That skill is potentially worth millions.

And with the right technique, anyone can copy it fairly easily.

I call it symptom mapping, and I learned it very early in my inbound content marketing days when I was strategizing about how to attract new buyers through SEO.

I learned it through this metaphor, which I’ll repeat for you:

When you are sick, you start by listing your symptoms. Burning in your chest, acid coming up after meals, bad sleep. You Google them and learn it’s probably acid reflux. You also learn there is a solution for it called antacids. And then you start figuring out which brand you should buy to solve your problem.

That’s a direct line: symptom > problem > solution > brand > solved. All of them named and understood.

Very clean journey.

B2B works the same way. Just with a messier journey and stretched over years potentially.

You start noticing something that annoys you again and again. You hear someone put words to it and you start to understand the actual problem. Time passes, you see more people talking about it and you develop affinity for a specific way of solving it and a brand that solves it that way. And one day in a meeting, you put forward the idea that you should solve this business problem this way with this product.

The cadence is the same and we can use that to pull buyers who suffer the symptoms toward the problem we solve.

How symptoms look in B2B

Let me show you with some examples.

Payroll Responsible pains

• We have way too many payroll errors and it’s time-consuming.

• I waste too much time on local tax and compliance rules every month.

• We have to start payroll on the 19th to make it and there are always corrections.

Sales Leader pains

• We never know if we’re going to hit the target before the 31st.

• I spend more time collecting data than leading the sales team.

• My sales reps keep complaining about systems, reporting and data inputs.

Park Manager pains

• Our systems went down 3 times this Saturday and it created 30 minute queues instantly.

• We use 4 people at the entrance to apologize for the queue and scan tickets by hand.

• We miss so much extra revenue because our system is so damn slow for each sale.

Notice how each one is specific, personal and job-specific. That’s the point. It means you have a target audience to talk to.

How can you use this in B2B?

When we start using symptoms in our marketing, we’re doing something a lot of companies have trouble with. We stop talking about ourselves. Symptoms can never be about us. They’re disconnected from our product.

The symptoms become triggers that pull people into a bigger narrative about the problem and the solution. When you use them for your advantage, you can start attracting buyers who weren’t necessarily looking to solve the problem the way you suggest, but now they’re listening.

The mechanic is very, very simple. You pick one symptom, wrap a small story around it, and spread it across channels.

Like this:

“We never know if we’re going to hit the target before the 31st.”

When we speak to the market, one of the biggest pains is their inability to forecast their sales. They have to report on gut, and that forces pressure all around the sales organization.

Notice the symptom is in their voice. The story around it starts adding layers to that specific pain. You give them a vocabulary, and you let them know you understand their situation.

Then you take that and spread it out.

Ads

Create an ad with the symptom. It can be a talking head, graphic or plain text. When you spread all your symptoms like this, some of them pop off, and then you know what your audience actually reacts to. It’s one of the faster market feedback loop you can deploy.

Social posts

Get your thought leader to put more words to it in a LinkedIn post. Don’t go into solution language. Unveil the problem and the pain you relieve. Run the best ones as thought leader ads against your audience. Again, direct market feedback.

Blog posts

Reuse the best ones for blog posts. Symptom-driven posts don’t rank for solution keywords. They rank for the language buyers use when they ask AI for a solution. That traffic is smaller and further from buying, but it converts well once it lands. And your sales reps can use the posts to elevate conversations by adding value and perspective.

Website

Place the symptoms directly on the website. It’s borrowed language from the buyer themselves, and when you nail it, it shows you understand them better than anyone else in the category.

Here are two examples from a recent client project. I changed the text around it to not disclose the customer as we still are woking on it.

In the problem section, I used three personas, each with one sentence someone in that role has actually said out loud:

On another page, I stacked three symptoms from the same persona so a sales leader reads them and thinks "that's me, that's me, and that's definitely me":

You really need to know your buyer

This only works when you are tight in your market. If you sell the same product with the same value props to multiple segments, it breaks. Because the language isn’t tied to your solution, it’s tied to their pain. And if the buyers don’t look alike, it will completely miss the mark.

Remember my three examples from earlier. Here’s one symptom from each:

• We use 4 people at the entrance to apologize for the queue and scan tickets by hand.

• We never know if we’re going to hit the target before the 31st.

• We have to start payroll on the 18th to make it, and there are always corrections.

Because they’re persona-specific, you cannot run these across all segments. Either you have to segment your market very tightly and understand the buyer in it, or you have to create multiple segments each with their own set of symptoms.

If your market is wide enough, I will always go for the first. One buyer persona, in one market, is the gold standard for doing marketing where you talk directly to everyone in your chosen segment. But also rare.

So how do you find these symptoms?

I decided to save my tactical 9 step process for the next newsletter. It also comes with a Claude Skill I developed that will help you create these in the right kind of language.

I’ve just put up the last gear for a conference in New York. And then I’m done as CMO at MapsPeople. It was the last job on my to-do list. Now I just have a bunch of days in the big apple for myself. Roaming between skyscrapers and thoughts about my future.

That was 6 months ago today. Half a year.

And now I know. What I’m gonna dedicate my energy to.

When fireworks sounded us into a new year, I thought it was all about buyer enablement. Helping others making it easy to buy from them.

I’ve been writing about that in this newsletter some time now.

I even started a consultancy to help companies with it.

But every engagement ended in the same place. Companies came to me to fix how they talked to buyers. To answer their questions better and lower the buyer friction.

And every time, we ended up doing something else first: defining their market, mapping their ideal customers, nailing their value props, choosing how to position themselves. Building their GTM platform, as I like to call it.

Because you can’t answer your buyers’ questions if you don’t know who you should attract. Every message becomes a compromise then.

Once they had that clarity, the next move was obvious. Pick a market and win that first. Run a focused GTM motion against a list of ideal buyers.

And that’s when something clicked.

See, I had a lot of spare time after New York. So I started learning. I read, watched and listened to more go-to-market AI content than should be legal without a prescription. And my builds and experiments stacked even higher.

My biggest learning is this: in GTM AI, context is everything.

The more context you can give the LLMs, the better they work for you. On your positioning, your ICP, your writing style, your channels, your templates.

And that’s exactly what I’d been building for my clients with the GTM platform.

Perfect GTM context.

So when they wanted to run marketing against a list of ideal buyers, I felt right at home. I’ve owned that motion in 3 separate companies and I wrote a book about it. And with my new knowledge about AI, I knew what to build to make that work at a speed and depth that wasn’t possible just a year ago.

The tool I always wanted for myself.

Here’s what I built.

When you work a finite market, a list of named ideal customers, every account matters. You have a fixed number of them. You can’t afford to show up generic, burn a contact and move on. So you do the hard work. Spending time understanding their challenges, figuring out a way in, how to provide value and strategize for each account.

That used to be expensive, messy, and slow. And it kept lots of companies from even attempting to do it.

AI can solve for that.

All you need is GTM context and 3 agents.

Research Agent — An agent that does deep research on your ideal buyers. It creates an account overview, pulls industry insights, maps personas and creates a perfect research profile for each account on your list.

Strategy Agent — Then the strategy agent takes over. It looks at the research and plans an approach based on findings. It maps their challenges to your value props and determines which fits best. It understands your case studies and aligns what content you could use. And maps it to each stakeholder you should reach out to.

Content Agent — Here something magical happens. The content agent sees the research and understands the strategy. So it builds talking points, outreach messages, pitch deck copy and landing page outlines. 100% personalized for that account and stakeholder. And it tells you the reasoning behind it all.

With those 3 agents alone, you understand the account, have an approach figured out and personalized content to reach out. Here is an example of how it’s coming together:

Working 500 accounts this way was reserved for enterprise deals a year ago and required 4 people or at least 4 different skillsets and tons of time. Now agents are running the full process and the only thing holding you back is how fast your team can put these assets to use and connect with your accounts.

This is a wild, wild time to be in business 🤯

Context is EVERYTHING

To produce great results with AI, context matters more than anything. Instructing the AI what good looks like and how you see the world is key to great outcomes.

I actually think that a good context library is going to be the difference between teams using AI and teams winning with AI.

Here is how I’ve built my library and what is being pulled. I’m still making iterations and adding stuff, but this is the base.

Se more at lowfriction.io

Enough self-promotion.

This excites me. And I hope you too.

My newsletter is going to take a slightly different approach to buyer-first GTM going forward.

I am going to talk more about AI.

I will dive more into the internal GTM side and how to optimize for the buyer.

I am thinking more about account-based approaches.

But overall, this is my thinking space, so it’s not going to be a product newsletter. Most of you on this list came from reading my book Cloud Republic. That is the constant here. How to make buyers see you as the only obvious choice.

The paths to that goal are just widening as we adopt AI.

Subscribe now

6sense, Demandbase, Terminus. They monitor thousands of accounts, track intent signals, and tell you who’s surging into market. The entire ABM industry is built around discovery. Find the accounts. Detect the signals. React.

But I didn’t need discovery. I already knew who should buy.

If you sell to a well-defined market of 500 or 1,000 accounts, the question “who should we talk to?” was answered before you ever opened a tool. You know the companies. You know the problem. You probably know the job titles.

Your bottleneck isn’t discovery. It’s activation.

And with it ABM takes a different shape.

Two motions, one label

There are two fundamentally different ways to run ABM, and the market barely ever differentiate between them when we talk about ABM.

Signal-first ABM starts wide. You load thousands of accounts into a platform or filters them from firmographics. You monitor intent signals: web visits, content downloads, keyword surges. The system tells you who’s “ready.” You react.

List-first ABM starts with business design. You built your product for a specific problem. You know who gets the most value from it, who it’s easiest to explain to, and who’s most willing to buy. So you build a list of those accounts and activate ads, outreach, content, and events against it. You create demand instead of waiting for it. When you’ve exhausted that market, you open the next ICP and repeat.

Signal-first ABM is a pipeline motion. You monitor thousands of accounts, surface whoever is showing intent, and convert them. The objective is to capture in-market demand this quarter. It has a short-term focus.

List-first ABM is a market ownership motion. You know who gets the most value from what you’ve built, who it’s easiest to explain to, and who’s most willing to buy. You build presence with those accounts so that when the pain is big enough to act on, you’re already there. The objective is to own your market over time.

They can even co-exsist and solve for different parts of your growth equation.

But when you look out into the market, most of the ABM playbooks, conference talks, and tool demos you’ve seen are signal-first. That’s not an accident. Two things drive it.

First, most companies treat ABM as a short-term leadgen tactic. We need leads now, not tomorrow. So marketing gets to work. ABM becomes a leadgen tool, not a fundational GTM model everyone works by.

Second, the tools are built for scale, not focus. ABM vendors need enterprise contracts to grow. Enterprise contracts mean monitoring 10,000+ accounts, not running focused plays on 500. So the tools were designed around breadth — more accounts, more signals, more data. The small-batch, list-first motion isn’t a product they can sell at that price point.

And as they lead the conversation and most marketers are pressured for leads, this is where we end up.

The problem with letting a system pick your accounts

Even when signal-first works, it produces a different kind of list than the one you’d build yourself. And often, a worse one.

Intent tools are great at firmographics. They’ll filter by industry, size, geography, job titles. But within that filtered universe, they can’t tell the difference between an account that desperately needs what you’ve built and one that looks identical on paper but has no use for it.

At MapsPeople, where I led GTM, we sold indoor mapping to Workplace Management SaaS companies whose products interacted with physical space. Desk booking platforms needed us. Employee survey tools didn’t. Same industry, same size, same stakeholders. The difference was a product architecture decision that lives nowhere in any database.

And even for the companies that did need indoor maps, very few was searching for “indoor mapping SDK.” The market was too small, too niche. There was little search volume to monitor. No surge to detect. The intent signal simply doesn’t exist when you’re in a market with very few players.

A tool could find Workplace Management SaaS companies. It could not distinguish who had the need and who didn’t. And it could not tell us when they were “in-market”.

So we built the list ourselves. Not because we couldn’t afford the tooling. Because we had better targeting logic than the tooling could express.

