You’re bidding on keywords. Your buyers aren’t searching like that.
Most founders don’t come to Google Ads because they misunderstand marketing. They come because a channel that should be driving growth is failing.
You’re bidding on keywords. Your buyers aren’t searching like that.
Most founders do not come to Google Ads because they misunderstand marketing. They come because a channel that should be driving growth feels fine, but never decisive.
The account looks sensible. The keyword list is logical, the budget is not the problem, and leads arrive regularly. And yet growth feels capped.
Sales teams hesitate. Performance reviews happen. Optimisation follows. Bids are adjusted, ads rewritten, targeting tightened, landing pages tweaked.
What rarely gets questioned is the assumption the entire account is built on.
That assumption is simple. If someone needs what you sell, they will search for it.
For a long time, this belief worked well enough. Today, it increasingly does not.
Why Google Ads feel fine but never decisive
Most Google Ads accounts are built around keywords. Buying decisions are not.
That gap is where performance quietly degrades.
Clicks still happen. Forms still get filled. Costs appear manageable. But downstream, something feels off. Sales conversations start with education rather than intent. Deals take longer to move. Teams argue about lead quality instead of learning from it.
At that point, optimisation becomes the default response.
What goes unchallenged is whether the account reflects how buyers actually arrive at decisions.
The 95/5 reality most teams ignore
In B2B, only a small fraction of your market is actively buying at any given time.
Research from the LinkedIn B2B Institute consistently shows that roughly ninety-five percent of potential buyers are not in-market right now. Only five percent are ready to evaluate solutions.
Most Google Ads strategies are built entirely around that five percent.
That makes high-intent keywords expensive and unforgiving. You are competing where attention is scarce, expectations are high, and tolerance for confusion is low.
In many B2B SaaS categories, solution-led keywords routinely cost three to five times more than problem-led ones. A fifteen-euro click for “software” versus three to five euros for “how do I fix this?” is not unusual.
When your entire strategy depends on intercepting buyers late, you are paying more to speak to fewer people, at the moment they are least patient.
This is not a bidding problem. It is a sequencing problem.
High-intent keywords are not wrong. They are simply late.
How buyers actually use search
Buyers do not search to compare options. They search to reduce uncertainty at specific moments.
They do not experience their situation as a product category. They experience it as friction.
Something is inefficient. Something that used to work no longer does. Something feels risky, unclear, or unnecessarily complex. Search is how they try to make sense of that feeling.
The language they use reflects this. It is situational and descriptive rather than categorical. Buyers search for explanations, reassurance, and clarity long before they search for software names or service labels.
Keywords are not intent. They are a symptom of it.
The AI shift most ad accounts are not built for
This behaviour has accelerated as AI has changed how search works.
Buyers now use large language models as filters, not destinations. They ask questions like, “How do I stop clients from missing appointments?” or “Why does this process keep breaking?”
The answer they receive is rarely a product. It is a method. A framework. An explanation of what is usually wrong and what typically fixes it.
By the time a buyer sees an advert, they often already have a mental model of the problem shaped by AI summaries and recommendations.
Most Google Ads accounts are built as if that model does not exist.
If your ads only show up when someone searches for a tool, you are competing after the diagnosis has already happened. Often without you.
A real SaaS example from the field
Here’s what this looks like in practice.
I worked with a SaaS company offering an online appointment scheduling platform for small businesses. The product was strong. Flexible, no-code, and easier to use than many established alternatives.
The challenge was not capability. It was discovery.
Google Ads and SEO were already active. Traffic arrived. Forms were filled. Yet sales conversations kept starting in the same place. Education before intent.
When we analysed search behaviour, the pattern was clear. People were not searching for “appointment scheduling software” because they wanted to compare tools. They were searching because something in their workflow was breaking.
Instead of bidding primarily on category terms, we shifted budget upstream. We targeted situational queries such as “how to reduce no-show appointments” and “clients keep cancelling bookings.”
Those searches converted at roughly forty percent lower cost per qualified lead. More importantly, sales conversations changed. Calls started with a shared problem rather than a product comparison.
The work did not start in the ad account. It started with positioning.
Messaging shifted towards concrete operational friction. The website was redesigned to remove small UX signals that were quietly undermining trust. Search campaigns followed the same logic. Ads reflected the situations buyers recognised. Landing pages explained why scheduling usually breaks before introducing the platform as a possible resolution.
Lead volume did not spike. Lead quality improved. Sales cycles shortened because buyers arrived with context already formed.
This shift did not come from clever bidding. It came from alignment.
Where most founders misread intent
Most teams treat intent as fixed. Either a keyword has it, or it does not.
In reality, intent is progressive.
Buyers move from uncertainty to clarity over multiple searches, not in a straight line. They explore symptoms before solutions. They seek reassurance before comparison.
Founders optimise for coverage. Buyers respond to relevance.
Ads optimise for clicks. Funnels win with continuity.
Google Ads accounts fail when they collapse this progression into a single moment and try to force conversion there.
The two-layer account structure
A Google Ads account that reflects real buyer behaviour has two distinct layers. Each has a different job, and confusing them is where most performance issues begin.
| Feature | Intent-learning (upstream) | Demand-capture (downstream) |
|---|---|---|
| Buyer trigger | “This process is a mess.” | “I need a tool to fix this.” |
| Search goal | Diagnosis | Evaluation |
| Typical query | Situational or problem-led | Category or solution-led |
| Ad promise | Why the problem exists | Why this is the best option |
| Landing page | Educational and safety-focused | Demo, pricing, or trial |
| Primary metric | Search term insight and clarity | Cost per acquisition |
Most accounts are built almost entirely on the second layer, and then blamed when growth stalls.
Ads that mirror, not pitch
Most ads fail because they answer a question the buyer has not asked yet.
In intent-learning campaigns, ads should mirror the problem, not pitch the solution.
That means naming the friction clearly, reflecting the situation the buyer recognises, and avoiding feature-heavy language.
The goal is not persuasion. It is relevance.
When ads feel familiar rather than impressive, engagement improves. Quality Score improves. Sales conversations improve.
Landing pages that create safety
Sending problem-led traffic to demo pages is one of the fastest ways to lose trust.
Landing pages at this stage should reduce uncertainty, not force commitment.
They should name the problem accurately, explain why it usually exists, and show what typically breaks first. The product should appear as a possible resolution, not the inevitable one.
Calls to action should match the buyer’s state of mind. Exploration before commitment.
This does not reduce conversion quality. It improves it.
What to look at instead of CPL
Founders are conditioned to judge everything by cost per lead. That instinct breaks intent-learning work.
These campaigns should be evaluated by signal quality, not efficiency.
Useful indicators include:
- Search terms that clearly describe real situations
- Engagement with problem-led content
- Shorter sales discovery calls because context is already shared
The question is not “Did this lead convert cheaply?” but “Did this search help us understand how buyers frame the problem?”
Where learning feeds back into scale
The biggest mistake teams make is treating intent-learning as an experiment.
Search terms, ad performance, and engagement patterns from these campaigns should inform demand-capture copy, landing page headlines, sales discovery questions, and positioning language.
Over time, high-intent campaigns become clearer, cheaper, and more predictable because they borrow precision from earlier-stage insight.
This is how learning pays for itself.
Closing
If you keep bidding on keywords without understanding why buyers search, performance stays fragile. Costs rise. Teams optimise without traction.
When you design for decision-making instead, something shifts.
Ads become relevant. Landing pages build trust. Sales conversations start further along. The system stops leaking.
Not because the ads are smarter.
Because the system finally matches how buyers think.