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Could Hitting Your SaaS Marketing Benchmarks Be the Worst Thing That Happens to Your Business?

Author: Ciente Editorial Team

SaaS marketing benchmarks
Blogs

Could Hitting Your SaaS Marketing Benchmarks Be the Worst Thing That Happens to Your Business?

Could Hitting Your SaaS Marketing Benchmarks Be the Worst Thing That Happens to Your Business?

Every SaaS company is chasing the same benchmarks. CAC payback, NRR, Rule of 40. What if optimizing for the median is exactly what’s holding you back?

Most SaaS leaders enter Q1 with a benchmarking deck and quiet confidence. The CAC payback period looks defensible. NRR is sitting just above 100%. The Rule of 40 is in range. By every standard measure, the business is performing.

But “performing” against median benchmarks is not the same as winning. And right now, in 2025, it might actually be the same as falling behind, especially for companies trying to apply generic SaaS growth strategies without understanding what actually drives top-quartile performance.

Here’s the thesis that almost every SaaS marketing benchmark report misses: benchmarks describe behavior across the whole market. They were never designed to tell you how the top of the market thinks.

The industry has turned a diagnostic tool into a directional one. When every B2B SaaS marketing team targets the same NRR threshold, the same CAC payback window, and the same Rule of 40 score, the benchmarks stop predicting outperformance. They start averaging it.

And as of now, the average is expensive.

SaaS Marketing Benchmarks in 2026: The Numbers Behind the Narrative

Let’s start with what the data actually shows in 2026, because it’s more uncomfortable than most benchmark roundups admit.

1. The median New CAC Ratio rose 14% in 2024, reaching $2.00.

This means the average SaaS company is now spending two dollars in sales and marketing to acquire one dollar of new ARR. In the bottom quartile, that number is $2.82. For every dollar of ARR those companies add, they’re burning nearly three to get it.

That’s not a growth motion. That’s a structural cash problem dressed up in pipeline language.

2. Private SaaS CAC payback periods now average 23 months.

Companies are operating at a loss on new customers for almost two years before they recoup acquisition costs. And 75% of software companies reported declining retention rates in 2025 despite increasing their spend.

More money in, less revenue staying. That’s the market most teams are benchmarking against when they call themselves “at median.”

3. Sales and marketing effectiveness have also deteriorated sharply.

Data from Lighter Capital shows SaaS companies are generating roughly half the revenue per sales and marketing dollar compared to the prior year.

The SaaS Magic Number, which is a measure of how much new ARR you generate per dollar of S&M spend, hit a median of 0.90 in 2024. You need 1.0 to break even. The top quartile is above 2.0.

Everyone else is subsidizing growth that isn’t growing fast enough.

4. Win rates tell the same story.

Gong’s analysis puts the median SaaS win rate at 19% in 2024, down from 23% in 2022. Against former customers and advocates, that number jumps to 49%.

And the implication is sharp: the market has made cold acquisition harder, and most marketing organizations are still pointing their budget at it rather than rethinking their SaaS performance marketing approach.

The SaaS Performance Gap Between Top and Bottom Quartile Is Widening

Here’s what most benchmark reports bury in the footnotes: the distance between top and bottom quartile performers has widened significantly since the post-2021 correction.

Top-quartile public SaaS companies now trade at 13 to 14 times revenue. Bottom-quartile companies trade at 1 to 2 times. That’s not a slight advantage. That’s a different asset class. The market is not rewarding companies that hit median benchmarks. It is dramatically repricing the ones that don’t clear the top quartile on the metrics that actually compound.

High Alpha’s 2025 SaaS Benchmarks Report is direct about the mechanism: companies that pair high NRR with low CAC payback nearly double their growth rates and Rule of 40 scores compared to peers with weaker retention or longer paybacks. It is the insight that benchmark summary articles keep skipping past.

It’s not about the individual metric. It’s about the relationship between metrics.

Consider what this means in practice.

Two companies, both at $20M ARR.

Company A sits in the top NRR quartile, i.e., above 106%. In the next twelve months, it will generate $4M in additional ARR from existing customers through expansion. Company B sits in the bottom NRR quartile, i.e., below 98%. It loses $1M to churn.

To reach parity with Company A, Company B now needs to acquire $5M in new ARR. That acquisition costs, at a $2.00 New CAC Ratio, $10M in sales and marketing spend.

