Time-to-value is a design problem

Picture a buyer who has done everything right. They've identified the problem, researched the options, chosen your product, and signed up with genuine intent to use it.

They are, at this moment, as motivated as they will ever be.

And then your product makes them wait.

At LeadGenius, this wasn't hypothetical.

The platform was historically sales-led, which meant a high-intent user could sign up and then sit for days before experiencing anything, because the journey ran through sales conversations and internal setup before the product ever showed them value.

Days. For someone who had already decided they wanted the thing.

The strange part is that nobody had designed it to be slow. The waiting was an accumulation of organisational choices, each reasonable on its own, that nobody had ever looked at as a single experience.

Which is exactly why I've come to believe time-to-value is a design problem, not just a metric that growth teams argue about in dashboards.

Value, from the user's side of the glass

Before you can shorten time-to-value you have to be honest about what "value" means, and most teams aren't. Account created is not value.

Onboarding completed is not value. Profile filled in is not value. Those are all things the company wanted, dressed up as user progress.

Value is the earliest moment a user could honestly say "this product has helped me." For an analytics tool, maybe it's the first insight they didn't already know. For our platform, it was a user actually working with the product on their own campaign rather than waiting for someone to do it for them.

Once you define value that way, time-to-value becomes something you can draw. Take a real user, start the clock at the moment of intent, and map every single thing that happens before they reach that moment.

Not just the screens. Everything. The approval email.

The scheduled call. The configuration someone internal has to do. The data they have to hunt down.

The step where they weren't sure what to do next and left, planning to come back.

When we mapped this at LeadGenius, the picture was uncomfortable. Most of the elapsed time wasn't in the product at all.

It was in hand-offs and dependencies, in the spaces between touchpoints where the user was simply waiting for us. You cannot see that in a funnel chart, because funnel charts only show the steps you built.

The waiting lives between the steps.

What we changed

The work was to open a self-serve path: letting users start, set up and reach value on their own, with sales entering the journey later and better-informed rather than standing at the front gate.

The design moves themselves weren't exotic. We removed dependencies that existed for company convenience rather than user benefit.

We restructured setup so users could reach something useful before completing everything, instead of finishing everything before seeing anything.

We used templates and guided flows so decisions that used to require a human conversation could be made confidently in the product.

And we made progress visible, because a user who can see they're two steps from value behaves very differently from one who can't tell if they're close or nowhere.

In our case-study framing, that journey went from days to roughly eight minutes, and the work helped drive a revenue lift of around five per cent.

I'm careful with both numbers: design didn't act alone, sales and product and engineering all shaped the transition, and I'd never claim a clean causal line from wireframes to revenue. But the direction was unambiguous.

When motivated users stopped waiting, more of them reached value, and more of the ones who reached value converted and stayed.

That experience permanently changed how I frame my own work, incidentally. I used to present outcomes in product metrics: activation up, drop-off down.

I've since learned that "faster activation became revenue growth" is a more honest and more useful story, because it forces you to trace the whole chain instead of stopping at the metric your team happens to own.

Friction is not one thing

A warning, because "reduce time-to-value" gets flattened into "remove steps" and that's how you get products that feel fast and hollow.

Some friction builds understanding.

When a user connects their own data, configures something meaningful to their business, or makes a genuine choice, they're investing, and that investment often makes the value that follows more real to them.

Strip all of it out and you can deliver "value" the user doesn't recognise as theirs.

Other friction is just your org chart leaking into the user experience. The approval that exists because of an internal policy.

The call that exists because that's how the sales team has always qualified. The form that collects data nobody uses. This is the friction to hunt.

The test I use: does this step help the user understand or shape what they're about to get, or does it only serve our process? Keep the first kind, kill the second, and be suspicious of anyone who claims a step is the first kind without being able to say what the user learns from it.

There's also a middle category worth naming: proof. Users need evidence the product is working before they'll commit deeper.

Early wins, quick confirmations, a small result delivered fast.

If your journey demands full commitment before showing any evidence, motivated users will still leak away, not because the path is long but because they can't tell it's leading anywhere.

A framework you can run this week

If you want to do this for your own product, the sequence is:

Define. Get your team to agree, in one sentence, on the earliest event where the user has honestly been helped. Expect this to take longer than you think.

If growth, product and design each give a different answer, you've found your actual problem.

Map. Follow three or four real users from intent to that event. Include everything: emails, calls, waiting, confusion, internal work they never see. Put elapsed time on every segment.

Remove. Separate friction that builds understanding from friction that serves process. Kill the second category, starting with the biggest time cost.

Prove. Find the earliest possible moment to show the user evidence that this is working. Move it earlier if you can.

Measure. Track time-to-value as an experience metric, then connect it to a commercial one, whether that's conversion, PQL quality or retention.

Do it honestly, with the caveats intact. A defensible "contributed to" beats an inflated "caused" every time.

Why this belongs to design

I keep returning to a simple observation: growth teams own the time-to-value number, but designers shape almost everything the user actually experiences between intent and value.

Every unclear next step, every decision made without context, every moment where the product could have shown progress and didn't. That's the path, and we draw it.

So the question I'd leave you with is the one I now start projects with. What is the earliest event where your user can honestly say "this product has helped me"?

Write it down. Then map every minute and every dependency standing before it, and ask which of them the user would keep.