Taylor Scher

SaaS SEO Consultant

Hi, I’m Taylor

I help SaaS teams turn search into a predictable channel for revenue growth. Whether you need a roadmap or someone to run the whole thing, I'm here to make sure your investment pays off. 

Here's a few examples of what I've done for other clients:

- 150% increase in demos for a Supply Chain SaaS over 3 months
- 161% increase in demos for a restaurant analytics team 
- 333% increase in demos for a legal tech brand over 3 months
- Added $138,000 in ARR to a Shopify Upsell App in under 6 months

I do all of this through 4-tiered packages:

- SEO consulting 
- Fractional SEO
- Content creation
- Content creation + PR

If you're interested in getting started, please use my Calendly booking page to schedule an intro call

BTW HERE IS MY EMAIL TO CONNECT: taylorscher5@gmail.com

Search Engine Optimization Consultant

GTM for Early Stage SaaS | Co-founder @ Datapad | SaaS Growth Advisor | Reforge | 1x Exit |

I’m a marketer, 2x entrepreneur with 1x exit, and helped companies to go from 0 to 8 figures.

My achievements:

- Built 2 VC backed startups with one exit

- Built a 7 figure productized marketing agency

- Became a mentor in top accelerators such as: 500, Plug and Play, Techstars

- Got to work with the portfolio companies of amazing investors such as A16z, Craft Ventures, YC

- Built a podcast with 20k downloads in a year-figure

- Transformed my body more times than Christian Bale ☺️

John Ozuysal

Apparently, according to someone’s lead list, I’m a high-performing woman.

Here is why:

“We help high-performing women like you.” - This is the email I got

I wonder where they got the list? Or maybe personalization is having a rough day.

Oh well, at least I am "high performing" so thank you for that 🤣

🚨Hiring: House of Growth - AI Led Growth Agency is growing, and we are looking for 2 new roles 🚨

1️⃣ GTM Engineer

We’re looking for a GTM Engineer who will work on:

Internal campaigns for House of Growth on email and LinkedIn to expand our reach. This will be a mix of:

- Signal based plays
- Cold outbound

Important:

 👉 Please reach out only if:

You’re really good with Clay
You’ve run outbound campaigns before
Bonus points if you’ve worked with agencies or done outbound for agencies
This is a hands-on role for someone who enjoys building systems, testing channels, and scaling what works.

2️⃣ Content Marketer (Internal Role)

We’re also hiring a Content Marketer to work on (internal brand, not client work).

You’ll focus on:

Research-driven content
LinkedIn content
Thought leadership pieces

This is not a client-facing role, and you will be doing content only for House of Growth

📩 Interested?

Send me a DM and tell me:
Which role you’re applying for
Why you’re a good fit

Both roles could be PT and FT

Looking forward to meeting sharp builders and thinkers.

Here’s how we helped a B2B SaaS client increase their AI citations by 21% and improve positions by 37% in just one month.

One thing I really like about AI search compared to traditional SEO is speed.

If you play your cards right, results come much faster.

The problem:

This client wasn’t struggling with visibility. Their brand was already well known.
The real issue was how AI systems were describing them.

When we analyzed AI-generated answers about their company, we noticed:

- The positioning didn’t match how they wanted to speak to prospects
- Product details were inaccurate or incomplete
- Most information was pulled from outdated sources (old blog posts, Reddit threads, and G2 reviews)

In short: AI didn’t understand their current product.

What we did:

Step 1: Identify the prompts that matter

We mapped the exact prompts they wanted to “win” in AI search, including:

Product overviews
Integrations
Competitor comparisons
Pricing-related queries

Then we created focused, high-quality content specifically for those prompts.

Step 2: Fix brand confusion with an AI info page

We discovered that AI was confused about their brand, products, and features.
So we created a dedicated AI-friendly information page that clearly explained:
What the company does
Core products and features
Use cases and positioning
This gave AI systems a reliable, up-to-date source to crawl and reference.

Step 3: Clean up outdated third-party information

We found multiple external articles and reviews sharing outdated or incorrect info.

