I'm a mixed-methods UX researcher specializing in B2B SaaS products, behavioral research, and bridging qualitative insight with quantitative evidence.
Scroll down to see my selected work ↓Despite feature maturity, adoption of Performance Alerts remained critically low. Prior hypotheses came from behavioral data alone — the "why" behind partner behavior had never been explored through direct conversation. This study set out to close that gap.
10 Growth/Enterprise partners:
End-to-end ownership — research design, interviews, qualitative coding, synthesis, stakeholder alignment on prioritization, and defining the UX metrics to track post-launch impact.
Some key insights from the final UXR report — the rest is not included due to confidentiality.
Partners default to manual, reactive monitoring instead of the alerting feature — not because it's undiscoverable, but because they don't yet trust it to catch what matters. This is the root cause behind every other finding below.
Some partners never noticed the alert bell existed; others found it but missed the setup flow; others completed setup but weren't sure what action to take. A single onboarding tooltip won't fix all three.
Partners want per-journey, percentage-based thresholds instead of one fixed global rule — rigid thresholds were named as a specific reason for abandoning alerts altogether.
Without a timestamp, partners can't tell a new issue from a recurring one — and more importantly, can't confirm whether a fix actually worked, so they quietly return to manual checking.
UMUX-Lite ease-of-use and capability-fulfillment scores, plus an overall usability score, were collected to validate the qualitative findings — results landed below industry benchmark, consistent with the trust gap identified above.
Exact figures withheld due to confidentiality.
Findings were synthesized into a prioritization framework — ranked by frequency, importance, and effort — and reviewed with stakeholders; the resulting design recommendations were handed off to the development team.
User feedback indicated that partners were not fully leveraging the AI-powered journey creation feature. The research aimed to understand expectation gaps and evaluate whether the feature truly met user needs in real-world workflows.
International enterprise B2B partners across multiple regions:
End-to-end ownership — usability test design, moderation, thematic synthesis, stakeholder alignment on prioritization, and defining the UX metrics tracked to validate post-launch impact.
Across all usability testing sessions, Lack of guidance and Need for guidance emerged as the dominant themes, followed by Manual editing and Lack of content & preview.
Exact frequency counts withheld due to confidentiality.
Some key insights from the final UXR report — the rest is not included due to confidentiality.
AI-generated outputs had an approximate accuracy rate of ~40%, making users feel that correcting the output was more exhausting than building from scratch — leading many to abandon the feature entirely.
Lack of guidance emerged as the top pain point across sessions. Instructions did not communicate the required level of detail, resulting in vague inputs and irrelevant outputs that further eroded trust.
Most participants reported needing to manually correct AI output. Even when directionally correct, fine-tuning branch-by-branch was seen as a net negative — users felt they were doing more work, not less.
Users preferred a back-and-forth, iterative refinement model rather than a single-prompt-to-output flow — indicating a desire for AI as a collaborative tool, not a black box.
Ratings were sharply polarized — some participants found the feature straightforward, others struggled significantly — suggesting it works well for a specific user type but fails to serve the broader partner base.
Exact scores withheld due to confidentiality.
Research uncovered critical gaps in in-product guidance and transparency around AI-generated outputs. Design improvements informed by these findings led to a 42% increase in feature adoption within 3 months — with 85% of research outputs actioned by the product and design teams.
As journey complexity scales — some workflows containing 300 to 800+ elements — navigating the canvas becomes increasingly difficult. This research mapped real user mental models to identify friction points and surface evidence-based product opportunities.
End-to-end research ownership: research plan, participant recruitment, interview moderation, affinity mapping, quantitative analysis, stakeholder alignment on prioritization, and defining the UX metrics to track post-launch impact. Solo researcher.
SUS and UMUX-L scores were collected to validate the qualitative findings — overall usability landed at a "Good" level, short of "Excellent," with requirement fulfillment showing wider variation than ease of use, suggesting unmet needs beneath a surface-level acceptable experience — likely tied to hidden or undiscoverable features.
