ICP fit vs buying intent: the four questions I ask

The question

A company can look like the customers I want and still leave me with unanswered questions about the work.

I ask four questions before choosing an approach: does the company fit the offer, where is the problem visible, what makes it current, and who is close enough to answer?

My working rule is to keep those judgments separate. When the evidence answers only the first, I want the research to help me find the missing answers. Unknown answers tell me what to research or ask the buyer next.

That is a standard I want Mach’s research to preserve. The output should help a seller decide what to investigate, what to ask and when to wait. A confident explanation cannot supply evidence the sources never gave us.

Fit gives me somewhere to investigate

A customer profile can tell me that a company is worth understanding. It may work in a sector I serve, have a team large enough to use the offer or operate in a country where I sell.

Those facts can remove a mismatch. I still need to find out whether a particular problem is present.

Consider a fictional example. I sell software that helps finance teams reduce manual invoice checks. A growing company has a finance team and an invoice-heavy business. It fits the kinds of companies the offer could help.

The research has found no statement about its invoice processing, no relevant job ad and no public project involving it. I have a plausible audience and an unanswered question about need.

A conversation may still be worthwhile. I would explain the work I help with and ask whether the issue applies. Naming an assumed invoice problem as a fact would make the buyer correct the research before discussing the offer.

I need to know what a signal adds

In an r/SalesOperations discussion[1], u/Comfortable-Lab-378 questioned the usefulness of their team’s high-intent flags. They reported that roughly 60% of won deals had been flagged high intent, alongside a similar share of what they called “everything.”

The second group is not defined precisely, and the post does not explain how the score was calculated. It is one team’s reported comparison, rather than a market benchmark or a causal test.

I would need to know which accounts were compared, when they were flagged and what information was available at that time. Without that, I cannot tell from those percentages whether the signal helped choose the next account.

I would look at missed accounts too. Google’s guide to precision and recall[4] explains why found items and missed relevant items both matter. Missed buyers are often unknown. My bar is to report what was checked and leave the rest unresolved.

A small review can help expose a disagreement. I would give two reviewers the same relevance rule and source material, include accounts the system set aside, and keep the cases where their judgments differ. That can give the team a specific question to investigate. It does not create a complete recall estimate.

A company signal still needs a person

The person is a separate part of my decision.

In an r/sales discussion[2], u/garden_gnorm said their difficulty was that “the intent is org wide, not individuals.” They described a broad cybersecurity-research signal at a large enterprise as unhelpful.

Another commenter, u/Onion_Hands, valued direct website browsing most and added that industries differ. Their advertising business-development context differs from an enterprise cybersecurity example. Neither view establishes a universally best signal.

I want to know what the source identifies. It may name a company, a team, a person or only a topic. Those are different starting points for research.

For the fictional invoice offer, a company’s size can help assess fit. A finance leader’s own description of manual reconciliation would support a more specific question about the work. If the person has not described the problem, I would keep that part of the approach as a question.

Separate four pieces of the judgment

For an account I am considering, I want a short note with four separate answers.

I want an answer to be allowed to remain unknown. If I have not found the finance process, that gap gives me no basis for calling the process good or bad. It tells me where the next question belongs.

Research needs a stopping decision

There is a cost to finding those answers.

In a research-time discussion[3], u/ElectricElephant4128 described checking websites against prospect requirements and spending a day on a list. It is the commenter’s report, without an independently checked time log.

In the same thread, u/ReachBeautiful1268 suggested a short timer, then a generic message if no personalization emerged. That is one person’s method, rather than a tested optimal research duration.

I would use time as a constraint on the work, while still asking what decision the research needs to support. A timer cannot establish that the company fits or that the person is relevant.

My working cutoff is whether I can name the next action and the uncertainty that remains. That action might be a question to a buyer, another source to check, preparation for an existing meeting or a decision to wait. I do not need every available fact before making each of those decisions.

What I want the model to preserve

We first tried Jev, a decision model from TypeSafe AI[5], and then built our own custom decision model. We call our family of decision models Mach.

My standard for any model in that work is that the decision stays attached to the seller’s offer and the available evidence. I want the seller to be able to see which observation supports the recommendation and what remains an inference.

The inspected agent-research format separates fit signs from levels of problem evidence. It can distinguish a kind of company that could have a problem, conditions that make it plausible, a visible sign and a buyer describing it first hand. A hypothesis can carry evidence for it, evidence against it and a way to test it.

Those fields give the research room to preserve the distinction. The interpretation still depends on the sources and the checks that follow.

In the inspected lead-search rules, a direct request, a company event and a fit-only finding take different paths. A fit-only result can be marked “worth a look” or set aside; that branch does not label it “reach out now.”

Some inspected account-research code also retains Jev scoring alongside code-based rules, with a fallback when Jev is unavailable or a check fails. The source review did not establish the current live configuration or measure an effect on replies.

The relationship changes what I would do next

I want research to begin with the relationship the team already has, too.

If a meeting is booked, the useful next action may be preparation. If an open deal has an owner, a public finding may belong with that owner before anyone considers another introduction.

An inspected steering step considers recorded meetings and open deals before composing next-move guidance. It can also infer meeting status from some notes or tasks. I would keep that inference visible for a person to check; other research paths and deployment settings may differ.

A current public event does not erase what the buyer has already told the team. I want the next action to use both sources of context.

Try the four questions on one account

Choose an account that looks like an obvious fit. Write one sentence for fit, one for the buyer problem and one for timing, with a source beside each. Name the person closest to the work and the team’s last interaction with the company.

Then mark the sentence that depends on an assumption. That is where I would decide whether to ask a question, find another source or let the account wait.

Mach’s published guide explains how to turn a signal into a useful message.

How this post was made: AI assisted the research and drafting. Public quotations and their limits were checked against retrieved records and the team’s source ledgers. Implementation details were checked against a source snapshot dated 5 November 2026. The source review did not establish live configuration or customer outcomes.

Which of those four answers is your research leaving as an assumption?

Related reading

This post is part of our guide to MEDDPICC and qualifying a deal.

Related reading: They already use a competitor. What should we say and BDR meaning.