How to Find People Who Are Ready to Buy

The people most likely to buy are not always the people who look most like your ICP. They are the people whose situation has changed, whose problem is active, and who are doing something about it.

Most founders know how to make a list of potential customers.

Pick an industry. Pick a company size. Find the job title. Build the spreadsheet.

Then comes the harder question:

Which of these people actually have a reason to buy now?

That is where buying signals become useful.

Your ICP tells you who could be a good customer. A buying signal gives you evidence that something is happening with that person or business now.

And there is a big difference between those two things.

This is not about predicting who will definitely buy. You cannot know that from the outside.

The goal is simpler: find people whose current situation gives you a credible reason to talk to them.

What does "ready to buy" actually mean?

Someone is ready to buy when the distance between having a problem and taking action to solve it has become small enough that a purchase is a realistic next step.

That can happen in different ways.

• They are actively looking for a solution.
• They are comparing ways to solve the problem.
• They have asked for recommendations.
• They have started talking about price, timing or implementation.
• A recent event made the problem more urgent.
• They are already using a workaround and it is no longer good enough.

None of these guarantees a sale.

A person can visit a pricing page because they are researching. A founder can ask for software recommendations and never buy. A company can hire for a role without purchasing your product.

So do not look for one magic signal.

Look for a pattern of evidence.

The Cusicon Ready-to-Buy Model

When you are searching for customers, use five questions to decide whether a person is worth investigating.

Think of these as filters, not a scoring system.

If someone fits your ICP but has no active problem, they are a prospect.

If they have the problem but have not started doing anything about it, they may be a future prospect.

If they fit, have the problem, experienced a trigger and are actively looking for a solution, you have a much stronger reason to start a conversation.

1. Start with the problem, not the buying signal

A common mistake is to search for signals before deciding what problem the signal should represent.

That creates noise.

For example, suppose you sell software that helps small businesses follow up with leads. You could search for companies hiring salespeople, companies raising money, companies visiting your website, or companies posting on LinkedIn.

All of those might contain useful information.

But first define the problem:

Now the search becomes much more specific.

You can look for people complaining about missed leads. You can look for companies hiring someone to handle lead follow-up. You can look for founders asking how to automate follow-ups. You can look for businesses publicly discussing a growing lead volume.

The signal becomes useful because it is connected to a problem.

This is the same logic behind the Cusicon Need Signal: person + problem + trigger + consequence + action is stronger evidence than generic demographic fit.

2. Look for trigger events

A trigger is something that changes the customer's situation.

Triggers matter because buying usually happens for a reason. Something became more expensive, more urgent, more difficult, or newly possible.

Common triggers include:

• A company starts hiring for a role related to the problem.
• A founder launches a new product or service.
• A business expands into a new market.
• A team grows quickly.
• A company changes its technology stack.
• A customer publicly complains about an existing process.
• A business announces a new initiative.
• A person moves into a new role with a new responsibility.
• A workaround stops working as the business grows.
• A buyer begins actively comparing alternatives.

Current B2B intent systems use similar categories, including website behavior, research activity, company news, hiring and changes in key contacts. citeturn0search1turn0search3

The important part for a founder is that you do not need an expensive intent-data platform to understand the principle.

You can start by watching the public places where your customers already reveal these changes.

3. Search where people describe the problem

If you want to find someone ready to buy, go where people talk about what is currently going wrong.

Search engines, Reddit, LinkedIn, industry communities, product review sites, job boards, public forums and comment sections can all contain useful evidence.

Do not search only for your product category.

Search for the problem language.

The second group gets closer to the moment before a purchase.

The person has moved from knowing that a category exists to describing a situation they want to change.

4. Read complaints as demand signals

Complaints are useful because they contain the buyer's own language.

A complaint can tell you:

• what is frustrating them,
• what they expected to happen,
• what they tried already,
• what is costing them time or money,
• and what they wish existed instead.

But a complaint alone is not proof that someone is ready to buy.

Someone can complain about a problem for years without spending money to solve it.

The stronger signal is a complaint followed by action.

That progression is far more useful than collecting complaints as a list of pain points.

5. Watch for solution-seeking language

The language people use changes as they move closer to a decision.

Early research tends to sound broad:

• "What is the best way to..."
• "How does this work?"
• "What does everyone use for..."

Evaluation becomes more specific:

• "Has anyone tried X versus Y?"
• "Which tool is better for a team of five?"
• "Does this integrate with..."

Purchase-oriented language becomes more concrete:

• "How much does it cost?"
• "Can we start this month?"
• "How long does setup take?"
• "Do you support this use case?"
• "Can someone show me how it works?"
• "What would we need to get started?"

Recent sales research makes the same distinction: concrete, action-oriented questions tend to provide stronger evidence of buying intent than vague expressions of interest. citeturn0search12turn0search13

Still, context matters. "How much does it cost?" can mean genuine purchase intent or simple market research.