Exact scores withheld due to confidentiality.
Some key insights from the final UXR report — the rest is not included due to confidentiality.
Experienced users develop internalized spatial memory of their journeys. This self-built navigation strategy works — but breaks down for new team members or during handoffs.
When zoomed out, users rely on color patterns rather than text labels to navigate — indicating a genuine unmet need for visual hierarchy tooling within the product.
The search function indexes content, but users think in terms of logic and conditions. Custom channel names — which users invest time creating — remain unsearchable, making the tool largely unusable for power users.
Slow load times on large journeys create a "fear of breaking things" — users actively avoid editing, leading to stagnant workflows and reduced overall feature engagement.
Research recently completed. Based on the findings, design decisions are now being made by the product and design teams. Outputs are actively shaping the next iteration of the canvas experience.
Understanding how enterprise partners test their journeys on Architect — which methods they use, why certain approaches are avoided, and what friction exists — to inform product decisions around testing tooling.
Enterprise partners across multiple regions and verticals:
End-to-end ownership — interview design, moderation, behavioral analysis, stakeholder alignment on prioritization, and defining the UX metrics tracked to validate post-launch impact.
Some key insights from the final UXR report — the rest is not included due to confidentiality.
Differences between available testing methods are not well understood. Users default to the most familiar approach — not because it's optimal, but because alternatives feel unclear, leading to under-utilization of more precise tools.
Testing a live journey requires stopping the entire flow — not viable for ongoing campaigns. This forces users to build parallel test setups, adding overhead and increasing the risk of misconfiguration.
Users prioritize flow-level testing (conditions, logic, attributes) over channel content verification — yet the product's UI affords the opposite, creating a fundamental mismatch between user goals and product design.
Scores placed testing solidly in the "difficult" range — confirming the current testing experience is a significant friction point across user segments and regions.
Exact score withheld due to confidentiality.
Research-driven design improvements delivered a measurable outcome: frustration rate dropped from 23% to 0.2% within 3 months of implementation — with 75% of research outputs actioned by the product and design teams.
Storybooks are one of the most preferred childhood activities — but does the story theme (realistic, anthropomorphic, or fantastical) affect what children actually learn from them? This thesis examined whether theme influences both analogical problem-solving and prosocial behavior.
Advisor: Assoc. Prof. Deniz Tahiroğlu · Boğaziçi University, Institute for Graduate Studies in Social Sciences
Children who listened to realistic stories were significantly more successful at solving physical problem analogies compared to those who heard anthropomorphic or fantastical stories. However, this effect did not hold for social problem contexts — suggesting theme-learning relationships are domain-specific.
Children exposed to realistic storybooks showed a greater increase in sharing behavior from pre-test to post-test, compared to anthropomorphic or fantastical conditions. Helping and honesty behaviors improved across all conditions, suggesting storybooks broadly promote prosocial development regardless of theme.
Good research doesn't live in a repository — it changes what gets built next. I care as much about getting insights acted on as generating them.
I'm a UX researcher with 4+ years of experience in B2B SaaS, most recently at Insider One, where I led 20+ end-to-end research cycles across product discovery, usability evaluation, and behavioral analytics.
I'm equally rigorous in qualitative and quantitative research, and built a practice of closing the loop after research — tracking pre/post changes in adoption, frustration, and usage rate to prove impact, not just claim it. Toptal Certified UX Researcher.
My background sits at the intersection of academic psychology and applied product research. I led a self-designed thesis study with 200+ preschool-aged children at Boğaziçi University, contributed to a TÜBİTAK-1001 funded national study with 5,000+ participants in collaboration with METU and Ege University, and presented research at international conferences including SRCD (USA) and BCCD CEU (Budapest).
I care deeply about research that actually gets used — not just documented.
Let's ConnectI'd love to hear about your project. Drop me a message.
haticeseymagurbetoglu@gmail.com