AI startup website optimization through canonical action research and continuous experimentation: An iterative UX design study

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master_Romeo_Gianluca_2025.pdf (4.27 MB)

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School of Science | Master's thesis
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2025-09-28

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Human-Computer Interaction and Design

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Degree programme

Master's Programme in ICT Innovation

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en

Pages

70

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Abstract

Early-stage AI startups face critical challenges in optimizing their digital presence for lead generation while operating under severe resource constraints. Traditional website optimization approaches often fail in complex technical service domains where abstract capabilities must be communicated to diverse audiences. This thesis investigates how the integration of Canonical Action Research (CAR) methodology with Continuous Experimentation (CE) principles can enable effective website optimization in resource-constrained AI startup environments. The research addresses three key questions: how CAR-CE integration enables systematic website optimization, which design elements demonstrate strongest conversion impact, and how integrated digital marketing influences lead generation effectiveness. Using a mixed-methods approach, the study employed two iterative CAR cycles spanning three months within an Italian AI consulting startup, combining comprehensive web analytics through PostHog with qualitative user interviews and systematic hypothesis testing. Results revealed a critical conversion hierarchy where semantic clarity and information architecture significantly outweigh visual design elements in driving qualified leads. Key findings challenge conventional startup optimization approaches by establishing that contemporary UI/UX design improvements, while achieving strong engagement metrics, cannot overcome fundamental communication barriers in complex technical domains. Qualitative analysis identified four critical conversion barriers: ambiguity in core offering, technical jargon alienating users, flawed information hierarchy, and universal demand for tangible demonstrations over abstract capability descriptions. The research demonstrates that social media marketing functions primarily as brand awareness amplification rather than direct conversion, with offline-to-online integration achieving the strongest measurable attribution effects. Practically, the research provides actionable guidance for early-stage technical startups, emphasizing message clarity and user comprehension optimization before aesthetic improvements, fundamentally reorienting resource allocation strategies for sustainable growth through improved digital presence.

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Supervisor

Fagerholm, Fabian

Thesis advisor

Mäntylä, Vihtori

Keywords

canonical action research, continuous experimentation, website optimization, AI startup, user experience design, digital marketing

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https://urn.fi/URN:NBN:fi:aalto-202510208320

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[dipl] Perustieteiden korkeakoulu / SCI