Six scenarios where intent tools are structurally blind

There are GTM situations where signal-first ABM doesn’t just underperform — it has nothing to work with. The signals don’t exist.

1. Category creation. You’re building something new, so no one is searching for your solution yet. You might pick up some intent signals around the problem, but that’s not in-market intent. It’s discovery. The accounts surfaced are nowhere close to a buying decision.

2. Competitive displacement. Your prospects aren’t “in-market.” They already have a solution. They’re not googling alternatives. You need to create switching intent by showing them what they’re missing.

3. Post-funding sprint. The board gave you 50 target logos. They want pipeline in 90 days. They don’t care about “surging accounts.” The target list is the strategy and everything else is execution against it.

4. Inbound supplement. Inbound is generating leads, but not from the accounts you actually want. List-first ABM lets you layer a focused motion on top. Going after named accounts directly instead of hoping they show up.

5. Ecosystem or platform selling. You’re selling into another company’s ecosystem or partner network. Your ICP isn’t defined by firmographics, it’s defined by who’s building on a specific platform or using a specific tool. No intent filter can express “companies building on Shopify who need X.

6. Niche markets with no search volume. Your category is so small that intent platforms don’t have enough data to model anything. They need thousands of people searching to detect a “surge.” If 15 people a month search your keyword, the system has nothing to work with.

In every one of these cases, intent data has nothing to measure. You’re not failing to use the tool correctly. The tool is measuring the wrong thing.

ABM is a GTM decision, not a tool decision

ABM works. The question is whether you’re using the right motion for your market.

If your buyers are actively researching and you need to intercept them, signal-first makes sense.

But if you already know who should buy. If your ICP fits on a spreadsheet. If your market is finite. If your buyers aren’t googling their way to a solution. Stop paying for systems that “find” accounts.

The best account list you’ll ever have isn’t the one a platform generates. It’s the one you build because you understand your market better than any algorithm can.

Every time I get to work with a new client, I bring this up and it turns into a messaging lesson.

Because most don’t know the difference between features, capabilities and outcomes.

Or more precisely: they don’t know what capabilities really mean.

So here’s the lesson.

The two extremes that kill your messaging

Extreme 1: Feature-led messaging.

“We have real-time dashboards, SSO, API integrations, and custom workflows.”

Cool. What do I do with that? The buyer has to translate your feature list into their own problem. Most won’t bother. They’ll bounce.

Extreme 2: Outcome-led messaging.

“Grow revenue. Reduce churn. Transform your business.”

So does every other vendor on my shortlist. When everyone promises the same result, nobody stands out. Research shows 40 to 60% of B2B deals end in no decision. Not because a competitor won. Because the buyer couldn’t confidently choose.

Both extremes create the same result: the buyer doesn’t see themselves in your product.

The missing layer: capabilities

There’s a level between features and outcomes that most SaaS companies skip entirely.

A feature is what your product has.

A capability is what your buyer does with it.

An outcome is what happens in their business because of it.

Features are ingredients. Capabilities are the meal. Outcomes are not being hungry.

A single feature rarely solves a problem on its own. Often it’s multiple features that unlock one or more capabilities. And those we can map directly to a problem worth solving.

Case: Evercam

Here is a problem you never thought of.

You have a construction site and cameras monitoring it 24/7. You have lots of moving parts and sometimes incidents occur. You need to be able to pinpoint fault, security, compliance with rules and make sure it never happens again. So you wanna catch all incidents. But sometimes you don’t know exactly when what happened. So you have to go through lots of video material.

Evercam does construction site visibility and can solve that problem for you:

Features

• Camera hardware

• Object detection

• Event timestamp

Capability — Incident capture and investigation. When a car crashes into the construction site, you have all the evidence you need without having to look for it.

Outcome — Fewer legal fees, fewer manual hours, better security = you save money

Messaging for Evercam with and without the capability:

Features + Outcome:

With Evercam, all cameras have object detection and event timestamps so you don’t have to spend hours on manual reviewing video and fighting legal cases without evidence.

Capability + features + outcome:

With Evercam, you get Incident Capture and Investigation. It automatically detects objects and timestamps events, so you don’t have to spend hours on manual reviewing video and fighting legal cases without evidence.

The first leaves out the capability, and even if you can do the math in the head because you know the problem, it requires more of you.

The second makes it clear what your new capability will be if you get Evercam. It feels more solid and easier to buy. It’s something that’s already built for you and you just use it. Not separate features you need to manipulate for your use case.

But a lot of times, people are trying to solve one specific problem when looking at your software, so they don’t have the context of the pain. Maybe the buyer is looking for Evercam because they need to do remote site management and supervision. So their pain is using time driving around to all building sites and spending lots of human hours on that. Object detection and timestamps means nothing to them. But they know that the team also spends lots of time on incident management, so that might be another value the software could add.

Capabilities add clarity to what problems you solve.

And if you wanna visualise the formula, it looks like this:

Capabilities remove buyer friction

If you’ve been reading this newsletter, you know I see everything through the lens of buyer friction. This one is no different.

Feature messaging creates cognitive friction. The buyer has to figure out what your tech specs mean for them. That’s work you’re making them do.

Outcome messaging creates trust friction. Big promises without a visible mechanism feel like marketing fluff. When your homepage says “grow revenue 40%” and buyers can’t see how, they don’t believe you.

Capability messaging removes both.

It shows the buyer the action they’ll take. That’s the thing they can evaluate. The thing they can picture doing on a Tuesday morning. And most importantly, it’s the thing your champion repeats in the room when you’re not there.

Nobody walks into a buying committee meeting and says “it has real-time dashboards.” Nobody says “it’ll grow our revenue.” What they say is: “We can finally see which accounts are heating up and act on them before they go cold.”

That’s a capability. And it transfers belief. The buyer goes from “sounds nice” to “I can see how that would work for us.”

How do you find your capabilities?

Firstly, you need to understand the problems you are trying to solve. People buy because they have something they want to solve differently. When you have that, your capability is the language of what your buyer now can do to solve that problem.

Here is your worksheet.

Problem: “We are drowning in manual hours searching through video for incidents”

Capability: “Incident Capture and Investigation: Get automatic object detection with timestamps from all of your cameras”

Features: Object Detection, Timestamps, Incident Log, Auto-clip of video.

Outcome: Company X saves 16 hours monthly per construction site they used to use rewinding video and caught 40% more incidents in year 1.

This lets anyone follow the story step by step and makes your value crystal clear.

Now, I’m not saying this is a small task. It requires you to understand who you are talking to, what their daily jobs are, what problems they face and interpret how you solve for them. This is product marketing work at its finest. But between product discovery, building the product and talking to customers, you have the information. Now it’s about channelling it forward so you get the reward of telling the market you solved a problem for them.

Capabilities is not about removing features or outcomes.

Features are great for checklist marketing. Buyers need to know if you can do this specific thing or integrate into their stack.

Outcomes are great for high-level understanding. Buyers want to see your claims and how you could move their needle.

But capabilities is where you translate into how they will use your product on a Tuesday morning.

If your buyer can’t picture themselves using your product before they talk to sales, you have a capability language problem.

And that problem is costing you deals you’ll never know about.

GTM engineer, GTM tools, GTM orchestration.

And every time I read some of it, I get frustrated. It’s reduced to a shallow version of what GTM strategy actually is.

There are 2 patterns I keep seeing where GTM is watered down. I’ll show you both, then give you the full picture most posts are missing with my GTM Cheat sheet.

1. Clay/Claude Code + AI + Outbound = Go-To-Market

Most “GTM Engineer” content on LinkedIn is a cover story for sending more cold outbound. Just faster with AI and Clay or Claude Code. Clay popularised the GTM Engineer role and I actually love the concept.

What once was hard is now easier than using a Canva template. But when 90% of the content is “here’s how I send 10,000 personalized emails a week with AI”. That’s not go-to-market strategy. That’s one tactic inside one channel.

2. Tech stack = Go-To-Market

The other is the tech stack. Clay, Claude Code, Attio and Slack nicely stacked in a graphic, keeps occupying my feed with GTM as the premise. Some take it further and draw up their workflow diagram between the tools, but the outcome is the same. It’s not GTM strategy. You need tools, but it’s the same as showing someone you kitchen and calling it a recipe. The tools serve the GTM strategy, they are not the strategy.

Where did the rest of GTM go?

Both patterns draw from the same source. The GTM Motion: How you connect with the market.

And the motion matters.

Without it, nothing happens.

But what’s missing is the GTM Platform: How you plan to attack the market.

The motion is how you reach people. The platform is why they should care when you do.

That’s the part that puts strategy in Go-To-Market strategy. I’ve spent years consulting 50+ SaaS companies and running GTM from the CMO chair in two others.

Here’s the framework I use to make sure both sides are covered.

The GTM Platform in 89 words

The Platform has three stacks that work together.

Borders define the market you can win. Your core belief, the problems you solve, and who you serve.

Positioning is how you stand out within those borders. Your category, differentiation, and segmentation.

Packaging is how the market experiences all of it. Narrative, messaging, value props, pricing, and buying process.

All of this should be in place before you pick a single channel or run a single tactic The bigger the team, the more this matters. Every gap in the platform becomes internal friction later.

Let me show you what I mean with two examples.

Two examples of how the platform drives the motion

Example 1: The AI-Agent CRM

Borders — You decide to solve the problem of keeping track of customer data and acting upon it. Your controlling idea: doing it 100% with AI agents. Not “AI-assisted.” Not “AI-powered.” The agents ARE the CRM.

That controlling idea forces your ICP. If you say “100% AI agents,” you can’t sell to enterprises with 200 AEs and a Salesforce admin team. You need buyers without sunk cost in the old way. Tech companies with 10-50 employees fit. They adopt fast, have less legacy CRM baggage, and their sales teams are small enough that an AI-first approach doesn’t threaten an army of existing users.

Positioning — You are going to lose if you compete with Salesforce and their AI solutions. So you have to split the CRM category and talk about it differently, putting all the weight on “no human data entry” messaging. Legacy CRM can’t follow you into that messaging.

Every other CRM makes humans do the work and calls AI a feature. You flip it. The AI does the work. Humans review. Segment by team maturity with AI tools. Target teams already using AI in other workflows. They won’t need convincing that AI can do real work.

Packaging — Narrative: “Your CRM should work for you, not the other way around.” Lead with the pain everyone knows. Every sales team hates logging. Start there.

Offer: Free tier with limited AI agent actions. Paid = unlimited actions + custom agent workflows. Pricing: low seat cost + usage-based credits. Low risk to try, and revenue scales with value delivered, not headcount.

Buying process: self-serve signup, connect your email and calendar, watch agents populate your deals and accounts.

Now watch what happens to the motion.

Product-Led Growth is the obvious choice. But the platform decisions above constrain HOW you run PLG:

• You need credits to let people experience value. That’s upfront cost per free user. You need funding or very efficient acquisition.

• Self-serve buying means your website, onboarding, and in-product experience carry ALL the weight. No AE to save a bad first impression.

• Usage-based pricing means expansion revenue is automatic IF the product delivers. Your growth loop becomes: try, see value, use more, pay more, tell others.

This connects directly to business strategy. If you’re bootstrapped, you cap free credits tightly and focus on a narrower ICP (say, only agencies) where conversion rates are higher. If you’ve raised, you afford more generous free tiers to grab market share. The platform and motion feed back into how you fund the company.

Example 2: Operations for AirBnB Hosts

Borders — You’re solving the problem of running financials and operations for AirBnB hosts managing 20+ properties. Spreadsheets, multiple tools, no single source of truth.

Your controlling idea: “The AirBnB host life without the hassle.” You’re not building accounting software. You’re building a lifestyle enabler for professional hosts.

Why 20+ properties as the floor? Below that, spreadsheets still work. Above 100, they likely have staff and custom solutions. The 20-100 range is where the pain is sharpest and the willingness to pay is real.

Notice: the controlling idea is a lifestyle promise, not a feature promise. You’re not competing on “better reports.” You’re competing on “get your weekends back.” That shapes everything downstream.