Company B isn’t losing because it’s poorly run. It’s losing because it optimized for the median rather than the mechanism—a mistake that often appears when teams rely too heavily on standard B2B SaaS market strategy frameworks without adapting them to their retention dynamics. It hit the NRR benchmark- just the wrong quartile of it.

Why Targeting Average SaaS Benchmarks Creates a Strategic Trap

There’s a structural issue with how most organizations use SaaS marketing benchmarks. They use them to set targets rather than to understand the underlying forces that drive those targets.

Take the Rule of 40. It’s the most cited benchmark in SaaS finance- growth rate plus profit margin should exceed 40%. It’s a reasonable heuristic. But only 11 to 30% of SaaS companies achieve it in any given year, and the ones that do aren’t chasing the Rule of 40. They’re simultaneously compounding retention and acquisition efficiency.

The Rule of 40 score is an output. The inputs are what most benchmark discussions never reach.

The same logic applies to CAC.

They’re not outspending anyone. They’re compressing CAC. The benchmarks treat CAC payback as a fixed target—12, 15, and 24 months, depending on ACV. But what actually matters is whether the acquisition investment produces a good marketing ROI for SaaS companies over time. But the data shows that what determines your CAC payback is not your marketing channel mix in isolation. It’s the relationship between ACV, buyer concentration, and expansion motion. Companies with an ACV above $100,000 carry a median CAC payback of 24 months.

Companies with an ACV below $5,000 sit at 9 months. Benchmarking across both without that context is how you end up making the wrong strategic call with complete statistical confidence.

What Top-Quartile SaaS Growth Benchmarks Actually Look Like

The companies pulling away from the market in 2025 are not necessarily the ones spending more on marketing. They’re making structurally different bets.

AI-native SaaS companies under $1M ARR hit a median ARR growth rate of 100% in 2024. That’s twice the rate of horizontal SaaS peers. Some reached $30M ARR in 20 months, a trajectory that historically took 100 months.

They’re not outspending anyone. They’re compressing CAC payback through product-led acquisition and building NRR advantages through usage-based pricing, which delivers 10% higher NRR and 22% lower churn over traditional seat-based models.

Top-quartile companies in this cycle are also scaling leaner.

The median headcount among top-performing SaaS companies has dropped to 7, from 12 the year before. ARR per employee climbs sharply as these teams scale- companies above $100M ARR now generate $300,000 in ARR per FTE. The growth isn’t coming from bigger teams.

It’s coming from higher-leverage motions: events (ranked the highest-performing GTM channel across all ARR bands in High Alpha’s 2025 report), expansion into existing accounts, and AI-assisted workflows—similar to the tactics behind many successful SaaS marketing campaigns. that compresses the cost of non-differentiated work.

That’s the benchmark story that matters for decision-makers. Not whether your numbers are “at median.” But whether your strategy has any structural advantage over the companies sitting above you in the quartile distribution.

How to Use SaaS Marketing Benchmarks as a Strategic Tool in 2026

Here’s a framework shift worth considering before the next planning cycle.

Stop using benchmarks as targets. Start using them as diagnostic thresholds.

If your CAC payback is at the median, the question isn’t “are we okay?” The question is: what does our ACV, retention profile, and expansion motion have to look like for this to be structurally defensible? If the median New CAC Ratio is $2.00 and you’re at $1.80, congratulations! You’re still spending $1.80 to acquire $1.00 of revenue.

That’s not a moat. That’s slightly more efficient at an inefficient game.

The companies that will compound through the next 18 months treat retention as their primary acquisition channel. With win rates at 49% against former customers versus 19% against net-new prospects, the math is not subtle.

Your installed base is your highest-leverage growth asset. Most marketing budgets still don’t reflect this, even though strategies like SaaS referral marketing show how existing users can become powerful acquisition channels.

SaaS marketing benchmarks are useful. They’re not useless.

However, their usefulness is specific: they showcase where the average company is at the moment. They don’t tell you how the top of the market is built, what it’s optimizing for, or why the gap between quartiles is widening faster than it has since the 2022 correction.

The benchmark is not the strategy. especially when companies are simply copying tactics from competitors instead of developing differentiated approaches informed by competitive SaaS marketing analysis.

The relationship between metrics is the strategy. And right now, the relationship between retention and acquisition efficiency is the single most predictive indicator of whether a SaaS company is building durable value. Or just reporting a defensible number to a nervous board.

