Prospect Research Should Make You Write Less, Not More

Here is a personalised outreach message:

Hi Daniel, I saw that you studied economics at Manchester, started your career at PwC, recently completed a marathon, and posted about your company’s new office. As a fellow believer in continuous improvement, I thought you might be interested in our AI-powered sales platform.

The sender clearly did research. The message still feels worse than a template. Why? Because the research produced facts, not relevance. The buyer is left wondering why a stranger collected personal details that have nothing to do with the business problem.

Research is not the same as evidence collection

Research often becomes a scavenger hunt. Find a hobby. Find a university. Find a recent post. Find a quote. Put it in the opening line. That creates the appearance of effort.

Useful research has a narrower job: it finds evidence that helps explain why the company may have a relevant problem, why the person may care, and why the timing may matter. The question is not, “What can I find about this person?” It is, “What can I learn that changes the reason for contacting this person?” That small shift removes a lot of useless work.

Fact, implication, hypothesis, question

A simple chain turns research into a message.

Fact: The company hired twelve account executives in three months.

Implication: More reps now need accounts, context, and a consistent prospecting process.

Hypothesis: The team may be struggling to keep account selection consistent while onboarding quickly.

Question: Are new reps receiving prioritised accounts centrally, or are they still researching and choosing targets themselves?

The fact alone is not the insight. The implication explains why it matters. The hypothesis admits uncertainty. The question gives the buyer an easy way to confirm or reject the idea. This chain is the bridge between research and relevance.

Three common research failures

Research theatre

The sender collects facts to prove effort: “I noticed your company was founded in 2017 and now has offices in London and New York.” The facts may be accurate. They do not support the commercial conversation.

Flattery automation

The sender uses a recent post as a compliment: “Loved your insightful post about leadership. Your point about culture really resonated.” Then the message jumps to an unrelated pitch. The compliment is not part of the reasoning. It is a decorative toll paid before the sales message.

Surveillance personalisation

The sender mentions personal details that feel intrusive: “Saw you were in Barcelona with your family last week.” Even when the information is public, it can be irrelevant and uncomfortable. Research becomes creepy when the buyer cannot see why the detail belongs in a business conversation.

The detective analogy, with one constraint

A detective collects evidence to answer a question. The detective does not collect every available fact about everyone in the city. Prospect research works the same way. The investigation begins with a question such as:

Is this company likely to be struggling with inconsistent prospecting as it scales the sales team?

Now the research has boundaries. Hiring patterns matter. Job descriptions matter. Team structure matters. The technology stack may matter. The founder’s holiday photos do not. The constraint is what makes the research useful.

A practical hierarchy of research

Level 1: Company movement

What is changing? Hiring, layoffs, market expansion, leadership changes, funding, acquisitions, new products, new customer segments, technology migrations, and organisational restructuring. Movement creates the possibility that an old process no longer fits.

Level 2: Role pressure

How might that change affect the person being contacted? A new market may pressure a sales leader to create pipeline quickly. A larger team may pressure RevOps to standardise workflows. A product expansion may pressure marketing to reach a new audience. The same company event matters differently to different roles.

Level 3: Problem evidence

Is there direct evidence of the issue? Job descriptions naming the task, public complaints, repeated hiring around a manual process, customer reviews, process documentation, interviews, comments from employees, tool changes, and requests for specific expertise. This is where a broad context becomes a stronger hypothesis.

Research needs a stopping rule

Without a stopping rule, research can consume more time than the opportunity is worth. The sender keeps searching for the perfect detail, even after enough evidence exists to ask a sensible question. A useful stopping rule is reached when four things are clear: what changed, what problem may follow, why this person might care, and what simple question can test the idea.

At that point, more research often adds trivia rather than confidence. The goal is not to know everything about the company. The goal is to know enough to start a relevant exchange.

Better research creates shorter messages

An under-researched message often becomes long because it has to explain everything:

We are an AI-powered end-to-end sales engagement platform with advanced features for lead generation, account research, personalisation, multichannel sequences, analytics, and team collaboration. We help organisations improve productivity and generate more revenue. I would love to understand your priorities and explore whether there may be a fit.

The sender lacks a precise reason, so the product description expands. A researched message can be shorter:

You have added twelve AEs while moving into the UK. Is account research still handled by each rep, or has RevOps centralised it for the new team?

The second message says less because the context is doing more work. Research is not supposed to make the message look researched. It is supposed to remove unnecessary explanation.

Negative research is valuable too

Research does not always produce a reason to contact. Sometimes it produces a reason not to. The company may have just renewed a competing tool. The team may be shrinking. The relevant function may be outsourced. The person may have moved roles. The public problem may already be solved.

Removing an account can be a successful research outcome. That idea is easy to miss because prospecting teams are often rewarded for adding contacts, not removing weak ones. But a smaller list with stronger reasons is more useful than a larger list built on wishful thinking.

The relevance filter

For any fact found during research, ask: does this change what we believe about the problem, does it change who owns the problem, does it change the timing, and does it change the question we would ask?

If the answer is no, the fact probably does not belong in the message. Prospect research is not a performance of effort. The buyer does not care how many tabs were opened. Good research makes the reason clearer, the question sharper, and the message shorter.