Actions we took:

Reached out to publishers and requested corrections
Identified outdated G2 reviews
Launched G2 review campaigns to reflect the current state of the product

The result (in 30 days)
📈 +35% increase in citation rate
🚀 +21% improvement in AI search positions

Key takeaway:

AI search isn’t just about visibility.
It’s about controlling the narrative.
If AI doesn’t have accurate, up-to-date information about your product, it will fill the gaps with whatever it can find—even if it’s wrong.

And that’s where the opportunity is.

Thank you, Scrunch, for making it easy for us to track this

AEO/GEO is not the same as SEO 

Microsoft confirmed this with the latest playbook they released 👇

Without going into too much technicality below are some of the remarks that got my attention:

"In shorthand, the industry is talking about shifting from SEO to AEO and GEO. At Microsoft, we believe SEO and catalog investments built a foundation to expand upon in LLM-based search"

"The base remains the same: up-to-date product feeds and clear, crawlable, structured content. But retailers and brands must now treat their entire catalog and site architecture as content, ensuring every product detail, benefit, and price signal is machine-readable, up to date, and context-rich"

"Traditional SEO remains essential because AI systems perform real-time web searches frequently throughout the shopping journey, not just at purchase time, and your site must rank well to be discovered, evaluated, and recommended."

"If SEO focused on driving clicks, AEO is focused on driving clarity with enriched, real-time data. GEO helps establish credibility through an authoritative voice. "

"CMOs need to ensure AI correctly understands and elevates,brand differentiators. Growth and performance leaders must adapt to AI-led. Digital and e-commerce leaders should plan new metrics for AI-intermediated journeys. CTOs must make the stack AI-readable and AI-accessible. Data and analytics leaders need strategies for the ‘invisible’ early-funnel research happening inside AI conversations." - CONTENT TEAM SHOULD NOT BE IN SILOS ANYMORE

Microsoft AEO Playbook

If I were a CMO of a B2B SaaS company…”

👇
But you’re not.

And honestly, that’s where most advice falls apart.

Stop telling people how to do things you’ve never actually done.

If you really want to be something, go be it first.

This is no different from people selling courses on how to make $1M
when they’ve never made it themselves.

Experience beats theory.

Execution beats opinion.

Results beat credentials.

If you haven’t walked the path, don’t sell the map.

I recently attended a founder dinner in Dubai, and a few patterns stood out. 

Sharing my observations around GTM:

1️⃣ Investment often feels easier when it is visible.

Merch, events, and branding are tangible and familiar, which makes them easier to justify. Companies are willing to invest in merch and traditional offline events, but not so much in channels such as content, community, ABM, etc.


2️⃣ Demand generation often comes before demand capture.

Many teams are excited to explore PR or paid social early on.

What is sometimes missed is fully capturing existing demand first through intent driven or signal based channels before expanding into broader awareness efforts.

 Both approaches matter. Sequencing changes efficiency.

3️⃣ Acquisition is heavily relied on paid

Many teams start with paid acquisition and end up relying on it almost exclusively.

 As ad costs rise, this naturally creates pressure and stress. Without diversification, there is also uncertainty around what happens if the channel changes or performance drops.


 4️⃣ Product market fit is discussed often. Message market fit less so.

 A lot of energy goes into building the product, followed by scaling acquisition.

What is easy to skip is validating whether the messaging resonates with the intended ICP, especially with cold audiences.

When that validation is missing, channels can look ineffective when the opportunity is really in the narrative.


There is an incredible amount of talent here, and the quality of builders and operators in this ecosystem is genuinely impressive. I am really enjoying the conversations and the openness to share and learn.

If you are around Dubai and open to a coffee and a thoughtful growth conversation, I would love to connect.

The intent data told us they raised a Series A.

What it didn't tell us: where they're actually bleeding cash.

"Recently raised Series A" - yeah, so did 47 other vendors in their inbox.

"Just hired a CMO" - congratulations, you and every other growth agency just sent the same pitch.

We were competing on speed, not relevance.

So we built something different.

Our internal tool doesn't just pull signals. It stacks them.

Series A in last 6 months? Cool. Everyone knows that.

But Series A + running Google Ads + zero organic traffic for their keywords + no competitor comparison pages?

Now we're talking.

That's a company burning cash on paid because their content strategy doesn't exist. That's someone who needs what we actually do.

The tool creates an AI agent that hunts for these signal combinations. The ones we define. The ones that actually matter to our specific service.