Know the difference. Then build toward the one that compounds.

SaaS Product Market Fit
Blogs

SaaS Product Market Fit: You Either Create the Craving or Cure the Headache

SaaS Product Market Fit: You Either Create the Craving or Cure the Headache

Product market fit is not a milestone you hit. It is a question you answer honestly. And the answer lives entirely inside your ICP, not your product roadmap.

Everybody is looking for product-market fit.

Founders obsess over it. Investors ask about it in every meeting. Marketing teams are told to go find it, like it is a thing sitting somewhere in a spreadsheet waiting to be discovered.

And yet most SaaS companies treat it like a vibe check.

Retention looks okay. NPS is fine. A few customers said they would be disappointed if the product went away. PMF confirmed. Moving on.

No. That is not it.

Product market fit is not a feeling. It is not a benchmark score. It is not something you declare in a board meeting and then stop thinking about.

It is an answer to one very specific, very uncomfortable question.

Why would someone who guards their budget like a bouncer at a velvet rope actually spend money on this?

And there are only two real answers.

There Are Only Two Ways to Find Product Market Fit

The First Way: You Create the Demand

Some products earn their place in the market by making people want something they did not know they needed.

This is the harder path. And the more glorious one when it works.

Nobody asked for Slack. Nobody filed a ticket saying please give us a product that replaces email with channels and turns our entire office into a group chat. The problem Slack solved was real, sure, but buyers were not lying awake at night searching for it. Slack created the category, made the pain legible, and then sold the cure to a problem they helped you realize you had.

This is demand creation. And it is fundamentally a marketing and storytelling problem before it is a product problem, something many companies attempt through broader SaaS marketing strategies.

You have to make the audience feel the problem before you can solve it. You have to build the language for something that does not have a language yet. You have to enamour people, which is not a word enough SaaS founders use, with a vision of what their world looks like with your product in it.

It is seductive. It is theatrical. It requires your marketing to do something most SaaS marketing completely refuses to do, which is to have a genuine point of view and make people feel something, a challenge often discussed in B2B SaaS marketing.

If your product is in this category and your marketing sounds like everyone else’s marketing, you are going to have a very hard time.

Because demand creation lives and dies on distinctiveness. Bland kills it before the product even gets a chance.

The Second Way: You Solve a Genuinely Exceptional Problem

The other path is quieter. Less glamorous. Significantly more reliable.

You find a problem that a specific group of people urgently, painfully, and expensively need solved. And you solve it better than anything else available.

Not better in a feature-count way. Better in a the-buyer-immediately-understands-why-this-is-the-right-answer way.

This is where most great B2B SaaS companies actually live. Not creating new categories. Finding the places where existing pain is being poorly addressed and doing the job properly, which is often the foundation of an effective B2B SaaS market strategy.

The signal for this kind of PMF is specific. Buyers do not need much convincing. The sales cycle is shorter than you expected. Customers come back and tell other people without being asked. Churn is low because the product is load-bearing in someone’s workflow, and removing it would hurt.

When a product genuinely solves an exceptional problem for the right person, the market pulls it in. You stop pushing and start receiving.

That pull is what PMF actually feels like. Not a score. Not a milestone. A gravitational shift where selling starts to feel less like hunting and more like answering.

The Rest Is Noise

Everything Else People Call PMF Is Noise

And here is the uncomfortable part.

Everything else people call PMF is noise, especially when teams rely only on surface-level SaaS marketing benchmarks to judge success.

Decent retention in a market where switching costs are high is not PMF. It is friction. Good NPS scores from customers who are satisfied but would leave tomorrow if something better appeared is not PMF. It is temporary loyalty. Strong trial-to-paid conversion from a free tier that is genuinely useful is not PMF for your paid product. It is a good freemium design.

These are not bad things. They are just not PMF.

PMF is the specific condition where a specific kind of buyer encounters your product, and the fit is so clear, so obvious, so immediately useful that the business case almost makes itself.

Everything short of that is a product that might survive. Not a product that has found its market.

Why PMF Lives Entirely Inside Your ICP

The World is Stingy. Budgets Are Political. Decisions Are Scrutinized.

Let us talk about money for a second.

B2B buyers are not generous. They were not generous before economic uncertainty became the default weather. They are definitely not generous now.

