Driving Lead Growth
Through a Smarter
Contact Flow.

Everything you need
to understand this project.

Note: The company name has been omitted at the request of my former lead. This work has been approved for publication.

Three navigation items.
Zero clarity.

I started by acting as a potential client and going through the entire flow myself. The website had three navigation items: Talent / Labs / Contact. Two questions came up immediately: What is Talent? What is Labs?

Talent was the team allocation service. Labs was project delivery. The labels made sense internally — but meant nothing to people outside the company.

Behavior data confirmed it. Talent had significantly more traffic than Labs — which was strange, since demand for Labs projects was actually higher. My hypothesis: the general contact flow was directing people to the Talent page before identifying their intent, inflating that page's numbers.

Usability tests with 8 participants reinforced what the data was suggesting:

The interviews also surfaced a conflict: Marketing wanted fewer fields to reduce friction. Sales wanted more fields to better qualify leads. Both were right — and that tension shaped the solution.

Essential information first.
Details later.

Phase 1 — Quick wins: Renamed "Talent" and "Labs" with clear descriptions so people understood what they were clicking on. Removed redundant fields. Added a generic inquiry form to capture everything that wasn't a qualified lead — keeping the main forms clean.

Phase 2 — The smarter flow: The form was redesigned as a multi-step experience. The first steps captured only what was needed to schedule a call. Once the meeting was locked in, the form asked for more detail to help qualify the lead.

This solved the marketing vs. sales conflict: reduced friction early, better qualification later. And if someone dropped off before finishing — the most important thing, the meeting, was already scheduled. A progress indicator kept people oriented throughout, and every step had a clear description so people knew exactly what was being asked and why.

Audit Summary of Existing Forms and Process

Key Findings in Competitive Benchmarking

Feedback that's
free from bias.

Before testing the prototype, I ran an async silent critique with the team. Specialists from different areas reviewed the wireframes independently — giving everyone equal space to share feedback without bias or scheduling conflicts.

Each person annotated their own copy of the Figma screens, without seeing anyone else's comments first. Patterns across reviewers carried real weight. Outliers became conversation starters, not vetoes.

Why I always do this: In group reviews, early opinions anchor the rest. Async critique removes that dynamic — and they always catch something I missed. That's exactly the point.

Asynchronous critique setup — each stakeholder reviewed an independent copy to avoid anchoring bias

A flow you can
actually walk through.

After incorporating critique feedback, I ran a second round of usability tests on the prototype. This gave additional evidence to support renaming "Talent" and "Labs," and validated the new multi-step flow.

Handoff included a clickable prototype and detailed documentation: field descriptions, clickable interactions, and developer notes. Everything was also documented in Confluence to make sure nothing got lost in translation.

Final prototype screens — the complete guided flow ready for usability testing

Every detail accessible to the developer — states, conditional logic, and specs per component

Numbers that confirmed
the approach worked.

These results were shared by my former lead while I was already allocated to another project — about two months after launch.

Clearer labels, a smarter flow, and a dedicated path for non-qualified inquiries made the difference on both sides of the form.

• +22% increase in form completions, based on initial usage after launch
• −71% reduction in irrelevant submissions, thanks to clearer form segmentation
• Stakeholders reported a smoother internal process due to the improved data structure

Before → After: the shift from a single long form to a structured, guided experience