Read the question together with the person's problem, fit and timing.

6. Look for people already spending money on the workaround

One of the strongest places to look for potential customers is among people who are already paying to solve the problem badly.

Why?

Because you are not trying to create the idea that the problem deserves money.

They have already made that decision.

They might be paying an employee. They might be using a spreadsheet. They might be paying an agency. They might be using three different tools. They might be doing the work manually every Friday.

The workaround tells you something important:

Your job is then to understand what is still broken.

That is often a better starting point than convincing a completely unaware market that your category matters.

7. Use job postings as problem evidence

Job postings can reveal operational problems before a company explicitly says it wants a software product.

Suppose a company starts hiring someone whose job is to manually perform a process your product automates.

That does not automatically mean they should buy your software.

But it tells you the problem exists and the company is allocating resources to it.

That makes the company worth investigating.

Job postings are also useful because they often describe the work in concrete language. You can take those phrases and search for other companies experiencing the same problem.

This turns one signal into a discovery method.

8. Find repeated behavior, not isolated clicks

If you control the website or product, watch for behavior that repeats.

Examples include:

• multiple visits to a pricing page,
• return visits to the same product page,
• repeated visits to documentation,
• comparison or integration pages being viewed,
• returning after an earlier sales conversation,
• asking implementation questions,
• inviting another person into the evaluation.

Intent platforms commonly combine these kinds of behavioral signals with company and contact context rather than treating one page view as proof of readiness. citeturn0search1turn0search5

For a small founder, the lesson is simple: look for movement, not just attention.

9. Stack signals before you reach out

One signal can be noisy.

Several related signals are more useful.

Imagine your ICP is small SaaS companies with five to twenty employees.

You discover one company that:

• fits your ICP,
• just launched a new product,
• is hiring for a sales role,
• is discussing lead volume publicly,
• and has started researching tools in your category.

You do not know that they will buy.

But you have a much stronger reason to investigate than you would have from company size alone.

This is why current intent-data guidance increasingly emphasizes recency, multiple signals and ICP alignment instead of treating every digital action equally. citeturn0search7turn0search14

10. Verify before you sell

This is the step founders skip.

You find a signal and immediately write:

"Hey, I saw that your company is hiring. We help companies like yours..."

The problem is that you are acting on your interpretation before checking whether the problem is actually present.

Instead, use the signal to form a hypothesis.

The signal gets you into the right neighborhood.

The conversation tells you whether you are actually at the right house.

Where should founders look for ready-to-buy people?

You do not need to monitor the entire internet.

Choose a few places where your customers naturally reveal problems and changes.

Search engines

Look for problem queries, comparison searches, alternative searches and implementation questions.

Communities

Look for people asking for recommendations, describing failed workarounds, comparing products or asking how others solve a problem.

Social platforms

Look for public posts about current problems, launches, hiring, expansion and tool changes.

Job boards

Look for roles that indicate a company is investing in a process your product helps improve.

Competitor reviews

Read what customers like, dislike and wish were different. The complaints can reveal both the problem and the language buyers use.

Your own product

Track returning visitors, pricing interactions, product usage and direct questions. Your existing audience may already contain the strongest signals available to you.

A simple weekly buying-signal workflow

You can turn all of this into a small weekly process.

Keep a simple signal log.

Over time, this log becomes more valuable than a giant spreadsheet of cold prospects.

You start learning which signals actually lead to conversations, which ones produce false positives, and which triggers repeatedly show up before customers buy.

The goal is not to predict buyers perfectly

There is a temptation to turn buying signals into a perfect machine:

Signal appears → customer buys.

Real markets do not work that cleanly.

Intent data can be noisy. People research without buying. Companies change direction. Budgets disappear. Decision-makers leave. A problem can be urgent and still not receive budget.

Even current buying-intent research warns against treating a single signal as proof of purchase readiness. Stronger approaches combine multiple pieces of evidence and verify the underlying situation. citeturn0search7turn0search14

For a founder, that uncertainty is not a reason to ignore signals.

It is a reason to use them correctly.

From buying signal to customer

The real workflow is not:

Find signal → pitch.

It is:

That last step matters.

Your first version of a buying signal model will be wrong in places.

You might think funding is a strong signal and discover that funded companies are too busy to buy. You might ignore job postings and discover they are one of the best indicators for your market. You might believe pricing-page visits matter most and learn that direct comparison questions are much stronger.

Your customers teach you what the useful signals actually are.

The founder's advantage

Large sales organizations can buy databases, intent platforms and enrichment tools.

A founder can do something those systems cannot replace: talk to the person.

You can see a public complaint, identify the trigger, understand the workaround and ask one good question.

That conversation can teach you more than another thousand names added to a prospecting spreadsheet.

Start with the problem. Find the trigger. Look for observable movement. Verify it. Then talk to the person.

That is how a buying signal becomes useful.