Our list went from 2,000 "warm leads" to 47 companies.

But those 47 companies? They actually respond.

Because when you reach out, you're not pitching.

You're diagnosing a problem they didn't realize they had.

We've tried everything. Content. Cold email. Mass outreach. Paid ads.

This signal-based ABM is crushing all of it on ROI. (No random ABM)

Not because the list is bigger.

Because the list is real.

🚨 Hiring 2 FT or PT GTME to work with me 1-1

👇

I do hate writing job descriptions, but here's the TL;DR 😀 

You'll work directly with me to build the internal growth engine for House of Growth. We will do some cool stuff together if you are committed

Below is your typical formal JD (boring)

Expectations:

Build and run full outbound and warmbound GTM motions for House of Growth

List building to enrichment to copy that converts to launch to optimization to results

Work one-to-one with John as a GTM operator

Your output is meetings, pipeline, and insights to scale

Monitor deliverability, domain health, warmup and performance

Provide weekly performance reports and tactical recommendations

Route all warm and hot prospects directly to John

What You Need:

Expert level Clay skills

Workflows, enrichments, AI formulas, API integrations, waterfall enrichment, scoring logic and cost efficient data pulls through tools like SimilarWeb, Ahrefs and Adyntel

Strong list-building ability

You understand how to segment by ICP, triggers, signals and verticals

Strong cold email copywriting skills

Data-driven mindset

You understand reply rate, positive reply rate, meeting rate, and how to move each metric

Real GTM experience

This role is not for someone learning Clay or outbound for the first time

Autonomous operator

You can build, launch, and optimize without hand-holding

Application link under comments 👇

Send me your best stuff and we will see

Here is how we increased AI search visibility around buying intent prompts from %26 to %48 in 3 months only👇

1️⃣ Identified the most cited pages and updated them

Before we did updates at scale, we prioritized the most cited pages because we don't want AI to be fed with outdated information

2️⃣ We refreshed all of the decaying content

LLMs strongly favor fresh and accurate content.

We started simple:
• Updated publish dates
• Updated titles and dates inside titles
• Removed outdated stats, features, and claims
• Republished quickly
Then we went deeper:
• Took the main keyword
• Turned it into a prompt
• Searched it in ChatGPT
• Extracted follow-up questions people were asking
• Added those as new H2s and H3s
• Added internal data or external data (stats, quotes etc..)

 3️⃣ Reddit mentions

We identified Reddit threads already influencing AI answers for our target prompts.

What we did:
• Commented with genuinely helpful answers
• Pushed comments to the top
More third-party visibility → more AI citations → faster lift.

4️⃣ We fixed inaccurate AI narratives about the brand

AI was already citing the company, but with wrong information.

So we:

• Identified which URLs influenced AI answers
• Found outdated pricing and features
• Reached out to those publishers
• Corrected the source data

AI search is not just about visibility.

It’s about controlling your narrative.

 5️⃣We rebuilt comparison content for AI consumption

The listicles looked fine visually, but were semantically weak.

Fixes:
• Converted image-based tables into HTML
• Expanded rows to match real buyer comparison questions
• Added future-proof attributes
• Benchmarked tables against what AI already outputs

6️⃣ We improved the structure for humans and models

Across BOFU pages:
• Added TLDR sections right after the intro
• Added Q&A-style supporting articles
• Cleaned internal linking
This improved readability, extraction, and reuse in AI answers.

7️⃣ We optimized entities at scale

For every article:
• Intro
• Outro
• Every important H2
We identified missing and weak entities and reinforced them naturally.
This helps AI understand context, not just keywords. 

8️⃣ Brand mention campaigns 

We used Scrunch to pull all the relevant mentions for us. Our internal tool identified whether those pages are landing pages, reddit thread or listicles etc... 

Then our agent scraped the contact information of authors we want to reach out. After this step, we started a campaign to get mentioned on the listicles. Since we also run the GTME department inside House of Growth - AI Led Growth Agency it wasn't hard to scale outreach campaigns

We also repurposed some of the articles we did as LinkedIn articles - this is a new experiment we are doing after seeing LinkedIn articles starting to be picked up by LLMs. I will report on this when we have more data

If a company hasn’t invested in AEO, where should they start?

