What 15 Years in Presales Taught Me

I did not plan on spending 15 years in presales. I was in IT. The dream was to become a Chief Information Officer someday.

Then I took a job running Solutions Engineering and Network Engineering at Conduit Global. I did not think of it as a presales role at the time. But that was the moment everything changed. Somewhere along the way, what felt like a detour became the destination. And looking back, I am glad it did.

Technical credibility is rented, not owned

Early in my career I thought the job was about knowing the product. If I could answer any question, handle any objection, and demo anything on the fly, I was doing my job.

That view is partially right and mostly wrong.

Technical credibility comes from demonstrating that you understand the customer's problem, not just your solution. I have watched SEs who knew the product inside and out lose deals to people who knew it less but listened better. The buyer did not feel understood. The demo was impressive but irrelevant.

The most technically credible moment in a sales cycle is not when you answer a hard question. It is when you ask one that the prospect had not thought to ask themselves.

The best SEs are investigators, not just presenters

The mental model shift that changed how I approached the job was moving from "my role is to present and convince" to "my role is to investigate and guide."

The investigator mindset changes everything. Instead of preparing a demo, you prepare questions. Instead of anticipating objections, you surface concerns early. Instead of building toward a close, you build toward clarity.

When a prospect has full clarity on their problem and genuine confidence that your solution addresses it, the close takes care of itself. When they do not have that clarity, no amount of demo polish gets you there.

Capacity is the hidden constraint in every presales org

I spent years in leadership watching teams underperform without understanding why. The pipeline was there. The talent was there. The product was strong. But the team was always behind, always stretched, always putting out fires.

The answer was almost always capacity. Not enough hours in the week to do the work well. Too many deals at once, too many custom requests, too many reactive POCs that were never properly scoped.

Capacity is invisible until it breaks. By the time a leader notices the team is overloaded, the best people are already looking for other jobs, and the deals that needed attention three weeks ago are now lost.

Building a real capacity model, one that accounts for logged hours, projected commitments, and typical prep and overhead ratios, is one of the most important investments a presales leader can make. I wish I had done it earlier at every company.

Win rates are a lagging indicator of everything else

Every presales leader tracks win rate. Very few can tell you what actually drives it.

In my experience, win rate is an output of three things: deal qualification, discovery quality, and POC execution. If you are qualifying deals well, running thorough discovery, and executing POCs against clear success criteria, your win rate goes up. If any of those three break down, the win rate eventually reflects it.

The problem is that by the time win rate moves, the problems are already systemic. The discipline is to track the leading indicators: discovery completion rate, POC success rate, product gap frequency by deal stage. Those tell you where to intervene while there is still time.

The function is undervalued and it is partly our fault

Presales has historically done a poor job of telling its own story. Win rate is shared with leadership. The rest of what the function produces, customer intelligence, product feedback, technical risk identification, competitive positioning data, almost never gets surfaced in a structured way.

That leaves presales leadership making the case for headcount and investment based on gut feel and anecdote rather than data. It is a weak position.

The teams and leaders who are changing this are the ones investing in operational rigor: structured discovery, tracked POC outcomes, organized product gap data, real capacity models. They are making presales legible to the rest of the business.

That is the version of the function I spent 15 years trying to build. I think we are finally getting close to having the tools to do it properly.