VERONIKA ONDROVÁ
CV CONTACT

SELECTED WORK

EXPERIENCE & DESIGN

Following the signal from insight to experience.

I turn research, behaviour and complex product needs into clearer learning experiences, interactions and tools people can use.

  1. 01RESEARCH-LED EXPERIENCE DESIGN

    WHEN A LEARNING PROBLEM REVEALED A SYSTEMS PROBLEM

    Research into a confusing request revealed competing mental models and shaped clearer, scenario-based guidance for external and internal users.

    PROBLEM
    People used the same terms but understood the task differently.
    EVIDENCE
    Interviews and cross-team research revealed where the mental models and processes diverged.
    DECISION
    I translated the findings into scenarios that clarified the decisions users needed to make.

    SIGNAL PENDINGCASE STUDY IN DEVELOPMENT

  2. 02LEARNING PRODUCT & UX

    WHEN CONTENT BECAME A JOURNEY

    A targeted learning-path pilot grew into a connected product experience that helped suppliers understand what to learn now and what to do next.

    PROBLEM
    Training existed as separate pieces and stopped helping when the work became more complex.
    EVIDENCE
    Supplier research confirmed demand for recommended paths; after launch, learning traffic increased by 130.3% YoY.
    DECISION
    I turned the pilot into a connected experience with recommendations, visible progress and meaningful next steps.
    FOLLOW THIS SIGNAL

  3. 03INTERACTIVE LEARNING DESIGN

    WHEN LEARNING BECAME A CHOICE

    A game-based learning experience replaced passive reading with decisions, scenarios and feedback that responded to each choice.

    PROBLEM
    Learners were reading about decisions instead of practising them.
    EVIDENCE
    Scenarios let people try options and see the consequences of each choice.
    DECISION
    I designed branching scenarios with meaningful feedback instead of static content.

    SIGNAL PENDINGCASE STUDY IN DEVELOPMENT

  4. 04AI-ENABLED LEARNING DESIGN

    WHEN A HUMAN VOICE SCALED WITH AI

    An AI-assisted voiceover workflow explored how learning could reach more markets without losing clarity or human review.

    PROBLEM
    Recording and translating voiceovers by hand did not scale across markets.
    EVIDENCE
    AI-generated voices reached good quality when paired with careful human review.
    DECISION
    I built a workflow where AI drafts the audio and people approve every version.

    SIGNAL PENDINGCASE STUDY IN DEVELOPMENT

  5. 05CONTEXTUAL PERFORMANCE SUPPORT

    WHEN SUPPORT LEARNED TO STAY SILENT

    A concept for in-context help built on one principle: the right hint can help, but the default state should stay silent.

    PROBLEM
    Constant tips and pop-ups taught users to ignore help altogether.
    EVIDENCE
    Help was most useful when it appeared only in the moments people actually needed it.
    DECISION
    I designed simple rules that decide when to show a hint and when to stay quiet.

    SIGNAL PENDINGCASE STUDY IN DEVELOPMENT