👇

Start by diagnosing the problem.

Before creating any content, figure out whether the issue is visibility, representation (citation control), or both.

Later-stage companies usually already have visibility. The risk is how they’re being represented.

 AI search often pulls from competitor blogs, old Reddit threads, reviews, and third-party posts that don’t reflect the company’s current narrative.

The first step is to identify the URLs influencing AI answers and audit them for accuracy.

In parallel, build earned content quickly so AI systems learn from the company’s own materials, not someone else’s.

Earlier-stage companies typically have a visibility problem and a representation problem.

Start by mapping the prompts you want to win, then identify which URLs currently influence those prompts (often listicles and Reddit threads).

From there, focus on earned visibility by participating in those conversations and getting included where influence already exists.

Once there’s more budget, expand into creating content designed to compete for broader, category-level prompts.

"SEO isn't expensive. Being invisible when your ICP is choosing vendors is

👇

Many start-up founders are hesitant to invest in SEO/AEO as a growth channel.

This is because of the stigma that it takes too much time to see results, and that there is a high upfront cost before results properly compound.

Even though this might be true for competitive niches, not being a part of the conversation when your ICP is making decisions and creating shortlists is going to cost you in the long-term.

SEO as a growth channel has turned from 10 blue links to demand capture and narrative control as a whole.

The demand capture aspect is that you can compete for the #1 recommendation spot in AI search engines while also competing in organic Google.

The narrative control aspect is that, in the long run, you're going to be the go-to option when someone is searching for an alternative to your competitors or a solution like yours.

Being invisible is not expensive, but it can cost you in the long run when your competitors have an established presence while you're still in the situation of putting money into getting money out with paid ads, conferences, etc.

Below is an excellent case study of one of the companies we work with, Warmly, which invested in SEO and AEO early and is now seeing it as one of its most efficient channels from an ROI perspective.

The ROI comes from them appearing for their main category keywords when people search for them, and also from the fact that Warmly is also in the recommendation options for most of their direct competitors.

Sharing the image below from maximus greenwald post

If you’re a B2B SaaS company, there’s one thing you can do that will improve your visibility in AI search and increase conversions from paid ads

That move is building category landing pages mapped to specific ICPs and use cases.

Most SaaS companies stop at a single category page.

Project management software. CRM. Analytics platform.

That’s no longer enough.

Instead, break the category down by context.

For example, instead of one generic project management software page, create pages like:

 Project management software for real estate
 Project management software for finance
 Project management software for education

Now you are not just targeting a category keyword.

You are mapping that category to a clear buyer and use case.

You can take this one step further.

Beyond industry pages, create pages based on how the product is actually used:

 Project management software for offline teams
 Project management software for managing client projects
 Project management software for cross-functional collaboration

This helps in two ways.

First, for AI search and AEO.

These pages send clear signals about where your product fits. Long-tail, intent-driven pages are much easier for LLMs to surface than a generic homepage.

Second, for paid ads and conversion.

If you are bidding on these keywords but sending traffic to a generalized page, you are leaking revenue.

When someone clicks an ad and lands on a page that exactly matches their intent, friction drops and conversion improves.

Right now, we are testing this ourselves at House of Growth - AEO Agency

 We are building dedicated landing pages for each ICP and use case.
 We are also testing the same strategy using list-style content.

The goal is to see which format drives better AI search visibility and stronger conversion.

One thing is already clear.

If you are paying for traffic and not mapping it to specific ICP pages, you are not just missing the AEO upside.

You are leaving money on the table.

Everyone is obsessing over being visible in AI search.

But that’s only half the battle.

The real question is:

 👉 Is AI representing your product the way you would in a sales call?
Here’s the uncomfortable truth.

 AI doesn’t invent opinions out of thin air.

 It summarizes what already exists on the internet.

So if the internet has outdated, incomplete, or flat-out wrong information about you,

AI will confidently repeat it.

What I’d do instead 👇

1️⃣ Take 20 to 30 high-intent prompts you care about
 (for example “best X software,” “X alternatives,” “tools for Y teams”).
2️⃣ Run those prompts through an AI search analysis tool.
3️⃣ Look at which domains influence the answers.