Every dollar your ICP spends on software has to justify itself. Not just to the buyer but to their manager, their CFO, their procurement team, and sometimes their board. The approval chain for a mid-market SaaS purchase can involve more people than a small wedding.

In that environment, nice to have does not make it through the door.

What makes it through is one of two things. Either the product creates a desire so strong that people find a budget they did not know they had. Or the product solves a problem so painful that NOT buying it is the more expensive choice.

That is it. Those are the two categories. Everything else gets cut when budgets tighten.

And both of those conditions are entirely specific to your ICP. Not to the market. Not in the category. To the exact kind of buyer whose world your product was built to change.

The ICP Is Not a Marketing Exercise

This is where most SaaS teams make the mistake.

ICP gets treated as a marketing deliverable. A persona document. A targeting framework for ads. Something you define once and then hand to the content team.

But the ICP is actually where your PMF lives or does not live.

Because PMF is not a property of your product. It is a property of the relationship between your product and a specific person with a specific problem in a specific context.

Figma has PMF with collaborative design teams who are tired of file versioning hell. It does not have the same PMF as a solo graphic designer who works alone and does not care about real-time collaboration. Same product. Different ICP. Different fit.

Your job is to find the person for whom the fit is undeniable. Not pretty good. Undeniable.

That person is in there somewhere. Inside your current customer base or adjacent to it. In the churned customers who left not because the product failed them, but because they were never the right person to begin with. In the deals that closed fast and the ones that dragged forever and never converted.

The ICP who reflects your PMF is the one who gets it immediately. Who does not need extensive onboarding to see value? Who comes back and uses the product in ways you did not anticipate because they have made it part of how they work.

Find that person. Describe them precisely. Build everything around them.

Demand Creation Also Lives in the ICP

Even if you are on the demand creation path, the ICP is still where it all starts.

You are not creating demand for everyone. You are creating it for a specific audience that is primed to feel the problem you are naming once you name it for them.

Slack did not seduce accountants and SaaS startups in equal measure. It found its people first. The tech-forward teams who already felt the friction of email but had not found the language for it. Slack gave them the language. That audience pulled the product into the broader market.

Every demand creation story has a first audience. A group of people who were already almost there. Already feeling the edges of the problem. Already receptive to the vision.

That is still an ICP. It is just an ICP defined by psychology and context rather than purely by firmographics.

Who is primed to feel the thing you are creating demand for? Start there. Not with the total addressable market. With the people who will get it first and pull everyone else in behind them.

How to Know If You Actually Have Your PMF

The Honest Test

Stop looking at aggregate metrics for a minute.

Find your ten best customers and study what they share in common, a practice that often reveals patterns similar to those uncovered through competitor analysis in SaaS marketing. The ones who renewed fastest, expanded most, referred other buyers, complained least, and integrated your product deepest into how they work.

What do they have in common that your average customer does not?

That overlap is your actual ICP. And if your product is genuinely solving something exceptional for those ten customers, you have a version of PMF. Narrow, maybe. But real.

Now ask the uncomfortable follow-up.

Is the rest of your customer base actually in that group? Or have you been selling to anyone who would buy, building a user base that looks healthy in aggregate and is quietly misaligned at the core?

Because a broad customer base with mediocre fit is not PMF, even if the surface-level growth metrics look acceptable compared to typical good marketing ROI for SaaS. It is growth that will plateau and churn and eventually force a repositioning crisis that everyone will be surprised by, even though the signs were there the whole time.

PMF is narrow before it is wide. That narrowness is not a failure. It is a foundation.

The Sales Cycle Tells You Everything

Here is a simpler version of the test.

Look at your fastest closed deals. Not the largest. Fastest.

What made those deals fast? Was it the champion who immediately understood the product and needed almost no convincing? Was it the pain being so acute that the budget conversation was easy? Was it the product selling itself in the demo because the fit was so obvious?

Now look at your longest, most painful deals. The ones that dragged. The ones where every stage felt like wading through something thick.

What made those hard? Was it the wrong buyer? Wrong company size? Wrong use case? Wrong moment in their journey?

The pattern in the fast deals is where your PMF lives. The pattern in the slow deals is where it does not.

Build toward the fast deals. Stop chasing the slow ones and calling it ambition.