Positioning — Category: Instead of going into the classic accounting software or property management categories, you wanna go very laser focused “Operations platform for professional AirBnB hosts.” You’re specific to AirBnB hosts because their problems are unique: dynamic pricing, guest communication, cleaning schedules, seasonal demand.

Generic property management tools serve landlords, real estate agents, and hotels. They’re broad. You’re laser-focused on the AirBnB workflow. Every feature maps to a host’s actual day.

Segment by geography first. AirBnB hosting density varies wildly. Start where the biggest pool of 20+ property hosts exists. Pick ONE region to win first.

Geography matters here in a way it didn’t for the CRM. AirBnB hosting is tied to local regulations, tax rules, and seasonal patterns. If you try to serve all markets at once, your messaging fragments and your resources spread too thin

Packaging — Narrative: “You became a host for freedom, not for spreadsheets”. Messaging: lead with time saved and money found. “Hosts save 12 hours a week and find an average of $X in missed deductions.”

Offer: all-in-one. Financials, cleaning scheduling, dynamic pricing insights, tax prep. Bundled, not modular. Because the value prop is “no hassle.” If you sell modules, you’re creating the very complexity you promised to eliminate.

Pricing: flat fee per property, per month. Not per seat. The host IS the user. Pricing per property aligns cost with the scale of their business. Dead simple to understand.

Buying process: This audience is NOT tech-savvy in the SaaS sense. They don’t want to “configure” anything. Onboarding has to feel like “connect your AirBnB account, we handle the rest.”

Now watch what happens to the motion. It’s completely different.

PLG is NOT the obvious choice here. Why?

• The ICP doesn’t hang out on Product Hunt or Twitter/X. They’re in Facebook groups, AirBnB host forums, local meetups, and YouTube channels about hosting.

• The product requires connecting real financial data. That’s a trust barrier to just connect to see how it works. They want to talk to someone first.

• The deal size (20+ properties times a monthly fee) is meaningful enough to justify a sales-assisted motion.

The right motion is community-led + sales-assisted:

1. Community-led acquisition. Be present in every AirBnB host community. Not with ads. With genuinely useful content: tax tips, pricing strategies, operational templates. Build trust first. Sponsor podcasts and YouTube channels the pro AirBnB hosts listen to.

2. Sales-assisted conversion. Once someone is interested, a short guided setup call. Not a hard sell. A “let us connect your account and show you what we find.” The AHA moment IS the onboarding.

3. Referral-driven expansion. Hosts know hosts. A referral program with real incentives (free month per referral) is your growth engine. This audience talks to each other constantly.

This feeds back to business strategy too. Community-led + sales-assisted is slower to scale but more capital-efficient. You don’t need to burn cash on free credits. You can bootstrap this if your market entry is tight enough. But it also means you need patience and a content engine, not a growth-hack playbook.

That’s why you can’t copy playbooks of LinkedIn

The platform doesn’t just “inform” the motion. It constrains it. The CRM’s tech-savvy ICP and low-risk free tier enabled PLG. The AirBnB host’s non-tech ICP, trust barrier around financial data, and community-driven behavior demanded a completely different approach.

If you pick the wrong motion for your platform, the unit economics break, the buying experience feels off, or you’re reaching the wrong people in the wrong way.

So when you hear someone say “Steal my GTM strategy” and it’s how to do outbound with Clay + AI, understand: It’s one tactic, inside one channel, inside one motion. Not a GTM strategy.

With that said, there are tons of cool tactics and plays I read about every day on LinkedIn and save for my own swipefile. But I always crossmatch with my platform before deciding if this is actually something I could deploy.

Their platform isn’t your platform. Their motion was built on decisions you didn’t make. Take inspiration from it. But don’t copy it.

Being able to see that difference is what separates a manager/director from a VP/CMO. You gotta understand the strategic layer to lead GTM, not just run it.

I’m recording a full video walkthrough of every moving part in this framework.

That was the Chief Revenue Officer’s words directed at me during a leadership meeting.

Three weeks into my new job as CMO.

I had run analysis on our demo leads and showed a graph of how many hours we spent on badly qualified leads.

For me it was low hanging fruit. A quick win to make serious impact in the first month on the job.

For him it was a personal attack.

Like I aimed it at him and his responsibilities.

I failed hard that day.

My objective was to optimize the business, not single anyone out. But I forgot something darn important.

I see the world outside-in. Buyers first. Most don’t.

So what I see as a slam-dunk business case, others see as a surprise attack on their way of work.

I should have warmed up the room to what they were about to see.

Buyer behaviour in our context. But they felt I put a microscope to their job.

Lesson learned.

Since then I built myself a cheat sheet.

Rational, research-backed, arguments to build a GTM that adapts to how buyers actually wanna buy today.

That fight holds enough energy to light a small Danish west coast town in the dead of winter.

Sales leaders protect their pipeline. Marketing don’t wanna lose leads. Leadership worries about “giving away” information.

The evidence supports the case. You subscribe to my newsletter, so you already know.

But you need more than suggestions when you start challenging “the-way-we’ve-always-done-it-mentality”.

You need them to see the world as you see it.

So here is your cheatsheet.

7 objections with data-backed arguments. Use them.

“But we’ll lose leads if we show pricing.”

You’ll lose submissions. You’ll gain pipeline.

HockeyStack found transparent pricing generates 39% fewer form fills. But 1.7x more pipeline. The leads you “lose” were never going to buy. They were just curious about cost. Now they self-qualify out before wasting your AE’s time.

Read this article here or watch the 6-min video

“Enterprise is different. You can’t self-serve a €500K deal.”

You’re not removing the demo. You’re removing the demo as the only path to information.

Even enterprise buyers want to self-educate before the call. Gartner says 83% of the buying journey happens before talking to sales. That includes enterprise. The question isn’t “should we have demos?” It’s “should demos be the only way to learn about our product?”

You should read Stop sending buyers to “Book demo” (do this instead)

“Competitors will see our pricing and undercut us.”

They already know your pricing. G2. Reddit. Existing customers. LinkedIn posts. AI search. Don’t believe me? Just ask ChatGPT.

64% of C-suite executives say they are less likely to purchase software if a vendor gates pricing. They’re not comparing you to competitors on price. They’re crossing you of the short-list for hiding it.

If gated pricing is your only moat, you have a positioning problem. Not a pricing problem.

“Our pricing is too complex to show.”

You don’t need a checkout page. You need a signal.

Show ranges: “Companies like you typically pay €15K-40K/year.”

Show starting points: “Plans start at €500/month.”

Show context: “We work with teams of 50-500. If that’s you, let’s talk.”

The goal is to help buyers self-qualify. Not to close the deal on the website.

Good thing I created 7 ways to have a pricing page without pricing →

“Creating all this self-serving content costs money.”

Yes. But content scales. Demos don’t.

A great video demo costs €3K once and serves 10,000 visitors.

A live demo costs €50 every single time in sales salary.

After 60 demos, the video has paid for itself. Everything after that is margin.

When you build self-serving content you are not only improving your unit economics, you are also investing in more potential buyers. 61% of B2B buyers prefer a sales-rep free path to buying.

And AI makes it way cheaper to create.

“Our demo IS the differentiation.”

Great. Then why are you limiting it to 30 people a week?

Buyers agree with you: 71% rate demos as the most influential resource in their journey. But here’s the gap: vendors produce demos averaging 15+ minutes. Buyers watch 5 minutes and 44 seconds on average.

Record the best version. Cut it by use case. Keep each under 6 minutes. Your buyers will show up educated and your AEs can get into selling instead of teaching on the sales call.

“If buyers self-educate, we’ll loose control of the narrative.”

They’re already self-educating. They’re reading G2 reviews. Asking peers on Slack. Watching competitor videos. You’ve lost control of the narrative whether you like it or not.

In fact, giving them a better way to consume a demo will recreate that control for you. Use the 60-6-60 framework you can find in this article here.

The choice isn’t “control vs. no control.”

It’s “answer your buyers’ questions vs. let the internet answer for you.”

In fact, answering your buyers on your website will help you attract more.

The death on top of the high friction hill

These arguments will feel like trying to steer a parked car sometimes. You will meet someone who is not willing to change. They would rather die on their high friction hill.

But most will listen to reason if you package it for their context.

• When someone cares about margins and efficiency, lead with the demo cost math. 42% less sales time per deal, 18% more revenue from the same traffic, 30% shorter cycles. This is a cost conversation. When they push back on switching costs, remember them about how this scales better than what you do today.

• When someone cares about pipeline and quota, lead with time savings. 40% fewer demos, but the ones that remain are higher intent. Calendars gets lighter and numbers get better. When they worry about pipeline shrinking, show the 1.7x pipeline research.

• When someone cares about lead volume, lead with conversion quality. Fewer form fills, but 1.7x more actual pipeline. The metrics that matter go up. The vanity metrics go down. When they flag top-of-funnel risk, point to the pipeline multiplier.

See this 6 min video for full context to why this discussion matters. And then share it with your team to build understanding.

Most B2B SaaS companies treat their demo call as the gateway to everything.

Want to see pricing? Book a demo.

Want to see how it works? Book a demo.

Want to know how we work with your industry? Book a demo.

The logic seems sound. More demos = more pipeline.

But here’s what the data actually shows: you’re spending sales time educating people who could educate themselves while losing the ones who won’t wait.

The price you pay is higher CAC, smaller deals and less revenue.

Let me walk through how we can calculate this. Step by step.

You can also catch the summary of the article as video here.

A directional model

There is no single study connecting all the dots I’m about to show you. The research exists in pieces. I pulled from multiple sources, layered in patterns from my own SaaS implementations, and built the bridges between them.

Every number has a directional basis. Where I estimated, I’ll tell you. And all sources are linked.

With that said, let’s walk through it.

Not everyone who books a demo wants to buy

We start with why people actually book demos. The most important thing to notice here is that most companies that use “book demo” to answer questions they do not give out elsewhere (like pricing) attract very different intent levels.

Some will argue that “pricing” is not low intent. But in most cases it is, because buyers use it as an early indicator about if we should keep looking at a product. Our pricing page gets 13x more traffic than our demo page and is one of the most visited pages on our websites.

When a demo is booked because you do not show pricing, even when it’s a good-fit buyer, the signal is still not a strong buying signal. It’s an information signal with low conversion rates.

I mapped out 16 reasons with matching intent level. Here’s what I found:

Look at that distribution. A huge chunk of your demos are low-intent information-gathering sessions. They’re not ready to buy. They shouldn’t need a 45-minute call with your AE to find out your pricing.

Intent level distribution in percentages

Knowing the reasons is useful. But to calculate the actual cost, we need to estimate how many demos fall into each bucket.

75% of your demos are with people who aren’t ready to buy. They’re gathering information that could be on your website.

The percentages are directional estimates. It comes from RevenueHero (1M+ demo requests), HockeyStack’s 2024 Benchmark Report (135 companies, ~$690M in spend), Maccelerator and patterns from my own SaaS implementations. But I wanna highlight this research in particular:

HockeyStack analyzed 31 million data points across 80 B2B SaaS companies. They only looked at transparent pricing vs gated pricing. What they found:

Transparent pricing generates 39% fewer form submissions but 1.7x more pipeline.

Fewer leads. Better quality.

Why? Because when you hide pricing, you attract “information” submissions. When you show it instead, you will see fewer bad-fit leads and more high-intent buyer submissions. That same effect applies to all self-serve content: High buyer friction dilutes quality.

What if you removed buyer friction from every demo entry point?

Let’s say you commit to lowering buyer friction across the board. You provide a self-service alternative for every question that currently requires a demo:

I excluded “Spam and bots”, “Curiosity clickers”, “Students/researchers”, and “Competitor scouting” because you don’t design your demo experience for those. But they will still be affected by the low-friction alternatives, which will keep some of them out of your demo funnel.

I also excluded “Ready to buy” because the lowest-friction path at that point is a human. A clear “Talk to a human” option covers it.

