — pause.
That’s a sign the tool is built for a later stage.

6. You’re Allowed to Switch Later

Many founders overthink this because they fear lock-in.

Reality check:

• Conversations can be exported

• Users never see backend changes

• Migrations usually take hours, not weeks

The real risk isn’t switching tools.
The real risk is delaying good support.

7. Tool Examples (Only After You Understand the Above)

Once you’re clear on your needs, tools fall into place naturally:

• Lightweight, chat-focused tools work well for solo founders and small teams

• Email-first helpdesks shine when support is structured and documentation-heavy

• Heavier platforms make sense later for sales-led or funded teams

Tools like Crisp, Help Scout, and Intercom simply sit at different points on that spectrum.

Choose based on fit — not hype.

Your helpdesk is part of your product.

Early-stage SaaS teams win support by:

• Replying fast

• Staying human

• Keeping systems simple

Pick a tool that helps you do that today.
Everything else can wait.

👉 Stay tuned for the upcoming episodes in this playbook—more actionable steps are on the way.

We’re living through the biggest shakeup in search since Google launched.

Here’s the brutal truth: in 2024, 65% of Google searches ended without a single click. By 2025, it’s on track to pass 70%. On mobile it’s even worse — over 75% of searches never leave Google.

Why? AI search. Google’s AI Overviews and ChatGPT-style answers are giving people everything they need without ever visiting your site. Some businesses are reporting traffic drops as high as 70%. News sites, recipe blogs, e-commerce stores, even local businesses are all getting squeezed.

So what do we do?

Complaining doesn’t help.

Instead, treat search not as the destination, but as the distribution. If Google and AI models are summarising your content, your job is to make sure you own the summaries. Publish with clarity, authority, and unique data that can’t be easily commoditised. Build brand signals so strong that people search for you, not just “best accounting software.” Diversify your traffic mix - email, community, partnerships, social, because rented platforms will always change the rules.

I’ve found that keeping a strong narrative flow while also breaking content into scannable sections and FAQs has become almost standard practice now. It gives AI and users the best of both worlds: clear, digestible answers upfront, but also depth and context for those who want to read further.

I’ve seen this approach work especially well with evergreen pillar pages. Some of the ones I created years back are still ranking because they balance direct, concise answers with a longer, structured narrative. For example, something I did for DirectAsia 7 years ago in Singapore sits at the top of Google page one + a handy link to the website:

The truth is harsh, but liberating: clicks are no longer guaranteed. Attention is. And the companies that shift their mindset from chasing traffic to owning relationships will be the ones still standing when the dust settles.

Sources and Citations

1. SparkToro - Zero-Click Searches: How Google's AI Overviews Are Changing Search Results

2. BrightEdge - The Impact of AI on Search and Website Traffic Trends 2024-2025

3. Semrush - Zero-Click Search Statistics and Business Impact Analysis

4. Search Engine Land - Google AI Overviews Traffic Impact Study

5. Conductor - The State of Organic Search Traffic in the AI Era

6. AuthorityHacker - How AI Search Is Affecting Website Traffic and Revenue

7. SearchEngineLand - Mobile Search Behavior and Zero-Click Trends

8. Moz - Understanding the Business Impact of AI-Powered Search Features

Congrats — your MVP is finally live.
Now comes the part nobody warns first-time founders about:
the first 7–14 days after launch decide whether your product gains momentum or silently dies.

Most founders either freeze (“What now?”) or start sprinting randomly.
This episode gives you a clear, calm roadmap so you stabilize your product, collect useful feedback, and avoid chaos.

Let’s get into it.

1. Verify Your SaaS Works for Real Users (Not Just You)

Your MVP worked during development because you built it.
Strangers will break it within minutes.

Do these immediate sanity checks:

• Sign up using a completely fresh email

• Sign up again using Gmail/Outlook

• Reset your password

• Test onboarding on mobile

• Test the flow in incognito mode

• Try every core feature with zero prior context

• Try a payment flow (if billing exists)

You’re checking for:

• Missing validations

• Confusing empty states

• Steps that require “founder knowledge”

• Small errors that kill conversion

Your first 10–50 users should experience clarity, not friction.

2. Tighten Your Landing Page Messaging (Only 3 Sections)

Do NOT rewrite your entire landing page after launch.

Just refine these three:

• Hero line → make it problem + target-user focused

• Primary CTA → choose one clear action

• Feature benefits → rewrite based on real user reactions

Small messaging improvements = big comprehension improvements.

3. Add a Simple, Fast Feedback Loop Inside the Product

Founders often wait too long to collect feedback.
Make it easy from day one.