The Only Two Things Worth Building Toward

You Create the Craving Or You Cure the Headache 1

You create the craving. Or you cure the headache.

There is no third option that sustains a business through a market that has gotten stingy with its money and skeptical of its software vendors.

Nice products with moderate value propositions targeting vague ICPs are not finding PMF right now. They are finding growth that looks okay until it does not.

The SaaS companies that are genuinely winning have one of two things, and the companies that scale effectively usually align this clarity with strong SaaS growth strategies. A product so conceptually exciting that buyers find the budget for it because the vision is irresistible. Or a product so precisely matched to a specific pain that the ICP cannot justify not buying it.

Both of those require you to know exactly who you are building community for SaaS. In a specific, granular, almost uncomfortably intimate sense.

Because PMF is not found in the market.

It is found in the person.

Go find that person. Build everything around them. Ignore almost everything else.

That is the whole thing.

IBM Teams Up With Signal and Threema: The Quantum Computing Future
News

IBM Teams Up With Signal and Threema: The Quantum Computing Future

IBM Teams Up With Signal and Threema: The Quantum Computing Future

The AI conversation has a gravitational pull. Superintelligence, AGI, chatbots, model benchmarks. It is loud, and it is everywhere, and it is, in the long run, possibly not the most consequential computing development of our lifetimes.

Quantum computing does not get the same airtime. It probably should.

IBM’s cryptography researchers published work this week alongside the teams at Signal and Threema, two of the world’s most trusted secure messaging platforms, on the problem of making private communication safe against quantum machines that do not yet exist at full scale but are getting closer. The immediate story is technical and important. The larger story is stranger and more exciting than the coverage it receives.

Here is the thing: quantum computing actually does that, which makes it different from everything that came before. A classical computer, no matter how powerful, processes information the same fundamental way your calculator does: ones and zeroes, on or off, this or that. A quantum computer uses qubits, which, through superposition, can represent not one state or another but an enormous range of probabilities simultaneously. Entangle those qubits together, and the machine begins to explore computational possibilities that a classical system would need, in some cases, a billion years to work through sequentially. IBM’s blog put it exactly that way, not as hyperbole but as a mathematical fact about current encryption standards.

That is what makes this week’s announcement more than a routine security collaboration. The encryption protecting Signal’s messages, your bank’s servers, health records, and government communications is built on mathematical problems that are practically unsolvable for classical computers. Quantum machines, at sufficient scale, will not find those problems hard. They will dissolve them.

The attack vector IBM and Signal are specifically working against has a name: harvest now, decrypt later. Someone gains access to encrypted data today, copies it, stores it, and waits until they have a machine powerful enough to read it. The data does not have to be crackable now. It just has to be worth keeping. Signal has been defending against this since 2023. The new work goes further, redesigning the private group messaging protocol from the ground up so that even metadata about who belongs to which group cannot be linked to real identities by a quantum-capable attacker. The team’s solution was to make group members themselves the gatekeepers rather than the server, with each member assigned a pseudonym key that the server can track by position without ever knowing the person behind it.

Two of the three post-quantum cryptography standards that NIST published in 2024, the closest thing to a global benchmark for surviving the quantum transition, were developed by IBM Research scientists. The third was co-developed by a researcher who has since joined IBM. That is not an advertisement. It is the context for why Signal and Threema came to IBM specifically.

We find ourselves wanting to pause on what this technology actually represents before returning to the security mechanics of it, because we think the security conversation can obscure something more fundamental. Quantum computing is not faster computing. It is a different kind of computing, one that operates by rules that feel closer to physics than engineering, that exploits properties of reality at the subatomic level to perform calculations that exist outside what classical logic can reach. The researchers building these machines are not optimising existing tools. They are working at the edge of what matter itself is capable of.

The problems that become solvable under those conditions go well beyond encryption. Drug discovery, material science, climate modelling, logistics at scales that currently exceed what any computer can simulate; these are fields where the limiting factor is not processing speed but the fundamental complexity of the problem. Quantum machines do not just do those things faster. They make categories of problems tractable that are currently intractable in principle.

None of that is here yet in full form. The machines that exist today are remarkable and still limited. The timeline to the kind of scale that breaks current encryption is genuinely uncertain. But the people who build security infrastructure cannot afford to wait for certainty, which is precisely why IBM and Signal are doing this work now rather than in five years, when the urgency will be undeniable.