Most of the time, it’s:

“Alternatives to” blog posts

Category listicles

Third-party reviews written one to three years ago

4️⃣ Ask one simple question:

 Are we mentioned there, and is the information accurate?

What you’ll usually find:

Old positioning
Wrong ICP
Outdated pricing
Missing features you launched years ago

“Competitor alternative” posts that no longer reflect reality

This is where the real work starts.

You have to:

Reach out to those publishers
Point out factual inaccuracies
Provide updated, verifiable information

Make sure AI isn’t selling the wrong version of your product on your behalf.

Because if AI is your new first sales touchpoint, you want it telling your story, not a 2022 version of it.

Why you don’t show up in AI search?

Here’s the simplest answer:

You have no content.

And nobody knows, mentions, or talks about your brand.

That’s it.

AI systems don’t “discover” brands magically.

They reflect what already exists on the internet.

Once you accept this, everything else makes sense.

Only then do details start to matter:

Entity optimization
Query fan-outs
Topical authority etc..

Is AI search describing the product you sell today, or the one you sold two years ago?

Most Series A SaaS teams think:

“Great, AI already knows about us.” - but this is just the beginning of the battle 

You can show up in AI answers all day long, but if that information is coming from competitors, outdated blog posts, or inaccurate third-party sources, you’re still losing.

So how do you fix it?

1️⃣ Own the narrative

Start by writing about:
Your product (clearly and repeatedly)
Your positioning vs. competitors
The exact questions buyers ask AI today

Host this content on your blog so AI has fresh, authoritative sources to pull from.

2️⃣ Fix the ecosystem

Next, audit where AI is getting information about your product:

Old reviews
Comparison articles
Blog posts from 2022–2023
Third-party publishers with outdated takes

Then reach out and say:

“This information about our product is no longer accurate. Here’s what we do today.”

This is exactly what we’re doing right now for a Series B SaaS company:

They already have AI visibility

But AI is describing a 2023 version of their product

So we’re publishing updated owned content and correcting misinformation across third-party sources

Winning is not just about visibility, it's also about controlling the narrative

Sometimes I take sales calls even when I know the person is not qualified.

Before you think that’s dumb, let me explain.

I don’t do this all the time.

I only do it when I have spare time and when I genuinely believe I can add value.

Why?

Because I’ve been in their shoes.

Ten years ago, I didn’t know anything about SaaS marketing or marketing in general. I just wanted to talk to people, learn, and get guidance. But the response was often:

“You can’t talk to me unless you can afford it.”

And I couldn’t.

I remember how bad that felt.

Even worse, I remember being sold services I didn’t need by people who just wanted to close a deal. I spent money I couldn’t afford, followed advice that wasn’t right for my stage, and it set me back.

That experience stayed with me.

So today, when someone books a call and I know my service isn’t right for them, I sometimes still take the call.

Not to sell.

But to tell them not to buy.

This happens more often than you’d think.

People want to work with me because they like my content or profile, and I tell them:

“You don’t need us.
 You don’t need any agency at this stage.
 You need to do something different.”

Could I take their money? Yes.
 Do I need to? No.

I’m fortunate. My businesses are doing well. I have healthy cash flow. I don’t need a few thousand dollars from someone if I know it won’t help them.
Instead, I spend 20 to 30 minutes guiding them in the right direction.

I don’t make money from that call.

But I gain trust.

And very often, that call becomes the start of a real relationship.

Years later, I’ve had people come back and say:

“You helped me when you didn’t have to.
 We just raised 50M and now I want to work with you.”

Not everything is transactional.

It’s easier to say this when you’re in a comfortable position, but still:

Don’t be a predator.

Don’t sell to people who don’t understand marketing just to make quick money.

They’ll churn.

And they’ll remember you for the wrong reasons.

Play the long game.

ChatGPT ads are coming. Paid search just entered the chat.

Ads are reportedly coming to ChatGPT’s free tier and $ 8-per-month tier, appearing as sponsored placements at the bottom of search results.

Testing is expected to start in the US as early as next week.

What’s most interesting to me isn’t the ads themselves, but the shift in perception:

How will users interpret AI responses when ads are present?

Where does trust begin and end when answers and ads live in the same interface?

Does this blur the line between assistance and influence?