When you build low-friction alternatives for every demo-triggering question, and this happens:

A massive drop in demos from some intent categories.

The reduction percentages are directional estimates based on this research, this one and own experience.

The number to keep an eye on is the 51% reduction in total. This means that if we had 100 demos in the old model, we would only have 49 left in this low friction alternatives model. The majority of the ones we remove are information-seekers and validation leads. It’s the ones we don’t wanna spend same time on anyway.

The triple multiplier effect

This affects lead quality massively. We’ve removed 51% of the leads from the baseline.

The ones that get through to a demo are more likely well-educated, high-intent buyers. And that has an impact on two more numbers:

• Sales cycles get 30% shorter (Forrester 2023)

• Deals are 2.8x more likely to close at a higher deal size (Gartner B2B Buying Report 2023)

That “2.8x more likely” is a likelihood multiplier, not a price multiplier. It means educated buyers are three times more likely to close at a higher price point. Not that they pay three times more. I’m translating that into a conservative 15% ACV uplift. When buyers already know what they need before the demo, they commit to bigger packages with more confidence.

Educated buyers close faster. Spend more. Waste less of your sales team’s time.

These effects compound.

Let’s do the math for both models

We’ll track 100 people who need information as a cohort over 90 days. We’ll compare two models:

Demo-gated model: No self-service. Everyone needs a demo to get answers.

Self-service model: Comprehensive self-service content. Sales only talks to qualified, high-intent buyers.

Baseline assumptions:

• Average sales cycle: 84 days (Optif.ai‘s 2025 benchmark of 687 companies)

• Average deal size: €26K (SaaS Capital’s 2025 survey of 1,000+ private B2B SaaS companies)

• Intent level distribution matches the table higher up

• Win rates for each intent level:

  • Zero 0%

  • Low 5%

  • Medium 15%

  • High 40%

  • Very High 80%.

No research breaks down win rates by demo intent. What exists are blended B2B SaaS benchmarks that typically land between 20-30%, with a median around 21%. I’ve distributed that range across the five intent levels based on a simple logic: someone who booked a demo to check pricing closes far less often than someone ready to start paperwork.

The blended win rate in my model comes out at 18%. That’s below the benchmark range, and it should be. Most benchmarks count qualified opportunities. My cohort counts everyone who books a demo, including zero-intent noise and low-intent information seekers.

One important simplification. I’m using the same win rates in both models. In reality, the self-service model should produce higher win rates because buyers who reach a demo are better educated. But changing win rates and volume at the same time makes the comparison harder to follow and easier to challenge. So I held them constant to isolate the one variable that matters: the quality of demos, not just the quantity.

This means the numbers below undercount the real gap between the two models.

Model 1: Demo-gate.
100 people, 100 demos, 18 deals

Without self-service, every question requires a sales conversation.

All 100 people book demos. Sales talks to everyone, regardless of intent level.

The number of people comes from the Intent level distribution table. It shows what percentage of the 100 comes from each intent level.

Result: 100 demos produce 18 deals over 84 days.

Model 2: Self-service.
100 people, 60 demos, 18.5 deals

With comprehensive self-service, people get answers without sales time. Bad fits self-disqualify. Lower-intent buyers research until they hit the right intent to reach out. High-intent buyers book demos right away. And you will always have some who book a demo no matter their intent level.

49 demos instead of 100. The other 51 people who now didn’t book a demo don’t disappear. They self-serve. And they split into two groups:

Self-disqualifiers (40 people)

They find their answers on your site. Realize it’s not a fit. Leave without consuming sales time.

• 5 Zero-intent: Were never going to buy

• 21 Low-intent: Price too high, features don’t match, timing wrong

• 13 Medium-intent: Found a better-fit solution, discovered an internal problem

• 1 High-intent: Budget pulled, no buy-in

Self-educated buyers (11 people)

They research independently. Build internal cases. Compare options. Mature from lower intent to ready to buy. Return for demos when they are ready to talk.

11 Self-educated buyers return as High or Very High intent. They close at 45% (blended high-intent win rate). 11 demos produce 5 additional closed deals.

These return rates are educated estimates. No research tracks how many self-service buyers come back for demos by original intent level.

The logic: higher original intent means a higher likelihood of return. Someone who came in at low intent and found the pricing too high is unlikely to come back. Someone at high intent who just needed one more answer probably will.

The 11 new demos is added to the 49 and the 5 new closed deals to the 13.5 existing.

Result: 60 demos produce 18.5 deals over 84 days.

Sales cost baseline

The last thing to add to our comparison is sales costs. The main argument here is that you spend too much time serving people who are not ready to buy. That is what hurts your CAC. So to put economics behind it, we need to understand sales costs.

This is our baseline:

• Fully loaded AE cost: €100K/year (€48/hr). Wellfound puts the average B2B AE salary at ~€99.8K before benefits and overhead, so this is on the conservative side.

• Average demo time: 1.5 hours (including prep and follow-up). Gong analyzed 67,149 demos and found winning and losing demo time average 47 and 36 minutes for the live call. Add prep and follow-up and you’re at 1.5-2 hours total.

Cohort comparison

Here is the full comparison from the 2 cohorts.

What this actually means

By the end of 90 days, both cohorts produce roughly the same number of deals. But the economics are completely different:

1. Lower CAC. You spend 42% less sales demo time per deal. That’s real margin.

2. Larger deals. Educated buyers close bigger at the estimated 15%. They know what they want and are willing to pay for it.

3. Faster cash. A 30% shorter sales cycle means you collect revenue a month earlier. That’s cash flow.

4. Shorter CAC payback. If your sales part of CAC drops 42% and deal size rises 15%, you recover acquisition costs faster. That’s the number investors and CFOs care about.

5. More revenue. 18% more from the same input. With less effort.

This isn’t about doing more with less. It’s not about keeping leads from sales. It’s about growing profitable at the path of least friction.

In the era of “growth at all costs,” you could ignore this. Fill the funnel. Hire more AEs. Figure it out later. In the era of profitable growth, this is the difference between scaling and stalling.

So why isn’t everyone doing this?

I see two reasons:

1. Marketing isn’t measured on revenue. Their job is to create leads for sales. By every measurable angle, the high-friction model looks better. It generates more leads. You can’t fix this until you stop treating marketing and sales as separate entities with different goals and understand the full buyer journey’s impact on your business

2. Revenue leaders were trained on playbooks where early sales intervention was the goal. Buyer behavior and SaaS economic models have changed, but moving away from what worked earlier is difficult, especially when this new playbook isn’t considered best practice.

This is a strategic decision revenue leadership must make. The biggest objection I still hear:

“Our business will suffer if we don’t capture leads and instead give away our pricing and more.”

I’m here to tell you it’s not true.

If you don’t believe me, listen to the market leaders.

I ran a study of the 50 fastest growing companies of 2025.

50 out of 50 subscribe to the low-friction self-service model.

Not most of them. ALL of them.

Buyers want this.

The market leaders are doing it.

Why aren’t you?

The upside I left out

I tried to stay true to the numbers in each model. I didn’t add the 2 effects I’ve seen every time I’ve been part of making a buying journey self-served:

1. More inbound leads.

People like your brand more. They appreciate transparency. Your valuable content now affects search rankings (especially AI citations) which drives more great converting traffic. All of those effects will result in more inbound leads.

2. Cleaner pipeline.

Everyone feels the pressure of getting deals in, so reps add deals they hope will close, even when they know better. This bloats your forecast, breaks your percentages and wastes time on low-intent leads. With the self-service model, there are fewer bad deals to work on.

These are real bonuses, not included in the model above.

A last note on the numbers

These aren’t lab-tested figures. There’s no single study that connects all these dots (yet). This is a directional model. Built from the research that does exist combined with industry experience and informed estimates.

My goal wasn’t to hand you a CFO-ready ROI deck. It was to show that the model behind low friction self-serve works. Even when you adjust the inputs.

So challenge it.

I’m building a calculator where you can input your own numbers. If you want it when it’s done, write me at soren@lowfriction.io.

I’m part of a community of marketers who believe removing friction builds better businesses. If you find evidence otherwise, I want to know.

Conclusion: Your demo gate doesn’t protect your business. It hurts it.

The cohort analysis tells a clear story: Both ways produce similar deal volume over 90 days. But that’s also the only metric that is close.

• 40% less sales time

• 15% larger deals

• 30% shorter sales cycles

• 18% more revenue

The question isn’t whether you can afford to lower the friction for your buyers.

It’s whether you can afford not to.

Buyers also like them. 91% of B2B buyers say content like this is “very important” in the research phase and 82% they even expect it from vendors.

Companies see an effect from them. Tailoring copy, proof, and CTAs industry, use case and lifecycle stage raises the likelihood to convert.

Yet we don’t prioritize making them.

Industry pages have my attention this week because of two things:

1. I’m making 3 for one of my customers to lower buyer friction and get the attention of the right kind of leads they are in the market for.

2. Casey Hill sent me down a rabbit hole with this LinkedIn post. Data from 8 SaaS companies shows industry pages are not the most valuable kind of context page if you look by the clicks. It’s role/team/department context pages.

That made me wonder: Am I doing this right? I’ll share my thought process and outline some examples with you here in this newsletter.

What is the objective of a context page?

I’m using the word context page as there are multiple kinds of ways to put context before the buyer. Industry pages are just one of them. I’ll list more types later. Back to the objective:

The core objective is to build trust by showing buyers how your product fits their world.

Aka, lower the friction in the buying journey to let the buyer slide into your pipeline.

A generic home page without context forces the buyer to do a translation: “Okay, they do X… but how does that apply to my situation?” A context page works as the translator and helps the customer see how you already know their world and how the product fits into it.

You can break this down into a few sub-objectives:

1. Signal relevance. A buyer wants to know: “Is this for me?” A context page answers that in seconds through language, images, and proof points that mirror the world of the buyer.

2. Reframe value props to the buyer’s language. Your product is more than likely to do the same for all buyers. But certain words and jobs to be done mean more in one context than they do in others. So context pages give you an opportunity to focus on what matters to each buyer’s context and suppress other things you would otherwise highlight on your other website pages.

3. Lower perceived risk with relevant proof. A case study from a similar company in a similar industry at a similar size is 10x more persuasive than a generic testimonial. Context pages let you cluster your strongest social proof where it matters most.

4. Qualify and route the right buyers. Context pages act as a self-qualification mechanism. They attract the buyers you actually want and help the wrong-fit visitors self-disqualify early, which saves your sales team time and makes it easier to sell when buyers look the same.

5. Match search intent. When someone is asking ChatGPT: “Which CRM is built for real estate?” you have much higher chances of being cited by answer engines if you have a good context page for Real Estate.

What kind of context pages are most valuable, then?

From the very small batch of numbers Casey provided in his LinkedIn post, we have two data points:

Best performing: Role/Team/Department pages.

Worst performing: Industry pages.

That made me wonder: What kind of context pages could we actually make?

Here’s the list I have right now:

• By Industry: SaaS, Manufacturing, Wrestling promoters

• By Title: CMO, CEO, Dog Walker

• By Buying Role: Champion, Economic Buyer, Technical Evaluator

• By Department: Marketing, Sales, Product

• By Team: Commercial, Backend, Development

• By stage: Start-up, Scale-up, Enterprise

• By size: SMB, Mid-market, Enterprise

• By Pain Point/Problem: data silos, manual processes, compliance risk

• By Technology: CRM, Marketing Automation, Workforce Management

• By Frameworks: GDPR, HIPAA, SOC2, ISO

• By outcome: Reduce churn, increase conversion, shorten sales cycle

• By deployment model: B2B, B2C, Marketplace, Platform

• By maturity level: Beginner, Experienced, Expert

• By migration: From WordPress to Webflow, from Framer to Webflow, from HTML to Webflow.

This can seem overwhelming. How on earth do we know what kind of context pages are right for us? To help you find an answer, I’ll share a story of why we chose to do framework pages at Wired Relations when I worked there as Head of Growth.