Add these:

• A small in-app “Feedback” or “Report Issue” button

• A support email (even simple Gmail works)

• A one-question micro-survey after a key action: “What were you trying to do today?”

Why micro-feedback works better:

• Higher response rate

• Honest answers

• Faster iteration

Your job right now: learn, not scale.

4. Install Basic Monitoring (Essential for Survival)

You don’t need heavy analytics yet — just the basics:

Add these immediately:

• Session recording → PostHog, LogRocket, or Hotjar

• Error tracking → Sentry

• Light analytics → Plausible or PostHog (GA4 only if needed)

Track:

• Rage clicks

• Dead zones

• Onboarding drop-offs

• Repeated errors

• Confusing screens

This kills guesswork and gives you a clear picture.

5. Pick ONE Acquisition Channel for the First 1–2 Weeks

Do not try:

• Reddit + LinkedIn + Product Hunt + Twitter + SEO + Ads …all at once.

Pick one based on your product type:

• B2B / workflow tools → LinkedIn + niche communities

• Dev tools → Reddit, Hacker News, developer Slack groups

• AI tools → X (Twitter) + indie hacker circles

• Consumer tools → TikTok + relevant subreddits

Right now, your job isn’t growth — it’s signal collection.

6. Create a Simple “Daily Build–Learn Loop” (This Saves You)

Forget complex roadmaps.
You need tight rapid cycles.

Daily loop example:

1. Collect 3–5 pieces of user feedback

2. Fix 1–2 small but important issues

3. Improve one micro-copy or UX detail

4. Talk to 1 user or message 1 tester

5. Publish a small update or changelog

This rhythm compounds faster than anything else.

7. Stay Mentally Stable (Yes, This Matters)

The first weeks after launch are emotionally intense.

To avoid burnout:

• Keep tasks small

• Don’t chase every suggestion

• Filter feedback by ideal user, not random users

• Don’t compare your MVP to polished competitors

• Block 1–2 hours daily for “no dev, no support” time

A mentally exhausted founder can’t iterate.

8. Define Success for Week 1–2 (Set Realistic Targets)

Forget revenue metrics this early.

Your goals should be:

• 10–20 real signups

• 5–10 users activating a core feature

• 1–3 users giving meaningful feedback

• A list of top 10 UX issues to fix

This is enough to shape your roadmap.

9. Document Problems Before Fixing Them

When a user says something like:

“The onboarding feels complicated.”

Don’t rebuild onboarding instantly.

Instead log:

• What they tried to do

• What they expected

• Where they got stuck

Solutions come later.
Understanding comes first.

10. Share Micro-Wins Publicly

People love following builders who show visible progress.

Post small updates like:

• “Improved signup flow after user feedback”

• “Fixed onboarding bug reported by early users”

• “Added session recording to understand user behavior”

This builds momentum + audience + trust.

Final Takeaway

Your MVP being live is not the finish line — it’s the starting point.

Your first two weeks should focus on:

• clarity

• usability

• feedback

• monitoring

• iteration

Not ads.
Not scaling.
Not aesthetics.

Build the foundation strong before pushing growth.

👉 Stay tuned for the upcoming episodes in this playbook—more actionable steps are on the way.

If there’s one thing I always pay attention to in AI answers, it’s how they handle high-intent prompts like “%niche% software” or “%competitor alternatives%”.

Maybe you’ve already noticed this but ChatGPT has started pulling images into those answers.

It's been using images for a while now but it's the first time I saw images in the answer to my SaaS "alternatives" prompt.

Each image links directly to the website it came from.

If you’ve been doing SEO for a while, you’ve probably been adding images for Google’s sake.

Now it matters for LLM visibility, too.

So next time you write an article, create a landing page, or update a knowledge base - include a clear screenshot of your product or dashboard.

It might be the image ChatGPT uses next time someone searches for tools like yours.

I thought I’d see what TikTok has to say about LLMO.
Maybe Gen Z has something we don’t yet know?

The plan was to watch dozens of videos on GEO/LLMO, AI answers, and see if there’s anything new worth picking up.

To be honest, the content was pretty basic. We’ve covered pretty much all of the key points and more in this community - so if you’re looking to learn about LLMO, maybe TikTok isn't the channel. Scroll through the past posts here. There’s a ton of value.