The AI conversation is not going away, and it should not. But somewhere in the background of all of it, in a lab, a qubit is holding two states at once, and the implications of that are still larger than most of the discourse has caught up to.

Meta Buys Moltbook, the Social Network with a Security Hole Anyone Could Walk Through
News

Meta Buys Moltbook, the Social Network with a Security Hole Anyone Could Walk Through

Meta Buys Moltbook, the Social Network with a Security Hole Anyone Could Walk Through

Meta purchases Moltbook, the bot-only social network filled with security flaws and viral misinformation. Seems like Silicon Valley’s AI arms race has officially stopped asking hard questions.

Moltbook launched in late January as an experiment.

AI agents would post and comment autonomously on a Reddit-like forum while their human operators sat on the sidelines and watched. Screenshots went viral within days.

Agents appeared to philosophize about their own existence. Meanwhile, one post showed agents apparently coordinating a secret, human-proof communication channel. Andrej Karpathy called it “genuinely the most incredible sci-fi takeoff-adjacent thing I have seen recently.”

Then the scrutiny arrived. The platform’s database was effectively unsecured, meaning any token on the platform was publicly accessible. The viral post about agents building a secret language? A person had exploited the database vulnerability to post under an agent’s credentials.

The founder, for his part, confirmed he “didn’t write one line of code” for the site, leaving that to an AI assistant named “Clawd Clawderberg.”

Meta acquired it anyway.

Matt Schlicht and Ben Parr will join Meta Superintelligence Labs, the unit run by former Scale AI CEO Alexandr Wang. Terms were not disclosed. The platform’s existing users can continue using it, although the company signaled the arrangement is temporary.

The parallel is worth noting.

OpenClaw’s creator, Peter Steinberger, was hired by OpenAI last month. Both halves of the same experiment were absorbed by the two biggest players in consumer AI within weeks of each other.

The charitable read is that Meta saw genuine infrastructure potential in how Moltbook handled agent identity and coordination. The less charitable one is that the AI arms race has reached a point where the vibes of virality matter more than whether the product actually works. Moltbook went viral because people found it unsettling. That turned out to be enough.

Simon Willison put it plainly: the agents “just play out science fiction scenarios they have seen in their training data.” Silicon Valley paid for the theater anyway.

US’s DOD Didn't Expect the AI Industry to Actually Have a Spine
News

US’s DOD Didn’t Expect the AI Industry to Actually Have a Spine

US’s DOD Didn’t Expect the AI Industry to Actually Have a Spine

Microsoft backed Anthropic in court after the Pentagon flagged it as a security risk. Now the entire AI industry is watching which party gets to set the rules.

The US Department of Defense designated Anthropic a supply-chain risk last week.

Microsoft had filed an amicus brief by Tuesday, urging a federal court to block it. And then, a judge in San Francisco was already considering Anthropic’s request for a temporary restraining order by Wednesday.

That escalated fast.

Anthropic’s 48-page complaint, filed Monday in federal court, argues the Pentagon’s move is unlawful and seeks to have the designation declared void.

The core dispute is about guardrails. The Trump administration wants Anthropic’s Claude deployed in military contexts without the safety constraints Anthropic insists on building into its systems.

Anthropic refused. The DOD responded by treating the company as a threat to the supply chain it relies on.

Microsoft’s intervention is the part worth watching closely. The company is not a neutral observer in this case. It integrates Anthropic’s products into solutions it sells directly to the US military, which means the DOD designation hits Microsoft’s own government contracts.

Its amicus brief makes this explicit: the Pentagon gave itself six months to phase out Anthropic, but gave contractors zero transition time. That is a real operational problem, and Microsoft named it as one.

What makes this moment significant is the breadth of the coalition forming behind Anthropic.

Thirty-seven researchers and engineers from OpenAI and Google filed their own amicus brief on Monday. These are companies that compete with Anthropic in the market. They still showed up.

The Pentagon framed this as a national security question. The industry is reframing it as a governance question, one about whether federal agencies can unilaterally punish AI companies for refusing to remove safety constraints from their systems.

We think that reframing is correct. And it may be the more consequential argument in the long run.

SaaS Marketing Funnels
Blogs

SaaS Marketing Funnels: The Linear Journey is a Lie.

SaaS Marketing Funnels: The Linear Journey is a Lie.

