Enterprise conversion research | Lauren Sener
Skip to main content
Lauren Sener

Enterprise automation platform  ·  CRO  ·  AI-assisted research

Building a research-grounded AI workflow for enterprise conversion decisions

An enterprise automation company wanted to improve high-value conversion pages for trials, events, demos, and related journeys. When conventional user testing was proposed, the client questioned whether it justified the cost.

I developed an alternative that could provide structured directional evidence without pretending to replace human research. Using the client's existing personas and prior human research as the foundation, I created meaningfully different wireframe concepts and evaluated them through synthetic personas using two AI models. The first trial engagement expanded into an ongoing CRO program across multiple page types.

Role
Senior Experience Designer
Scope
Audit · hypotheses · strategic wireframes · synthetic testing · analysis · recommendations · client readouts
Engagement
Fall 2025 to present
Status
Ongoing CRO program
Sanitized structural recreation of the trial-detail work. Two genuinely different page strategies were evaluated against each other, and the recommendation combined the strongest mechanism from each rather than declaring a winner.

The 60-second version

The problem
The client wanted stronger high-value conversion journeys but did not believe conventional user testing justified the cost.
I owned
Audit, hypotheses, strategic wireframes, synthetic-persona testing, output review, AI-assisted synthesis, analysis, recommendations, and client presentations.
The pivotal decision
Treat synthetic testing as evidence-grounded directional research, not a substitute for human behavior, and use it to compare genuinely different conversion strategies.
What changed
Winning concepts were implemented and the initial engagement expanded into an ongoing CRO program.

10.8% to 18.3%

Observed trial-page conversion in the reported month after implementation

Client-reported post-implementation result. Exact implementation timing and experimental controls were not available, so this is not presented as proof of sole causation.

My scope

I owned

  • Experience audit
  • Hypothesis development
  • Strategic wireframes
  • Synthetic-persona testing structure
  • Quality review
  • AI-assisted synthesis
  • Interpretation
  • Recommendations
  • Client presentations

Collaborators

  • UI designer
  • Development team

They owned

  • Final visual design
  • Implementation of approved recommendations

Protected

This case study contains protected project work.

The executive brief above is public. The full study covers the method, the three conversion decisions, the tested concepts, the reported outcome, and the limitations. Access is provided to recruiters and hiring teams.

Need access? Email Lauren and she will send a password.

Case sensitive.

{{ errorText }}

In production, protected copy and imagery are not shipped to the browser until access is granted. In this prototype the gated content is requested only after the password is accepted, so the unauthenticated page source does not contain it.

Full case study  ·  access granted

The research constraint became a design problem

{{ p.constraint.lead }}

{{ p.constraint.principle }}

{{ para }}

{{ p.constraint.missingLabel }}

  • {{ row }}
    •

{{ p.constraint.haveLabel }}

  • {{ row }}
    •

{{ p.constraint.close }}

I built a repeatable evaluation workflow around the limitation

{{ p.method.lead }}

  1. {{ step.label }}

    {{ step.note }}

    {{ p.method.tag }}

{{ p.d1.kicker }}

{{ p.d1.heading }}

{{ p.d1.frame }}

{{ p.d1.risksLabel }}

  • {{ row }}
    •

{{ p.d1.question }}

{{ p.d1.caption }}

{{ p.d1.recLabel }}

{{ p.d1.recLead }}

  1. {{ note.title }}

    {{ note.body }}

    2.

{{ p.d1.why }}

{{ p.d1.principle }}

{{ p.d2.kicker }}

{{ p.d2.heading }}

{{ p.d2.frame }}

{{ p.d2.gapsLabel }}

  • {{ row }}
    •
{{ p.d2.aName }} {{ p.d2.aTitle }} Hypothesis. {{ p.d2.aHyp }}

  1. {{ band.label }}

    {{ band.note }}

    2.
{{ p.d2.bName }} {{ p.d2.bTitle }} Hypothesis. {{ p.d2.bHyp }}

  1. {{ band.label }}

    {{ band.note }}

    2.

{{ p.d2.evidenceLabel }}

{{ p.d2.evidenceNote }}

  • {{ row }}
    •

{{ p.d2.interpretationLabel }}

{{ p.d2.interpretation }}

{{ p.d2.decisionLabel }}

{{ p.d2.decisionLead }}

  • {{ row }}
    •
Recommended direction Clarity-led hybrid

  1. {{ band.label }}

    {{ band.note }}

    2.
{{ p.d2.caption }}

{{ p.d3.kicker }}

{{ p.d3.heading }}

{{ p.d3.frame }}

{{ p.d3.aName }}

{{ p.d3.aTitle }}

{{ p.d3.aSub }}

Optimized for

  • {{ row }}
    •

{{ p.d3.bName }}

{{ p.d3.bTitle }}

{{ p.d3.bSub }}

Optimized for

  • {{ row }}
    •

Evidence

Synthetic-persona response patterns across executive perspectives. Stated reactions, not observed behavior.

  • {{ row }}
    •

Decision

{{ p.d3.decisionLead }}

  • {{ row }}
    •

{{ p.d3.meta }}

{{ p.d3.metaNote }}

{{ p.d3.caption }}

The method became an ongoing decision framework

{{ p.program.lead }}

  1. {{ step.n }}

    {{ step.label }}

    2.

{{ p.program.stepsNote }}

The repeatable cycle

  1. {{ row }}
    2.

{{ p.program.close }}

The winning direction shipped, and the client reported a major conversion increase

{{ p.impact.lead }}

{{ p.impact.chartLabel }}

  • {{ row.label }}

    {{ row.from }}
    {{ row.to }}

Upper bar: December 2025Lower bar: January 2026

{{ p.impact.chartCaption }}

{{ p.impact.boundaryLabel }}

{{ para }}

{{ p.impact.accurateLabel }}

{{ p.impact.accurate }}

{{ quoteText }}

{{ p.impact.quoteAttr }}

{{ p.impact.quoteContext }}

The method was useful because its limits stayed visible

{{ p.limits.lead }}

{{ p.limits.keptLabel }}

  • {{ row }}
    •

{{ p.limits.limitLabel }}

  • {{ row }}
    •

What I would validate next

{{ p.limits.nextLead }}

Comprehension

  • {{ row }}
    •

Trust

  • {{ row }}
    •

{{ p.limits.methods }}

{{ p.studio.label }}

{{ p.studio.heading }}

{{ p.studio.lead }}

{{ shot.alt }}
{{ shot.caption }} {{ shot.expand }}

Working through a similar kind of complexity?

I’m interested in senior UX roles where research and design shape consequential product decisions.

Next: Building a research-to-partner pipeline  ·  Smurfit WestRock  ·  Product discovery  ·  5 opportunity referrals