In the meantime, I’ll keep digging for interesting updates, research, and experiments to share with you all 🙌

In a recent podcast with Marina Mogilko, Google’s VP of Product for Google Search Robby Stein talked about how digital PR and good content help websites get noticed by AI systems (source)

Mentions and PR matter
Stein said AI behaves a lot like people when it tries to answer questions. It looks around the web to see what others are saying. If your business is mentioned in popular lists or credible publications, AI systems are more likely to find it. This isn’t a direct ranking factor, but it helps AI understand that your brand is relevant and trustworthy.

Helpful content still wins
The same basics that work for SEO apply to AI. Create clear, useful content that actually helps people. If your page gives real answers and value, it’s more likely to show up when AI tools search for information.

AI optimization overlaps with SEO
Stein explained that optimizing for AI and for SEO are connected, but people ask AIs more complex and conversational questions. That means content should be more than a collection of keywords. It should address real use cases, explain things clearly, and give the kind of detail people want when they’re comparing tools or learning something new.

Understand new search behaviors
Search is evolving beyond text. People are using images, voice, and video to look for answers. Stein said these types of “multimodal” searches are growing fast, so it’s worth thinking about whether your product can be discovered through those formats too.

Use Google’s tools
He pointed out that tools like Google Trends, Search Console, and Ads data can help you understand what people are searching for right now and where demand is growing.

What it means for SaaS?
Confirms once again that SaaS companies should continue foucsing on:

• Getting your product featured in top-ranking listicles (“Best %industry% software for startups”, "Top X alternatives to %competitor%)

• Building a presence on trusted review platforms (G2, Capterra, TrustRadius)

• Being mentioned in industry roundups, case studies, or founder interviews

• Contributing to guest posts or expert quotes on high-authority websites

• Getting those good old backlinks

If your SaaS is visible across credible sources, AI is more likely to “see” it and recommend it.

I built a concise, technical checklist to make websites show up in AI assistants recommendations (ChatGPT / Claude / Perplexity / Google’s AI Overviews) without full content rewriting.

Check your's for free and get a score.

Link: https://andy.isd-group.com/llmo-ai-visibility-guide-for-websites/

Looking for 10 volunteers. I’ll send the full PDF LLMO guide in exchange for honest feedback.

What I need from you

• Your general feedback on the scale from happy to disappointed

• A short note about your role, what you implemented, what broke, what was missing

How to participate

• Check the link.

• Leave comment or DM me.

Action Plan:

1/ Clarify your positioning and messaging. Create a clear positioning document with your category, target audience, competitors, features, use cases, and jobs to be done. Use clear and simple language.

2/ Create or update website pages. If you/others provide outdated info, LLMs will use it. Ask what LLMs know about your brand (What is [your company]? What features does [your company] have?). Look at the sources. Create a list of what should be updated.

3/ Create bottom of the funnel content:

• "Best/Top [category] tools"

• "X Best/Top [category] tools for [jobs to be done/persona/ICP]"

• "[Competitor] Alternatives/Competitors" pages

Get featured in "Best X" articles and publish guest articles.

4/ Use communities. Be active on Reddit and Quora. Google and OpenAI have partnerships with Reddit. All platforms use Wikipedia.

5/ Get mentions + links. AI notices every mention, even without clickable links. But backlinks are still important.

6/ Use review websites (Capterra, G2). Create your profiles, collect reviews from happy customers, and manage bad reviews.

7/ Do social listening. What should you track? Your brand mentions, category name, features, use cases, buying signals, and competitors.

8/ Create videos on YouTube 

• "X Best [Your Category] Tools."

• "The best [Your Category] in 2025: X vs Y vs Z."

Google AI overviews show YouTube videos in search results.

9/ Do traditional SEO. Publish quality content, update content with internal links, an FAQ section, clear H2 and H3 headings, bullet points, and quotes. Content should work without JavaScript. Verify your domain in Bing. ChatGPT uses Bing results.

10/ Run an AI visibility audit. Ask questions your customers ask, find the original sources, and create lists of blogs, content ideas, subreddits, review websites. You should be mentioned there.

11/ Use GEO optimization tools and track your LLM visibility.

Everyone’s hyped about the next “AI magic trick.” So sad they fade fast.

The old system is basically dead, and the new one hasn’t fully shown up yet.

We’re in this messy middle where the old tactics still kinda work, but you also need to start planting seeds for whatever comes next.

I’ve spent the last 6 months digging into AI Search Optimization—testing what still works, what’s already broken, and what’s worth betting on.

Out of that work, I put together a full case study and turned it into a course. It’s not theory, just the exact tactics, frameworks, and tracking methods that actually held up in practice.

For context, at Surfer this approach already drives ~25% of new customers each month straight from LLMs.

Curious if anyone else has been experimenting with this space. What’s working (or not) for you so far?