How I used context pages as primary entry point

Wired Relations is a compliance software company. They help compliance departments with GDPR and information security.

We divided our market into two segments.

Segment 1: Those who didn’t care about compliance but were forced to get the check mark to show customers and government institutions.

Segment 2: Those who thought of compliance as a competitive advantage and had dedicated people running it as a department.

This market segmentation is important to understand, because it helped decide what kind of context pages we would run with.

If we marketed to segment 1, I would have chosen to run industry pages. The buyers here were looking for someone who had done this before for companies who looked like them.

That was not our market.

We marketed to segment 2: the experts.

Their entry into buying new compliance software was not because they didn’t have any today. They wanted software to work more effectively for them. We had to convince them to replace software, not just buy it.

That’s why we chose frameworks. That was where the buying moment opened.

A compliance specialist looks at something new the market is demanding they comply with, like the NIS 2 framework or ISO 27001. Both are frameworks where you must go through a specific process to get the mark of compliant and keep it.

But not having done this before, they looked beyond their current system, which could not do this, or at least they had doubts about how, or if, it was the most efficient way of doing it.

So our context pages created that buying moment and explained all our value props and features from that context point. Not “How to use Wired Relations”, but “How to work with NIS 2 with Wired Relations”.

The page looked like this:

This page is too long and too big to include in this newsletter, but you can study it by following this link or click the button.

See the image in large

We built 9 of these, and it was our biggest entry point for generating demos and free trials. Both from new buyers and the ones who already knew us.

So which should you choose then?

This is definitely something you should test. But as most companies don’t even make an industry page, testing multiple variants seems like a hard-won path to take. So I’ll try to answer it confidently anyway, so you can start producing.

Look at your ideal customer profile. How do they understand your product best in their context?

• Does the product have a super user and very few other users? Go with pain/framework/role

• Is it a department or team primarily that works in it? Go with department/team

• Is the product used by everyone in the company? Go with industry/size/stage

• Is the product infrastructure that serves the company? Go with industry/size

• Do none of the buyers operate under the same business model? Go with deployment model

But honestly, I have no idea which would work best for you. It is very context-dependent (no pun intended). I would need to know the customers, market and product before being able to answer.

But that is why I love marketing.

If you are willing to spend time understanding your customers and are business savvy, there are very few problems you can’t impact.

Start building context now

Should you still build industry pages then?

Industry pages, it depends. Context pages, definitely.

Buyers like them.

They impact business.

It’s an underused tactic.

If you start now, you’ll have a lot of upside on this tactic.

Back when I was CMO.

I shared that on LinkedIn and the sentiment was excitement and… anxiety.

Fast forward to today.

Now it’s ALL anxiety.

Peep Laja from Wynter (do yourself a favor and follow him) did market research among CMOs.

Here are the findings:

“We focus on GEO but don’t have a good benchmark if we’re doing everything that’s doable.”

“AI is taking over search... it’s the most important visibility tool now.”

“The decline in organic search due to zero-click AI search directly impacts our pipeline.”

Everyone is scrambling and there is no proven playbook.

46% of these leaders are actively pulling back from paid ads. They know organic search is declining. And they’re terrified of disappearing from AI answers.

Full on anxiety.

I realized something really obvious when I started to dive into AEO.

And I’ll share that with you in here, so you hopefully can direct your anxiety towards something else instead.

Here it is:

AEO is looking for the same answers as your buyers.

So if you already are working on content to make your buyers pick you, you are probably in a good place when it comes to AEO strategy.

And i’ll prove it to you.

The shift in how buyers search

AI search is fundamentally different. Users ask deeper, more specific, buying-contextual questions.

An example from my own Gemini account just last week:

“I need a simple CRM system for my solo business.

I’ve worked with HubSpot before and like the simplicity of it.

Demands:

• Pipeline I can edit as I choose

• Can integrate PMs from LinkedIn

• Have companies and user levels connected

• Is cheap for a single-person startup (free even better until x level)

I’m fairly technical and like a clean nice UI.

My other stack is Notion and G-suite primarily.

Use case is tracking who I talk to and manage my LinkedIn inbox in close relation to my pipeline.”

That is not a Google search.

It’s very contextual to my situation, my needs and personality.

Specific features, pricing, UI and use case.

I’m asking as a buyer, not a searcher.

I don’t need a “Top 10 list of CRMs for small business”.

I want answers in my context.

What AI Actually Looks For

I went on a mission to understand this, so I have a bunch of resources for you if you wanna dive deeper into it. Just follow the links.

It left me with these 5 bullets I had AI help me turn all my findings into:

AI favors content that:

1. Represents an idea clearly

AI systems reward clarity over keyword density. The key is making your content “extractable.” Easy for AI to lift your insights and cite them properly. When someone searches a specific question, your page should load with a crystal-clear answer that’s easy to skim. Direct questions with clear answers mirror the way people search, and AI assistants can often lift these pairs word-for-word into their responses. (Directive Consulting, Microsoft Advertising)

2. Can be summarized safely

AI models prefer high information density with specific facts, statistics, and frameworks they can extract and attribute. Vague statements like “many companies see improved results” get skipped. Quotable statements like “companies using real-time analytics dashboards reduce decision-making time by 35%” give AI something concrete to cite. Create named frameworks that become associated with your brand. “The 4-Phase Implementation Model” is more memorable and citable than generic advice. (Evertune)

3. Aligns with established understanding

AI citation selection works through pattern recognition across vast text collections. Models measure trust through repetition and context. The more your content appears in credible environments saying consistent things, the stronger your statistical trust signal becomes. AI citations are distributed across a long tail of sources, not concentrated among traditional Google top-rankers. Content structure and semantic relevance matter more than traditional ranking position. (Profound, Duane Forrester)

4. Fits a coherent body of knowledge

AI systems prefer content that exists within a larger, interconnected context, not isolated pages. Models build confidence through corroboration. When your content connects to other pages on your site covering related topics and forms a consistent narrative, AI treats it as more trustworthy and “safe to cite.” One-off pages feel risky. Connected content feels stable. Traditional SEO was built to optimize for ranking signals. Generative engines evaluate content based on meaning, clarity, and credibility. They don’t reward volume. They reward understanding. (a16z)

5. Has credibility signals (E-E-A-T)

Experience, Expertise, Authoritativeness, and Trustworthiness. Google’s framework for content quality now extends to AI citation. Research shows LLMs reward expert quotes, statistics, and cited sources, while keyword stuffing barely registers. Trust is built through transparency, consistency, and honesty. AI can’t “feel” trust, but it can measure it through repetition and context. To strengthen your AI trust markers: use structured data for authors and organizations, build external validation (press mentions, conference appearances), and maintain consistent author identity across platforms. (BrightEdge, CXL, Salt Agency)

Let me summarize that differently.

They favor content that:

1. Represents an idea clearly. They want to skim, get it, and move on. No fluff, just clear answers to their questions.

2. Can be summarized safely. Specifics they can extract and repeat. Vague claims get ignored.

3. Aligns with established understanding. If you contradict the consensus, they need proof. No receipts, no trust.

4. Fits a coherent body of knowledge. Same story, same language, same proof everywhere. Scattered messaging gets forgotten.

5. Has credibility signals. Customer stories, ROI, third-party validation. Evidence is how they measure trust.

Now re-read that list.

Was I talking about AI or your buyers?

What makes the buyers short-list your is what makes AI cites you.

8 content areas you should invest in

If you put your investment behind these 8 areas, you will serve both the buyers and the AI. I’ve picked these because they work interchangeably with both.

#1 Clear ICP messaging

Give context to who you’re building for. It helps both buyers and AI to understand who you are for and both will reward you for it.

Have industry pages to narrow audience in. Name your buyers in your materials. Keep a tight ICP in your case studies. Make your use cases examples of companies who use you.

#2 Not-good-fit pages

I love a good bad-fit page. Write clearly who you aren’t for. Eliminate bad-fits by clearly explaining your good-fits. That is probably the most specific instructions you can give AEO about your business.

#3 Deep feature pages

Remember my search: “CRM with LinkedIn capabilities, pipeline edit options and Notion integration”. If you describe your features with deep features pages on your product site or in your documentation that you link to, from your product pages, you win BIG in AEO.

This is where the gold is. You give clear instruction to highlight you in front of everyone else because you are telling AI that we most definitely can do what the buyer is asking.

#4 Use case pages

Use case pages pin-point problem/solution matching. So when I searched for “Use case is tracking who I talk to and manage my LinkedIn inbox in close relation to my pipeline” it can match with a “Content Creator CRM” use case page. That tells the AEO everything it needs. And buyers gain confidence to short-list you.

#5 Pricing page

Pricing is a clear-cut disqualifying mechanism. If the buyer is searching within budget ranges and you don’t have pricing, there is a good chance it won’t cite you. Because it doesn’t want to give bad answers. That’s its nature. It will cite anyone else that gives a clear answer that matches the search.

#6 G2, Capterra, TrustRadius reviews

Review sites are used to validate claims. Both from buyers and AI. The AI also has another angle you should learn from. The real customer language on reviews actually trains the AI on how to describe you. Not your website. Your customers voices.

#7 Customer case studies and ROI proof

“What results do customers get?” is a buyer question and an AI training input. Third-party validation and credibility signals are what calms everyone down. Buyers even say it’s some of the most valuable content you can give them.

#8 Community mentions (Reddit, LinkedIn, etc.)

AI looks for signals across the platforms where users talk about your product. So do buyers. And the more raves there are about your product, the more it will impact how they think of you.

It’s not been more than 6 weeks ago I wrote on this topic with my newsletter “AI can’t read your best content (and it hurts your revenue)”. You should read that one too.

Everything changed. Nothing is new.

I remember all the times SEO has been killed.

Or when social media marked our websites R.I.P.

Now it’s AEO’s turn.

And when everything is changing, it comforts me to know that nothing is new.

Operate with your buyer in mind and you will pass the trial of time.

• SEO guidelines works towards rewarding those who helped the searchers most.

• Social media algorithms reward those who are consistent in messaging and targeting.

• AEO will cite you if you are specific in what you do for who and can prove it.

Buying > Selling is a principle I tried to apply to all my work for a decade (at least).

And once again I’ve been confirmed in the direction works no matter how technology change.

That cured my AEO anxiety.

I hope it helps with yours too.

How to be sure

If you really wanna know how you do and discover all the gap, I created this Buyer Friction Grader.

An AI that scans your website and:

→ Grades you on 22 buyer questions

→ Scores you across 9 friction categories

→ Benchmarks you vs. SaaS peers

You’ll know exactly where you stand vs. the market and what to improve.

Takes 60 seconds to get your score.

Looking for 10 SaaS companies to field-test with.

Interested, reply to soren@lowfriction.io

If this helped you, forward it to a friend who it could help as well.

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The data backs it up:

• 16.5% of all visitors end up at your pricing page

• 1.7x more pipeline per lead from transparent vs gated pricing

• 51% of B2B buyers say transparent pricing is their #1 wish

So everyone should have a pricing page. Right?

Transparent pricing: The tinderbox-discussion like no other

Having advised 50+ SaaS companies and being internally responsible for marketing and growth at 3, I know the pricing-on-the-website-discussion really drives internal divides and resistance like few other things.

• Some think pricing belongs at sales as a tool in the conversation.

• Sometimes the packaging is not good enough to show publicly.

• Or pricing is just about to change, so let’s wait a bit (another year at least…).

No matter the reason, getting everyone onboard with showing transparent pricing is harder than steering a parked car.

But you still want to serve the buyers as they want to be served and grab that extra pipeline from the traffic you worked so hard to get.

So we have to answer the buyer question: “What does it cost?”.

What to do then? How do you fill the gap of pricing without being able to put up a pricing page?

I got you.

7 ways to show pricing without actual pricing

Before giving you the 7 tactics, here is a titanic-size battlecry: You should fight for transparent pricing. Nothing in this guide will help you as much as just showing your damn price to buyers who wanna buy from you.

This is NOT a replacement for doing the work. These are tactics for when you for some reason really can’t show your pricing or you have to bridge now to later when it’s possible.