At House of Growth - AI Led Growth Agency, we’re already thinking about how brands can leverage GEM to capture full demand inside ChatGPT before this becomes as competitive and expensive as Google Search.

Really curious to see how this reshapes organic search as we know it.

👉 Link to the announcement in the comments.

You don’t find message–market fit from 30 days of LinkedIn posts

Some people are claiming you can find message–market fit by posting on 

LinkedIn for 30 days and running a few events.

I strongly disagree.

Here’s why 👇

First, you don’t control distribution on LinkedIn.

You don’t choose who sees your message. That alone makes it a weak environment for validating whether a specific market resonates with a specific message.

Second, likes are not validation.

Getting 20–25 likes on a post doesn’t mean people resonate with the problem you’re solving—let alone the product you’re selling. Engagement ≠ intent.

Message–market fit requires scale and signal, not vanity metrics.

This is why I prefer email for message testing:

I control who receives the message

I can test fast
I can test at scale
I typically send a message to 1,000 targeted contacts.

 If there’s a strong response there, then we might be onto message–market fit.
There’s also a bias problem people don’t talk about.

When you validate ideas on LinkedIn—especially with a warm audience—people want to be polite.

 They know you. They don’t want to shut you down. So they say, “Yeah, this is interesting,” even when they wouldn’t buy.

A cold reply from someone who doesn’t know you?
That signal matters far more.

So yes—post on LinkedIn. Build authority. Start conversations.
 
Just don’t confuse content engagement with message–market fit.
They are not the same thing.

If you are a B2B SaaS company and you are still using clicks as your primary search KPI, you are measuring the wrong thing.

That approach is old school, and search has moved on.

Search today, especially in the AI era, is less about clicks and more about visibility and influence.

Here is how we think about it in the House of Growth - AEO Agency

1️⃣ Visibility on high intent prompts

We start by identifying the bottom of the funnel, high-intent prompts. These are the prompts that actually matter for revenue.

For each prompt, we track a simple but powerful signal.

Is our brand mentioned, yes or no?

If you are not visible when buyers are actively evaluating solutions, clicks do not matter anyway.

2️⃣ Position in the response

Not all visibility is created equal.
The next question is whether we are mentioned at the top, in the middle, or at the bottom of the answer.
Being listed first dramatically increases exposure. This is very similar to ranking first in a top tools listicle, where the brands at the top receive the most attention.

3️⃣ Citations and narrative control

This is the most overlooked metric.

We track whether AI is citing our content when mentioning us, or whether the narrative is coming from third party sources like G2 reviews, old Reddit threads, or competitor blogs.

Citations matter because they determine who feeds AI the source of truth about your brand.

You do not want a situation where you have visibility, but the story about your product is written by everyone except you.

The takeaway

Modern search KPIs for B2B SaaS are no longer about traffic volume.
They are about being present in the right prompts, being visible at the top of answers, and being the primary source that AI trusts for information about your brand.

Clicks are a lagging indicator.

Visibility is how demand is captured today.

Stop letting your competitors control the narratives inside ChatGPT

👇

ChatGPT isn’t "hallucinating" about your SaaS. It’s improvising because your website is a ghost town. You are not training AI with your own story.

Here’s the harsh reality:

LLMs are prediction engines. When you leave gaps in your digital footprint, the models fill them with whatever they can find: competitor comparison pages, angry Reddit threads, or 3-year-old press releases.

If you want to control the narrative in the age of AEO (Answer Engine Optimization), you need to spoon-feed the models.

You need to move beyond marketing fluff and build a "Source of Truth" architecture.

Here are the 3 types of pages I would build today:

- About us: Make sure that it's very clear on what your company is doing, who is your ideal ICP etc. Avoid using fancy language to impress your investors.

- Comparison pages: Control the narrative by owning the comparison-related queries. If you don't do this, someone else will do it, and AI will spit out the wrong information about your company.

- Integrations page: People don't just search "best project management software anymore; they search " best project management software with integrations to x". It's time to surface your integration docs and make them visible to search

If you don't provide the language, the model will generate its own. And I guarantee you won't like the version it writes.

taplio

The Battle

Taylor Scher

John Ozuysal

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taplio

The Battle

Taylor Scher

John Ozuysal

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}John Ozuysal's LinkedIn Performance

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