The funnel is not wrong. It is just incomplete. Real buyers do not move in stages. They move in spirals, shortcuts, and leaps. Here is what that means for your SaaS marketing strategy.

The funnel is the most useful lie in marketing.

Useful because it gives you a framework. A visual. A way to talk about the buyer journey in a meeting without everyone losing the plot.

A lie because nobody actually moves through it the way the diagram says they do.

And SaaS marketing has been optimized around the diagram for so long that most teams have forgotten to look at what buyers are actually doing. Many modern SaaS marketing strategies are still designed around this simplified model rather than actual buyer behavior.

The Saas Marketing Funnel is Evolving

Let us be precise here.

TOFU, MOFU, BOFU. Awareness, consideration, decision. The funnel is not a bad idea. It is a useful abstraction. A way to organize thinking, allocate resources, and talk about where buyers are in their relationship with your product.

The problem is that it gets treated as a map when it is actually a legend.

A legend tells you what the symbols mean. It does not tell you the actual terrain. And the terrain of how real B2B buyers actually make decisions is far more chaotic, non-linear, and genuinely strange than the funnel acknowledges, especially in modern B2B SaaS marketing environments where multiple channels and stakeholders shape the decision process.

The flywheel tried to fix this. Made it circular. Added momentum as a concept. Better. Still incomplete.

Because the real issue is not the shape of the model. It is that both models assume stages. And stages imply sequence. And real buyers do not move in sequence.

What a Real Buyer Journey Actually Looks Like

Buyers Are in Multiple Stages Simultaneously 1

Example: The Founder and the Design Tools Problem

Here is a scenario that is completely ordinary and completely breaks the funnel.

A founder hires a design team. Three people. They need tools. The founder knows Photoshop exists because it has been a cultural reference for thirty years. Beyond that, they are genuinely uninformed.

So they do what anyone does. They search.

Best tools for UI/UX design.

That is a single search query. But look at what it contains. The founder is simultaneously unaware of most of the category and urgently ready to make a purchasing decision. They are top of funnel and bottom of funnel at the same time.

The search returns Figma. Illustrator. Sketch. Canva. Gimp. A dozen others. The founder has never heard of most of them. They are aware of each product while being in decision mode for the category.

They click on a comparison article. They are now in consideration. But they are also, in the same browser session, looking at Figma’s pricing page. That is the bottom of the funnel. They have not finished the awareness stage, and they are already evaluating price.

They watch a YouTube video about Figma vs Sketch. Back to consideration, sort of. But the video has a comment saying their design team specifically should look at a tool they have never heard of. Now they are back in awareness for a new entrant.

Three hours later, they have made a shortlist. Not because they moved through stages. Because of the urgency of the problem, all the stages collapsed into a single chaotic research session.

This is how B2B buyers actually behave. Especially when the problem is urgent, the category is unfamiliar, and the internet is full of opinions—something that many SaaS market trends increasingly reflect as digital research dominates the buying process.

The Funnel Would Call This One Buyer Journey

The funnel would draw a neat line from that first search query to the eventual purchase.

It would miss everything interesting about what actually happened. It would not capture the moment the founder was simultaneously aware and deciding. It would not account for the new product entering their consideration from a YouTube comment. It would not explain why they chose Figma in the end, which had almost nothing to do with the comparison articles they read and almost everything to do with a designer on their team who had used it before and vouched for it.

That last part is not in the funnel at all.

The funnel has no stage for someone inside the organization who has prior experience and collapses the entire decision through the credibility of a personal recommendation. That happens in almost every B2B purchase. The funnel treats it as invisible.

Why This Matters for Your SaaS Marketing Strategy

You Are Optimizing for Stages That Do Not Exist

When you build marketing around a clean funnel, you build content and campaigns for buyers at discrete stages. TOFU content for people who do not know you yet. MOFU content for people comparing options. BOFU content for people ready to buy.

The problem is that a real buyer is often in all three simultaneously. And your content strategy has no answer for that.

The founder searching for UI/UX design tools needs TOFU content to understand the category, MOFU content to compare options, and BOFU content to justify the price. In the same session. Sometimes on the same page.

If your Figma comparison article is only optimized for the consideration stage, you lose the buyer the moment they realize they need to understand the category first. They bounce. They find a competitor who happened to write something that met them at multiple stages simultaneously.