With that said: doing some of these tactics instead and seeing for yourself how many people use the pricing page and how it affects the buyer’s journey just might be the thing that gets you enough power to prove your point.

Think of it like this:

Most people just want an indication. Is this $50-monthly-per-seat-software or are we looking at a $50.000 yearly write out with a 3-year commitment.

So even when you aren’t totally transparent, you can give directional guidance that actually helps people over the hump so they jump on a call to get the specifics.

That’s how these tactics work.

And now to what you came for:

7 ways to have a pricing page without real pricing

1. The feature columns

You know those classic pricing pages with three columns? Starter, Growth, Enterprise. Do that, but leave out the prices. Show the tiers, show what’s included in each, stack those beautiful checkmarks.

This works because buyers don’t only care about the price.

They care about what they get.

And when they can see the difference between your tiers, they start to self-select. “We definitely need SSO and dedicated support, so we’re looking at Enterprise.”

Now they walk into the sales call knowing what tier fits them. That conversation is much easier.

You can even add a little note under each tier like:

• “Custom pricing based on team size — talk to sales”

• “Starting from $X/month — get a quote”

Or just gate-slap the buyer with the OG: “Get a quote”.

Why it works: This setup makes it feel like a real pricing page (just without pricing). It lets buyers do the mental work of figuring out what they need before they even talk to you. They arrive at the sales call pre-qualified and with a clear idea of the tier they want. You’ve already anchored them. And you’ve shown them that there is structure to your pricing, even if you didn’t reveal the numbers. That builds trust. Way better than a blank page that just says “Contact us.”

Real-life examples:
https://www.command.ai/pricing/
https://www.vanta.com/pricing

2. The ballpark range

Take all invoices you shipped the last year and rip out 10% of the lowest paying customers and 10% of the highest paying customers. That should give you a good median to work with.

Take all the invoices you have left and drop them into a sheet and hover the bottom half and see the average.

Then do the same with the top half to get that average. Then you have an output that looks something like this:

“Our customers pay us between $11.400 and $87.000 yearly depending on features and usage”

You can also just drop all your invoices into your favorite AI and prompt it to give you the answer way faster.

Why it works: You just gave people two numbers to work with and depending on their business size they have a hunch about where they will land. For some, that is enough to move on.

Real-life examples:
I could not find a pricing page example. Almost no one does this on their pricing page, but it’s a very used Enterprise software tactic that sales reps use a lot.

3. The floor price

Tell your buyers your minimum and go from there. Especially if you are higher in price point. Nothing worse than thinking of a price and then getting totally blindsided when they mention the real pricing. That reminds me...

I was in love with Copy.ai and was doing my due diligence in the process. Their pricing page tells you that it costs $249 per month and then you have 10.000 credits to use. I figured there probably was coming an extra add-on for more credits, but I ventured into the sales process. In it I learned it was not $249 per month. In fact, their lowest tier for helping with setup was $24.000 yearly.

Imagine me scraping money from other initiatives in my marketing budget to find $5.000, walking proud and buying-ready into that meeting and then being told it’s 5x that amount. F*ck off (but nice product though).

“Our pricing starts from $3500 for our standard suite with video self-onboarding”.

You could also add tiers here.

• Start-up: Starts from $100

• SMB: Starts from $1.000

• Enterprise: Starts from $10.000

You see it a lot paired with the feature columns and seat pricing.

Why it works: The buyer gets a minimum that they can hold their budget against. It gives an indication about pricing and tells you it will be more expensive but it depends from here on out. And that alone will scare away cheapskates from your pipeline and hogging your sales reps’ time on tire-kicking.

Real-life examples:
https://www.twilio.com/en-us/flex/pricing
https://segment.com/pricing/connections/
https://www.databricks.com/product/pricing
https://www.askcody.com/pricing

4. The scaling customer

You can use a customer example to make it look super sharp. This will not only answer the question of price now, but also as you scale.

A sneaky advantage here is you can sneak in their outcome and make a really cool ROI comparison to make it look cheap. If you can name the company it’s a mini case story in itself and would be preferred.

“A 3,000-person pharma company has been a customer for 3 years. Here’s their breakdown:”

Total 3-year investment: $195,000

Their outcome: 14% faster time-to-hire and $2.1M saved in agency fees.”

Pro tip: Watch out for buyer-fit here. If you put out a number for a too small or too large organization compared to your average buyer, you scare them off. You want to use a customer story that has the median buyer-fit.

Why it works: This creates a believable setup where buyers can see how a company scales with your product. It shows the onboarding cost as a separate line item, then how the subscription grows with usage over time. If you’re running usage-based pricing, it can be really hard to understand before you’re onboarded. This makes it tangible.

Real-life examples:
This one is rare. You’ll find scaling stories in case studies, but almost never on pricing pages. And most you’ll find are hidden in doc sites.

https://launchdarkly.com/docs/home/account/calculating-billing
https://docs.snowflake.com/en/user-guide/cost-understanding-overall

5. The Price of not buying

This one is an absolute fav tactic of mine. Even if you have a pricing page, you should create this math to show the downside of not buying.

In this tactic, you outline the cost of time/spend/income of current solution and compare it to what it will be if they switch to your software.

Let’s say you sell time management software in consulting. Create a comparison of all the good stuff you help optimize: Time per tracked task, lost hours to registering fails and more.

Then you add the economy of it into it and have a great piece of content to convince people why it’s a smart choice to switch out your old solution.

SaaS’s biggest competitor is still Excel sheets.

It looks something like this

And with those numbers you can now write:

“With us you will easily save 800 manhours, bill $32.000 extra on used hours and save countless pained souls from Excel. Switch and get happy employees, more time and cash back. Get a quote”

Pro tip: Sometimes people don’t know the exact number of what you are asking, so they won’t fill it out. So pre-fill it with some numbers, so they can still get an output.

Vibe-code it in minutes

If you feel you don’t know how to build this, just vibe-code it. Your AI code tools like Loveable, make it laughably simple to build what was once complex.

And you should definitely put that on your pricing page as well. See here how easy it is to vibe-code things like this (or on YouTube)

It also has a bigger brother as the next tactic.

Why this works: It gives a clear image of how this will earn itself back and then some. If this maths holds true, the price is not really the big problem. But maybe timing of price will be. It’s hard to charge a year upfront when they didn’t have this expense before. So play it smart with how you charge if you use this tactic. Savings don’t equal having those savings upfront to pay you.

Real-life examples:
BetterCloud ROI Calculator

6. The payback math

This one is the big brother of “The Price of not buying” but with a different angle. Instead of showing what you’re losing by not switching, you show what you’ll gain by buying.

Different psychology. Some buyers respond better to “stop the bleeding,” others to “unlock the upside.”

Let’s say you sell sales enablement software. The kind that helps reps find the right content at the right moment and close deals faster.

You ask the buyer to fill in a few numbers:

And the output becomes something like:

With a 6% lift in win rate, your team will close 18 more deals per year, adding $864,000 in new revenue. Faster ramp means your new hires hit quota 2 months earlier — worth another $96,000 in accelerated pipeline.

Total first-year impact: $960,000

→ Get a custom quote”

Same as “Price of not buying” — vibe-code it with Lovable or Bolt. It’s basically just math and inputs. You’re not building rocket ships here.

Pro tip: If the math is too strong it’s going to be unbelievable and then it works against you instead of for you. So make sure you have guardrails in place, even if the numbers add up. It’s better to highlight big numbers in customer stories.

The difference between “The payback math” and “The price of not buying”.

Both are valid. Some buyers respond better to fear of loss, others to promise of gain. You could even have both on the same page for different personas.

Why it works: You just made price somewhat irrelevant. If the output says they’ll make an extra million, $30k or $80k yearly is not that important. The ROI does the selling. Now it’s a game of validating the numbers for the buyer so they can see it in their own business.

Real-life examples:
HubSpot ROI Calculator
Zendesk ROI Estimator (301% ROI based on Forrester TEI study)

7. The pricing logic

Sometimes your pricing is just too complex to slap a number on. Usage-based pricing, credit systems, or custom enterprise deals. Instead of hiding everything, explain how pricing works.

“We charge based on three things: the number of users, API calls per month, and data storage. The more you use, the more you pay — but volume discounts kick in at scale.”

You show a few numbers but never the full amount. Instead, you’ve told buyers how to think about their bill. That’s often enough for them to continue the conversation.

But I would still combine this with “The floor price” or “The scaling customer”.

Why it works: Buyers don’t always need to know the exact price. They need to understand the logic. When they get it, they can mentally model what their spend might look like. And that removes the fear of being blindsided.

Real-life examples:
https://betterstack.com/pricing#logs
https://newrelic.com/pricing
https://posthog.com/docs/billing/estimating-usage-costs

Quick reference

Here’s all 7 at a glance. Pick based on what you have and what the buyer needs to know.

Stack the tactics

These tactics work alone, but they work better together. The trick is to pair structure with numbers. Structure shows what they get. Numbers show what it costs.

Here are three combos that work well:

The Classic
Feature columns + The floor price

Show buyers what’s in each tier, then anchor them with a starting number. Structure meets price. This is the closest you get to a real pricing page without showing transparent pricing.

The Believer
The pricing logic + The scaling customer

Explain how your pricing works, then prove it with a real customer journey. Logic meets proof. Great for usage-based pricing that’s hard to understand upfront.

The Justifier
The floor price + The payback math

Anchor them with a starting number, then show them the value they’ll get back. Price meets ROI. Great when you want to lead with cost but need to prove it’s worth it.

Helpful? Yes. Optimal? No

These tactics help you play defense. If you wanna play offence, you have to have public, transparent pricing.

And buyers will find your pricing anyway.

Try this: Go into your favorit AI and ask

“How much does 6sense cost?”

The danger is buyers will base their number on something that could be totally off from how you set your pricing today. But they run with it because you don’t give them an alternative.

Remember the opening: your pricing page gets 18x more traffic than your demo page. That’s 18x more chances to win or lose a buyer.

If you’re stuck on what to show, I can help. Transparent pricing is one of my services at lowfriction.io.

I saw this list of the 50 fastest-growing SaaS companies in 2025 from Brex.

And I had a theory I needed to test out:

When you lower buyer friction, more people buy.

That means removing gates, showing real information and giving context so buyers can see value, try, evaluate, and understand before talking to sales.

If my theory is correct, the top 50 fastest‑growing companies should have clear evidence of this.

So I went through all 50 websites to check: Do they have transparent pricing? Free trials or freemium tiers? Video demos? Product visuals? Customer stories? All tactics deployed to lower buyer friction, that I could easily test.

In short: How easy do the fastest‑growing companies make it for buyers?

The results are unanimous.

100% of the top 50 fast-growing SaaS companies actively remove friction from the buying process and make it easy to try and understand their product.

Every. Single. One.

Theory proved.

They all subscribe to the same belief of making it easy for the buyer.

The individual things tested:

• Transparent pricing: 100%

• Product visuals: 100%

• Trial / Freemium: 98%

• Customer stories: 72%

• Video demos: 40%

Now, I expected a really good proof of my theory here, but not like this. I assumed at least a few would still be gating their stuff like it’s 2015.

To my delight, there wasn’t.

If you wanna grow fast in 2026 = lower your buyer friction.

Transparent Pricing: 100% Have It

Every single company in the top 50 has transparent pricing. No matter their pricing model they showed pricing.

Why it works: Pricing is the first filter. When buyers can’t find it, they assume they can’t afford it, or that you’re hiding something. Transparent pricing lets them self-qualify and move forward with confidence. HockeyStack analysed 31 million unique website visitors across 80 B2B SaaS that shows 1.7x pipeline created per lead from transparent pricing vs gated pricing.

Where they could do better: A lot of the companies on this list have usage-based pricing. The AI gold standard. The problem with this, is that even with transparent pricing, I don’t know what the cost is. Too few of them added calculators or examples that made me wiser about what I should ask for in budget to build my business case.

