Summary:
A LinkedIn connection is a signal, but it does not explain intent. Rather than inferring why new connections reach out, I ask them directly. Their responses reveal professional interests, unexpected areas of alignment, and insights about my audience that profiles and engagement data alone cannot provide. This article explores why curiosity can outperform manufactured personalization, how structured outreach can create authentic conversations, and why AI should help us preserve relationship context rather than pretend we already understand it.
LinkedIn tells me when someone wants to connect with me.
It doesn’t tell me why.
For years, like most people, I accepted connection requests that appeared relevant, looked at the person’s profile, perhaps exchanged a brief thank-you, and moved on.
Another connection joined the network.
But I eventually started wondering what that number actually meant.
Why did this person connect with me?
Was it something I wrote?
Do we share a professional interest?
Are they looking for expertise?
Did someone recommend me?
Are they simply expanding their network?
Or did LinkedIn suggest my profile and they clicked Connect?
There is an obvious way to find out.
I ask.
A Simple Question Changes the Conversation
When someone new connects with me, I reach out with a simple premise:
Thank you for connecting. I’m curious what prompted you to reach out.
There is no offer.
No calendar link.
No lead magnet.
No attempt to qualify them.
No clever transition into a sales pitch.
I genuinely want to know.
And people answer.
Not everyone, of course. No outreach message produces a 100 percent response rate, nor should that be the objective.
But the responses I receive are often far more thoughtful than I might expect from a simple LinkedIn connection.
People tell me they have been reading my articles.
Some mention specific subjects that interest them.
Others describe similarities between the problems they are addressing and the issues I write about.
Some see overlap between their work and mine even though we operate in different disciplines.
Others simply appreciate a particular perspective and want to remain connected to it.
And occasionally someone explains a potential business reason for connecting.
Each response teaches me something that LinkedIn’s connection notification can never tell me.
Otherwise, I Am Guessing
Without asking the question, I am effectively doing what many CRM and marketing systems do.
I am inferring intent from observable behavior.
Someone working in cybersecurity connects with me?
They must be interested in cybersecurity governance.
An enterprise architect connects?
Probably my architecture content.
A consultant?
Perhaps advisory work.
A board member?
Maybe board governance.
Those are reasonable hypotheses.
They are also guesses.
The person’s actual reason may be completely different.
We increasingly live in a business environment built around inferred intent.
Someone downloads a white paper.
Intent signal.
Someone visits a pricing page.
Intent signal.
Someone attends a webinar.
Intent signal.
Someone connects on LinkedIn.
Intent signal.
Enough signals accumulate and the person gets assigned a score, entered into a workflow, or placed into an outreach sequence.
Sometimes those inferences are useful.
But there is another source of intent data that we frequently overlook.
Ask the person.
The Difference Between Capturing a Signal and Starting a Conversation
A LinkedIn connection is a signal.
A response explaining why someone connected is context.
Those are fundamentally different kinds of information.
The first tells me what happened.
The second begins to tell me why.
That distinction becomes increasingly important as organizations introduce AI into customer relationship management, marketing, recruiting, business development, and professional networking.
AI is exceptionally good at finding patterns.
Given enough information, it can infer why someone might be interested in us.
It can examine a person’s profile, employment history, posts, comments, interests, mutual connections, and previous interactions.
Then it can generate a personalized message based on those observations.
Technically, that is impressive.
But there is something almost absurd about deploying increasingly sophisticated artificial intelligence to infer something the person might simply tell us if we ask.
The Question Does Something Else
There is another reason this approach works.
The message is not pretending there is already a relationship.
It is creating the possibility of one.
That is a subtle but important distinction.
Much of modern outreach begins with manufactured familiarity.
“I noticed your impressive background…”
“Given your experience in…”
“I’ve been following your work…”
“I thought this would resonate…”
Sometimes those statements are genuine.
Sometimes they are fields assembled by software.
Recipients increasingly know the difference—or at least suspect it.
A sincere question changes the dynamic.
Instead of telling someone why I think they should talk to me, I give them an opportunity to tell me why they chose to connect.
That shifts the conversation from targeting to curiosity.
And curiosity produces information.
Some of the Answers Surprise Me
One of the most useful outcomes is discovering connections I would not necessarily infer from someone’s profile.
People working outside my immediate technology disciplines explain that they see parallels between my work in governance, accountability, architecture, and decision-making and the challenges they face in their own fields.
That matters.
If I classify those connections solely according to job title or industry, I may completely misunderstand why my work resonates with them.
Their responses reveal something broader.
Ideas travel across professional boundaries.
Governance is not exclusively a cybersecurity problem.
Architecture is not merely a technology discipline.
Accountability is not confined to boards.
Decision authority matters wherever organizations are trying to turn strategy into execution.
Those insights help me understand not only individual relationships but also my audience.
That makes the conversation valuable even when no commercial opportunity exists.
Not Every Conversation Needs a Conversion
This may be the most important part.
I am not asking why someone connected so I can determine how quickly to sell them something.
If that were the hidden objective, people would eventually recognize the technique for what it was.
The question would simply become another funnel.
That would destroy much of its value.
Some conversations lead somewhere professionally.
Some may result in introductions, collaboration, advisory work, speaking opportunities, or other possibilities.
Many will not.
That’s fine.
A professional network should contain relationships whose value cannot be calculated by immediate pipeline contribution.
Sometimes the value is simply understanding why another person finds your ideas worth following.
There Is Still a System Behind It
This approach does not require abandoning process.
In fact, process makes it sustainable.
A growing professional network becomes difficult to manage without some structure. There is nothing inherently wrong with reminders, workflows, CRM systems, templates, or AI assistance.
The question is what the system is designed to accomplish.
Is it designed to maximize the number of messages sent?
Or is it designed to create better conversations?
Those are very different optimization targets.
My argument about LinkedIn outreach is that personalization is not the same thing as relationship.
A system can know your name, title, industry, interests, and engagement history and still demonstrate that it has forgotten the actual conversation.
The reverse is also true.
A structured outreach process can help create authentic relationships if the process is designed to discover context rather than manufacture it.
That is the flip side of the automation problem.
AI Should Help Us Remember, Not Pretend
The future of professional relationship technology should not be AI generating increasingly convincing simulations of personal attention.
We can do better than that.
AI can help identify when a new connection deserves attention.
It can preserve previous conversations.
It can surface relevant context.
It can remind us when someone has expressed an interest, declined an invitation, changed roles, or raised an issue worth revisiting.
It can help us manage networks larger than human memory can reasonably maintain.
But there should still be room for something remarkably simple:
A genuine question.
Because the objective should not be to make automated outreach indistinguishable from human outreach.
The objective should be to use technology to make human interaction more informed.
Stop Guessing
We spend enormous amounts of money trying to understand intent.
We build analytics platforms.
We calculate engagement scores.
We analyze behavioral signals.
We deploy predictive models.
We use AI to infer what someone might want.
All of those capabilities have legitimate uses.
But sometimes the shortest path to understanding another person’s intent is not another model.
It is a question.
Someone connects with me.
I could guess why.
Instead, I ask.
And the answers are considerably more valuable than the connection count.
Don’t use automation to pretend you know someone. Use it to create the opportunity to actually know them.