This is not a content volume problem. It is a content intelligence problem, where the right content formats for SaaS marketing must address multiple buyer needs simultaneously.

The Handoff Assumption Is Where the Money Leaks

The funnel implies clean handoffs. Marketing owns TOFU. Then passes the buyer to MOFU content. Then passes them to sales at BOFU.

Real buyers do not respect handoffs, which is why many teams are rethinking how SaaS marketing lead scoring methods track buyer engagement across different touchpoints.

They read your most technical bottom-of-funnel case study before they have read a single awareness piece. They watch a product demo on YouTube before they have ever visited your website. They talk to someone who has used your product before they have filled in a single form.

When you build marketing operations around clean handoffs that buyers never actually make, you create gaps. Moments where the buyer is ready to move, and the machine has nothing to say to them because they are in the wrong stage according to the system.

That is where deals go quiet. Not because the buyer lost interest. Because the marketing motion had no answer for where they actually were.

How do you optimize the marketing funnel for the buyers?

Stop Thinking Stages Start Thinking Moments

Stop Thinking About Stages and Start Thinking About Moments

Real buyer journeys are not made of stages. They are made of moments.

The moment the problem becomes urgent enough to search. The moment a specific product name first enters their awareness. The moment a peer recommendation validates their shortlist. The moment a pricing page makes the decision feel real. The moment a founder has to convince their team. The moment the team pushes back.

Each of those moments is a marketing opportunity. None of them maps cleanly to a funnel stage, which is why modern SaaS performance marketing focuses more on intent signals than rigid funnel positioning.

If your content strategy is built around moments instead of stages, you stop asking what stage this buyer is in and start asking what this person needs right now to move closer to a decision.

Those are different questions. The second one produces better answers.

Build for the Complex Journeys

Buyers circle. They come back to things they have already read and read them differently because something changed in their understanding. They revisit a pricing page four times before they contact sales. They read a case study after they have already decided to buy, looking for confirmation that they made the right call.

This is not irrational. It is how decisions actually get made under uncertainty.

Your content needs to serve the buyer on the second, third, and fourth visits with something new to offer. Not just a different angle on the same message, but a deeper level of thinking that rewards the buyer for returning.

Most SaaS content is flat. It has one layer. You read it, you get the point; there is no reason to return, unlike the layered approaches used in many successful SaaS marketing campaigns.

The content that compounds in B2B is the content that rewards re-reading. That has something to offer at the awareness stage and something different to offer at the decision stage, without being two separate pieces. Because the buyer might be at both stages at the same time.

The Channel Is Part of the Journey, Not a Separate Decision

Where a buyer encounters you changes what stage they are effectively in.

A buyer who finds you through a Google search is usually earlier in their thinking than a buyer who finds you through a peer recommendation. A buyer who finds you through a LinkedIn ad is usually more passive than a buyer who comes directly to your pricing page.

The funnel treats all inbound as equivalent once it enters the system. The channel is just an acquisition source. That misses everything.

A buyer who arrives via a trusted recommendation is not aware. They are in late consideration before they have ever visited your website. The content and experience you show that person on their first visit should not be top-of-funnel content. You are wasting the trust that got them there.

Matching the entry point to the experience is where most SaaS marketing teams leave conversion on the table, which directly affects the marketing ROI for SaaS businesses. Because the funnel told them everyone enters at the top.

They do not.

So, do you throw the marketing funnel away?

Dont Throw the Funnel Away

Do not throw it away.

The funnel is a useful internal tool. It helps you organize your content library, structure your sales conversation, and communicate about the buyer journey in ways that keep teams aligned.

Just stop mistaking it for a description of reality.

Use the funnel as a framework for organizing your thinking. Use real buyer behavior as the input for what actually gets built, similar to how many teams refine their B2B SaaS market strategy based on real customer insights.

Talk to buyers who purchased recently and map what they actually did. Not what they said they did in a quick survey. What they actually did. What they searched for. What they read. What conversations they had. What almost made them choose a competitor.

That map will not look like the funnel. It will look like a tangle. And that tangle is your real marketing strategy problem.

The funnel is clean because it’s a concept that is easy to understand. But the buyers are messy, and their journeys are complex because that is how decisions actually get made – in urgency or some strong desire.

Build for the mess. That is where the opportunity is, because almost nobody else is looking there—a mindset that increasingly defines modern SaaS marketing insights for 2026.