Product Visuals: 100% Have It

Use real UI graphics from your product. Abstract illustrations don’t count here. There were some companies that have a product without a visual interface, so I marked those with N/A and left them out of the scoring.

Why it works: Buyers wanna see your product. It’s value affirmation. Even when you have a free model, you should always display images from your product in its authentic form. This helps the buyer evaluate the product and makes it easier to proceed to next level.

Where they could do better:

Too many don’t show a full image screenshot from their product. So the buyer is left to do all the visual thinking about how it could work. Because all of them have an easy way to access the product, this doesn’t hurt as much. But they could benefit from additional product visuals.

Trial or Freemium: 98% Have It

Free trials and freemium tiers are standard among the fastest growers. Only 1 company didn’t offer a trial or free plan.

Why it works: 97% of B2B buyers want to try a product before they buy it. They want to see it, test it and see an outcome before committing budget.

Where they could do better: Some of them use weird language around this and don’t make it obvious you can try the product for free. A nice find here was there were multiple on the list that had ungated sandboxes you could play with without creating a user.

Customer Stories: 72% Have It

Customer stories, case studies, or outcome-driven testimonials. I made a mistake here. I should have separated case stories, reviews and simple quotes. They solve for different problems. But I didn’t and I decided it wasn’t worth going back, because it still proves the point no matter what kind of evidence it is: my customers like me. And that is the friction killer we looked for. Even though this is seen as one of the most compelling content types of buyers, only 72% had it.

Why it works: 90%+ of B2B buyers trust peers in their industry, only 29% trust vendor sales reps. You should use your customers to sell for you. It also gives customers a comparison option to find similar companies like themselves you solved the same problem for.

Where they could do better: A lot did not have case studies. That is first miss not having that. Secondly, only a few on the list had video case studies. This is as close you can get to final evidence of customers seeing value. Text can be faked, videos are harder (well, AI inno…). And again, buyers love shorts. So add them around your site for friction lowering assets. Check out how aggressively a high-performer like Clay is doing it.

Video Demos: 40% Have It

This is the weakest area of all tested. There is a lot to gain by adding a video demo.

Why it works:
In a video you control the narrative. You can put words and images into the minds of your prospects that they will take forward in their exploration. And some people like seeing a video of how it works, rather than trying it. It’s faster in most cases. And short-form video is the #1 way buyers like to consume B2B knowledge from vendors.

Where they could do better: There is not enough of it. Even the ones with good video demo don’t use it for use cases, features and other places where short-form demos will kill it. And there are a lot of companies who run a really short path to trying the product that would benefit from demos.

Testing methodology

You can see my testing method, the full list of companies and all results here. And you can understand how Brex arrived at their list of the 50 companies in the first place. Digital hugs for making this content for us.

See testing methodology and results

My itch is scratched. What about yours?

100% of the fastest-growing SaaS companies lower buyer friction. The pattern is undeniable.

But the majority of SaaS companies still gate their pricing. Still hide their product. Still make buyers wait days to talk to someone who can answer basic questions.

That’s the gap. That’s your opportunity.

I’m running 10 free buyer friction audits for subscribers.

You send me your URL. I send you a personalized report showing exactly where you’re losing buyers.

To qualify:

• You’re a B2B software company

• You close deals with a sales rep

• Your deal size is minimum $3,000

• You have at least 1 marketer on staff

Reply with your URL to soren@lowfriction.io.

I’ll tell you where you stand.

Ps. remember to forward this email to anyone who doesn’t think ungating buyer content is a good idea.

It treats all intent the same.

But intent is not binary. It lives on a spectrum.

• Exploring what you actually do and how it applies to them

• Thinking you might solve a specific use case

• Asking for pricing because you don’t have a pricing page

• Wondering if you have specific industry knowledge

• Looking for your compliance info as a last check before buying

All of them could go directly to demo if that’s the only option you give. But they have very different intent and your sales team should not sherpa every leads towards buying-ready.

It’s too expensive compared to the alternative.

Having bad buyer friction by not answering questions you know buyers ask, leads to bloat in your GTM. For example, research tells us that gating pricing will add 41% more work to the sales team, without any more pipeline.

Just people asking questions, not buying.

Not letting your buyers see how the product looks, works, and operates without booking a demo is the same kind of bad friction.

Like running in a swimming pool holding a wide sheet of plywood.

You want the ease of a fidget-spinner for every stage of the intent spectrum.

So let’s manipulate some buyer friction with the “Choose your own adventure” tactic.

The “Choose your own adventure” tactic

“Choose your own adventure” lowers friction by adding more paths to get answers that are mostly self-served and removes the big expense of educating buyers with sales reps.

Here’s how a “Choose your own adventure” dropdown could look:

This one has 3 paths.

• Try yourself — for the hands-on buyer

• See how it works — for the researcher

• Talk to us — for the ready-to-buy

All designed to answer specific buyer questions at different intent stages.

Let me walk you through each.

And show you all the friction-manipulating secrets baked into this design.

Start with the book demo button

Before we get to the paths, let’s talk about the button that opens the dropdown.

This can’t be called “Book demo”. That signals friction and keeps some visitors away from the button all together.

You want people to open this menu.

It’s a shortcut to valuable content that makes you look great.

When it drops down, all your added paths shows up and the buyer can pick theirs.

Instead, choose a low friction self-serving number like “Watch demo” or “See demo” or “Try yourself”.

“But if it doesn’t say ‘Book demo,’ people can’t find a way to talk to us,” I hear you thinking.

You have a full website to place CTAs on and you probably already have it in your hero anyway.

And if they don’t book because your menu CTA doesn’t say “Book demo” I doubt they ever were real buyers anyway.

You are adding good friction for your own funnel here.

Now let’s get into the paths.

Path 1: Try yourself

Your product with live data. If you have a public facing product, you could use that. If it’s closed off, but you can make a public version with fake data, do that.

Be a little creative on how people can see your product without having to onboard through a high-friction process like empty trial or demo.

Though trials and free tiers are of course valid options, I just avoided them here to show other alternatives. For some companies the path to showing value is too hard with a trial.

It could be

• Public-facing products

• Sandbox with fake data

• Interactive tour

Feel, see and click it

This lets the user understand your product without using your product.

Sometimes we just want to feel it.

See it.

Click it.

The goal: make the buyer behold the beauty of your UI and admire your experience. Then see how it adds business value too.

And yes, AI is eating the interface. But we’re not there yet. And until we are, your UI still matters.

Buyer-fit examples

Another great thing about this one is the buyer-fit labels. It helps identify “This is for me and my business”. And logos provide social proof that someone actually is using your product and is willing to display it.

And if you doubt this has value, you should look my newsletter on how Clay is a massive user of case studies.

Path 2: See how it works

Understanding requires story. That’s why this is the main path. I made it wider and gave it more visual weight with the video to make it feel like the most important in the dropdown.

Inject value

The reason I add weight to this over the others, is because it’s what gives me the most controlled environment to explain all the good things about the product and position myself to win. Without using a sales rep to do it that is.

When the buyer choose the first path, they control everything. I don’t have any sway over putting words or images into their mind and I wanna inject value and story into their discovery.

Done right, it removes a meeting from the sales cycle that the rep doesn’t have to do.

Auto-play

I want this to autoplay without sound. Not a full video — that’s too heavy — but enough to show the good stuff they’ll experience.

This will make more people click.

Another hack I like very much: It’s already autoplaying and they’re already watching. Work the audio angle on the button: “Turn on audio.”

It feels way more smooth as an experience.

60-6-60 framework

The next behavior hack is the 60-6-60 framework.

We don’t all consume content the same way. Some want surface-level only. Others prefer to sit down on research-Wednesdays in their home office, deep-diving into materials while Marsh sets the mood in the background.

We’re different. So give people options:

• 60 seconds — Quick pitch

• 6 minutes — Product walk

• 60 minutes — Full webinar

It can also be 84 sec, 12 minutes and 2 hours. The point is you give people 3 varied options to learn from. This also often creates a gateway to watch one and then come back and go deeper later, because you know the option is there.

Instead of product demos you could also run with these:

• Industry demos — Going over how a specific industry uses the product

• Use case demos — Showing specific use cases you know win customers

• Live product tour — A weekly group tour call you can jump on

• Customer showcase — Getting customers to showcase how they use the product

Path 3: Talk to us

Here’s the good old “Book demo.” That was what your button did before. But I added a lot of details even in this compromised view.

Book today

Instead of a classic “book demo” button, I surface available slots so visitors can see times they can book today.

This does 2 things: It removes friction from clicking the button and it lets buyers know they already can have a demo today. That should move buyers faster into your pipeline while their intent is hot.

No idea how you do this or what tool to use, but it’s gotta be possible in the name of low friction.

I also added design to reduce friction for timezone difference and of course added a button for more dates and times that leads to your full demo or direct to calendar booking.

Add friction through expectations

I apply intentional high friction in the wording: “Help you buy”.

I want people to understand if they use this option, they end up in a sales call. If they just want to understand the product, there are other options.

You can turn up the friction even higher by saying “Book a sales call” instead of demo at the top.

Lower sales anxiety

Adding faces, names and letting people see the questions they will be asked in the call, are all things that can lower the anxiety. The more your reduce it, the easier it will be for buyers to book that meeting.

Capture intent signals from each path

Each of these paths is an intent signal. A 1st party intent signal nonetheless.

With simple click-tracking for each path, you can see what adventures people are choosing. Measure for a month and understand your buyers way better.

If you have an even more advanced setup where you track on individual level or account level, this is all signal you wanna catch.

Each path = intent signal.

• Try = curious

• Watch 60s = browsing

• Watch 6min = evaluating

• Watch 60min = serious

• Book = buy-ready

Imagine seeing someone try your product one week. Then come back to watch a 6-minute video. Then the 60-minute tour. Then book a demo.

Those signals tells you so much about intent level.

Or: you just finished a sales call, and someone else from the same account is watching the 60-minute tour. Every sales team wants that information before jumping on a call.

It helps you identify the right accounts and intent level.

Yes, you’ll still see someone walk straight to “Book demo” thinking you sell solar panels for electric scooters as a software company. Humans will be humans 🤷‍♂️

But you can eliminate a lot of noise by understanding and placing strategic friction in your funnel.

In fact, by implementing this tactic, you have answered all of these buyer questions that are present in all journeys:

• How do you solve the problem?

• What makes you different from competitors?

• What does the product do (in plain terms)?

• What are the capabilities?

• Can I see how the product looks and feels?

• Can I see how the product works?

• How easily can I try the product myself?

• What questions will you ask us on the demo?

• What will we learn from a demo?

A demo-page answers 0 of them.

Knowing if it works

The ultimate test: how buyer-ready are your new demo bookings?

And is there a drop in bookings?

If there is a drop, it’s not bad. Most likely it means you are reducing noise in the pipeline and keeping low-intent buyers from spending your sales team’s time.

Future reports will confirm.

Start by measuring pipeline progression. How fast do prospects move through the pipeline and where do they drop off?

And then you ultimately want to measure on closed lost/won.

Remember to do a benchmark before you implement, so you have something to compare with.

Caring if it works?

Let’s say you can’t prove this by the numbers. Ask yourself: is this the buying experience I would like?

If you are like the rest of the market, it is.

Buyers are ~70% through their decision before they reach out.

61% of B2B buyers prefer a rep-free sales experience.

Your sales process is as little as 3,4% of the full buying journey.

Every damn study on B2B buyer behavior keeps confirming that buying is bigger than selling.

The question isn’t whether buyers want more ways to learn before talking to sales.

It’s proven again and again.

The question is whether you’ll meet them where they are.

Or keep funneling everyone through a door most of them don’t want to open.

Give them paths.

Watch which ones they take.

Then sell to the ones who are ready.

That’s how you turn a blunt instrument into a low friction revenue machine.

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Six. In writing it feels way too much. Six places?

But it really, really works. And elevates everything else they highlight.

I’m gonna take you through all of them, before we dive into tactics, here’s why they are doing it:

Case studies leads to more business

A case study is a piece of content that tells the story of how a customer used the product and what results they got out of it.

Here is one of Clay’s Case Studies

And we use them because buyers look for them and think they are helpful.

Here are the studies on Case Studies in B2B.

• 84% of B2B companies think they are clear on problem vs solution. Only 36% of buyers agree (source)

• 90% of B2B buyers trust peers in their industry, whereas only 29% trust vendor sales reps (source)

• 42% of B2B buyers said case studies and success stories are the most influential type of content (source)

• 55% of buyers find case studies and product reviews helpful or appealing (only surpassed by short form video content) (source)

• 72% of all B2B companies use case studies which makes it the most used marketing tactic (source)

Enough numbers for now.

I will dive into the depth of why you should drive more traffic to your case studies at the end.

Let’s look at the Clay Case Study Playbook.

The 6 case study tactics from Clay’s home page.

Logo wall with case studies

Most companies have a logo wall, but Clay is using theirs very clever. They have a small label under some of the logos that says Case Study. When you drag your mouse to it, you get a quote from a customer and it creates instant credibility.

We grow blind to logo walls over time, but this creates a deeper layer that really makes it interesting. But you have to make it obvious. Take a look at Wiz and their logo wall. They also use this tactic, but theirs are too hidden with that little plus and it makes it less useful.

Doing this allows you to pack more value into your hero and hopefully your buyers will notice. It’s worth the test.

Capability section

For each of their capability sections, they have attached another case story with an direct outcome. Again, this builds credibility.

This works really well if you have a number or result that links directly to the capability you are describing.

Feature section

The feature section has a different design than the capability section and that makes you stop at it, recognising it as a new section.

Following that change in design is the customer case. Here we get even more context with a quote, multiple results, logo and name.

And they struck a good balance in the visual hierarchy on how they put focus on the results rather than the name.

Again, use a contextual Case study if you have one.

Customer quote section

Big attention-grabbing cards with logos, real images of people, titles and a quote about how great Clay is.

This is the classic.

It’s lower down on the page because they want you to read about the product and problem they solve first and then introduce the evidence of their claims.

Their design on these are also great because of the big contrast.

Footer

Case studies have their own table in the footer where they highlighted some of the big brands they work with and then have a link to the rest of the stories.

This again makes it very easy to access customer stories and establishes trust from the big brands.

There is also another hidden effect from this: It makes it super easy for the LLMs to find who the customers are and highlight them in AI searches buyers do. Casey Hill wrote about that right here.

I do not like the design, but I think it’s something they have tested for attention, knowing the value of getting your buyers to read these.

In the solutions menu

They have two massive cases in the hover-state menu under solutions.

This again makes it very easy to find and read customer stories and again with a different design than all the others. Here with their own clay illustrations, which brings the customer very close to the brand.

Smart move - and highlighting content in our menus is a way underused great tactic

The buyer-fit problem solved

One problem Clay is solving perfectly here is the buyer-fit problem. Buyers look for companies like themselves and trust those sources more. You have to get different Case Stories in front of your audience on the website so there is a higher likelihood of them finding something that is a fit for them.

Go to Clay.com and check them all out for yourself. They deserve to be looked at in context of everything else going on at the Clay website.

Why should you drive more traffic to your case studies

To support your claims.

Everything you say will feel more convincing when you have a customer next to you acting like your hype-man. Underlining that the capabilities and results you promised is 100% what they experienced.

To win over the buying committee

Case studies are mostly a late-stage asset used for the final push to pick a vendor. In most B2B buying processes there are 6-10 people involved. Here it can become a strong asset of convincing internal stakeholders like finance or IT about the value and create internal buy-in.

To make an easy alternative for peer reviews

Case studies also solve for a different problem. Talking to a user or a peer about your product is the number one trusted source. But at the same time 41% of all B2B buyers wished it was easier to find another user to talk in their research (source). So the case study becomes a nice replacement.

To make an alternative to ROI assessment

And in the same line: 31% of buyers wished they could change this about the buying process: “I wish calculating ROI were easier so I could get the budget approved” (source). You should have clear ROI calculations available, but if you don’t case studies are a second best source.

To drive more LLM traffic

Case studies are the best content type to drive traffic in the age of AI (source). By a large margin. The more you make internal linking to them, the more visible they become for search engines.

But the most important strategic reason to drive more traffic to your case studies:

Answering more of your buyers questions.

You have to make it easy to buy from you. You do that by answering your customers questions with the depth and quality that makes them see you as a trusted source.

Case studies are built for that.

And by having them, you answer up to 20% of the non-negotiable buyer questions in the “Buyer Question Stack (I’m still working on the name, relax).

These are critical to win buyer trust and lowers friction for the buyers as they consider your as the solution to their problem.

• Who do you solve the problem for? (non-negotiable)

• What results do customers get? (non-negotiable)

• What ROI have customers seen? (non-negotiable)

• What metrics does this improve? (non-negotiable)

Case studies answer them all. And if you highlight them like Clay does, you’ll get the full benefit if the hard work case studies requires.

If you only take one thing away from this read, let it be this.

Don’t rely on buyers doing the heavy lifting and let them look for answers to their questions. Place your most valuable assets in front of them just like Clay does.

If you have less than 6, you now know where to start.

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Ps.

At Lowfriction, I’m building a library of all the questions buyers ask in the buyer journey, from problem understanding to onboarding with a vendor.

For each question I’m filling them with ways you can answer them elegantly, like this story from Clay. And writing advice on how to implement them.

I would love some feedback on the thing, so if you would like a peek, write me back and let me know.

“Can my team use Claude and ChatGPT through Notion AI without losing features? I love the idea of having AI where our context lives. Research and writing capabilities are most important (and we have Gemini on the side as stand-alone AI)”

And I got my answers in 15 seconds with a nice table of feature comparison, limitations and even a recommendation.

Can you imagine the time-sucking, soul-crushing agony to find this answer on my own?

Tab-Hoarding Googles, Notion Docs, blogs and AI documentation?

Nah…

I asked AI instead.

And I know I’m not the only one doing this.

AI is showing up everywhere in the B2B buying journey now.

Google has the AI overview.

ChatGPT and Gemini is used to compare options.

Perplexity to dig deeper than Google ever allowed.

So I started wondering: How much impact does AI actually have on the buyer journey heading into 2026?

I went looking for data.

And now I’m sharing that data along side my own thoughts with you.

The numbers are real

Let’s start with how buyers feel about AI in their buying process.

In 2024, most buyers said AI had “no impact.” That’s already changed. Now, over 40% say AI is actively helpful when researching software and the “no impact” group is shrinking fast.

And buyers are trusting AI-generated content more than before. Most say they trust it “Sometimes”, but the highest jump is in “Very often”.

Though I’ll admit: the 2% who say they always trust AI content? Yikes!

Here’s what else stood out from the report:

• 72% encounter AI Overviews in the discovery phase

• 90% click sources to learn more (source)

• 38% start with GenAI chatbots (source)

That last one is huge.

Because it changes how buyers search and view results.

And how you get eyeballs on your content.

If you wanna see the research, head over to TrustRadius (thanks Katie Allison).

So how are they actually using it?

I’ve been eyeing the types of questions people ask AI during a buying process.

That’s the most interesting part to me.

What are they actually trying to learn?

And the biggest find is people are just like me.

Getting deeper, adding more context.

Here are the top 5 ways buyers are ghost shopping for your software with AI.

1. In the old Google Search

AI snippets now appear at the top for queries like:

• “Best project management tools for marketing”

• “HubSpot alternatives”

Most buyers are still here. On Google. Asking questions.

But with Googles new AI mode, the AI guesses what the searcher is looking for and often gives great depth to simple searches.

And 90% clicks on at least one source from the AI overview in a buying journey.

2. When doing discovery

When buyers go straight to ChatGPT, Gemini or Perplexity, the questions get longer:

• “Give me a shortlist of 5 CRM tools for a 20-person B2B sales team selling to mid-market.”

• “We are looking at Salesforce and HubSpot — what else should we evaluate as the core for our revenue tech-stack?”

They’re not looking for a list. They’re looking for a fit.

And here is an important learning from my own AI search. They are starting to get complex. With lots of context to your own situation.

This is where AI excels as an experience for the user.

3. For technical specs

Some searches are becoming very technical and feature-rich. Buyers want to know if it works in a specific context:

• “Does Tool X support SSO with Azure AD and SCIM? Summarize from the docs.”

• “I need to find an employee experience survey tool that works in our Slack space and have API for pulling data”

If your documentation is solid, AI finds it and summarizes it.

If your users have been kind enough to write about it somewhere online, AI finds it and summarizes it.

If not, you simply don’t exist in that conversation.

For B2B SaaS especially, this means that your doc-site really needs to be updated. With features, capabilities, use cases and methodology.

The more context you can provide the LLMs, the more they will surface your product.

4. Price discovery

Because transparent pricing still isn’t table stakes in SaaS (why I still can’t tell you), buyers are reconstructing it themselves:

• “Based on public info, estimate the price of [Tool] for 120 users with premium support.”

• “Compare the pricing of Tool A and Tool B for 50 seats.”

They know it might not be accurate. But it gives them a ballpark — and the language to challenge vendors with.

** deep breath **

If you don’t have transparent pricing, AI is using forums like Reddit and blog posts to summarize the answers. Things that are totally out of your control and most likely, heavily outdated.

And AI is ruthless.

It’s gonna give the buyer an answer, no matter how wrong it is.

It runs of best possible answer it can find.

So your buyer is making a 2026 decision based on a random 2021 Reddit thread.

Nowhere near your pricing today.

Maybe not even in the same pricing structure.

Not having transparent pricing in 2026 is more offbeat than a jazz band at a square dance.

I’m willing to die on this hill, so expect me to mention this a lot in this newsletter.

** and exhale **

5. Vendor Comparison

This is where I think the shortlist gets created before vendors even know they’re in the race:

• “Summarize pros and cons of Tool A vs Tool B for a support team of 40 agents.”

• “I need to justify Tool X to our CFO. Give me a bullet list of risks, benefits, and ROI arguments.”

AI is helping buyers build the internal business case. Without sales ever being in the room.

You'd better have those covered so it gets it directly from the right source.

AI buying 5 ways. If you are using it outside this window, let me know. Just reply to this email. I wanna learn more.

Marketers don’t understand how AI finds their content

This stat was really surprising to me.

44% of vendors believe their gated content is being used to answer buyer questions in AI.

It’s not.

Your buyer guides. Your pricing pages. Your whitepapers. Your ROI calculators. Your market reports.

If it’s behind a form, it doesn’t exist to AI.

Full stop.

So you don’t get surfaced when people ask AI buyer questions where you are relevant.

It’s 2026 folks.

Enough with the gates already.

Speaking of 2026 — where to place your budget?

If you should switch some budget to get surfaced more by the LLMs, here are 7 places you should invest more money in 2026.

• Review sites — great source to get cited and awesome for buyers to learn from

• Communities — AI (and buyers) love real humans talking about real problems

• Deeper feature pages — so AI can answer technical questions about your product

• Use case pages — specific “how [Tool] works for [situation]” content

• Doc site — gives context to specific technical situations

• Customer stories — creates great trustworthiness you can build on

• A pricing page — because it’s 2026 and you are missing out without it

I’m so happy to give this advice, because there is a direct correlation between what the LLMs like and what buyers like. To me, this is shifting more budget towards making it easier to buy from you, not getting found by LLM. That’s just the upside.

And this is not a guide on “how to get cited by LLMs”, so don’t take it like it. I just wanted to uncover what is happening with AI and the buyer journey.

Buying with AI is just better

Using AI to research your problem and solution is a superior experience to browsing websites and doing Google searches, as a starting point.

As I went through a lot of research on this topic, I forced myself to think about my own way of using AI.

The depth of answers in the context you decide is something that has changed how I learn about things.

For good.

And I’m not alone.

We don’t make decisions with AI. Yet.

But more and more absolutely start there.

And it forces us to think differently about how we surface answers to buyers of our products.