Clinical trust, patient journeys, and the workflows in between.
Work spanning a top healthcare system in the American Southwest,
a global leader in diabetes care, and a global medical-device
company.
8
Patients, one at a time
Ran 1:1 moderated "walk-the-store" usability sessions for a
top healthcare system in the American Southwest, exposing
buried symptom checkers and unclear calls to action that
stalled appointment scheduling. Recommendations realigned the
information architecture to patient mental models via open
card sorting.
8
Clinicians on glucose dashboards
Led remote moderated tests with healthcare professionals on
continuous glucose monitoring dashboards for a global leader
in diabetes care. Uncovered a critical print limitation and
heavy reliance on hover states, then recommended a
one-stop-shop clinical dashboard with clearer visual urgency.
~60%
Sales friction cut on clinical AI
International interviews with 15 embryologists and lab
managers for a MedTech AI generative tooling company. Black-box
distrust and HIPAA anxiety reframed the roadmap toward a
conversational clinical partner and science-led enablement.
2
Service-line templates validated
Validated orthopedics and cancer-care page templates and
advised progressive disclosure for anxious patients,
establishing a persona-led navigation baseline for the
system's conversion engine.
Work spanning a Fortune 50 bank, a top-10 US retail bank, a
Fortune 100 financial services company, and a global gaming
platform's payments.
75
Applicants, three products, one diagnosis
Synthesized open-ended feedback across personal accounts,
credit cards, and business loans for a Fortune 50 bank.
Application length and repetitive questions emerged as the
top abandonment drivers, met with recommendations for time
estimates, pre-approval signals, and upfront transparency.
73%
IVR failure rate, quantified
Tree testing with 17 users measured a severe failure rate in
a top-10 US retail bank's phone-banking tree. A 30-person
open card sort then rebuilt the menu around "Self-Service"
and "Money Movement" clusters.
58 → 81
SUS jump on a rewards flow
Benchmarked a fintech rewards redemption flow, redesigned
against the data, and proved the lift with the same numbers
leadership trusted: task completion up 53%, redemption
drop-off down 47%.
24
Sessions with an AI dining concierge
Evaluated an AI restaurant-recommendation chatbot for a
Fortune 100 financial services company, catching natural
language failures around dates and mealtimes. Findings fed
directly into algorithmic optimization and clarifying
preference prompts.
2
Platforms mapped for regional payments
Mapped the full alternative-payment checkout on web and
mobile web for a global gaming platform's UK launch, keeping
a regulated regional integration frictionless.
Sector · AI & Emerging Tech
Human-in-the-loop research for products that think.
Work spanning a Fortune 50 technology company, a global
medical-device company, a Fortune 100 financial services company,
and Flyhomes.
87.5
SUS for AI-powered home search
Human-in-the-loop validation of an AI home search feature at
Flyhomes scored an A- on the System Usability Scale, with
dendrogram clustering revealing four distinct interaction
patterns that shaped the launch design.
23
Ambient AI trust gaps
Moderated 60-minute sessions across two studies for a Fortune
50 technology company: tablet out-of-box setup and hands-free
AI messaging on smart speakers. Surfaced how users misread
ambient AI status cues, underestimated always-listening
privacy implications, and stalled on dual account linking—plus
a disappearing-keyboard hardware bug caught before launch.
~60%
Clinical AI sales friction
Fifteen international embryologists and lab managers mapped the
mental model for trusted clinical AI: a proactive conversational
partner, not a black-box grader. Roadmap and enablement shifts
followed.
NLP
Failures traced to the algorithm
Pinpointed natural language bugs in an AI concierge, from
"next Friday" date parsing to lunchtime context, turning
vague dissatisfaction into a concrete optimization backlog.
HITL
Guardrails as a deliverable
Recommended consent-first AI features and supervised
note-taking with explicit user permission, establishing
ethical guardrails that protected a premium first impression
of the device ecosystem.
Work spanning a Fortune 50 quick-service brand, a global pizza
chain, a European sports-betting operator, and a former restaurant
employer.
151
Participants in a delivery benchmark
Mixed-method study comparing a Fortune 50 quick-service
brand's app against three competitor delivery apps. Hidden
deal restrictions and shifting delivery estimates were
eroding trust, answered with automated rewards at checkout
and real-time visual transit tracking.
10
Heuristics, severity-coded
A rigorous heuristic evaluation of a global pizza chain's
deals pages exposed gated shopping, burdensome navigation,
and recognition-over-recall failures, each mapped to fixes
targeting checkout conversion.
6
Global competitors mapped
Unmoderated competitive research with 14 participants across
four countries for a European sports-betting operator's 2026
feature launch. Banner blindness and deposit walls drove
drop-off, met with literal naming tests and a centralized
offers hub.
+20–30%
Sales for three straight months
Field research at a struggling restaurant location turned
customer interviews into menu, quality, and personalization
changes that reversed its decline until the pandemic forced
closure.
Work spanning a leading global rideshare platform, a Wi-Fi
sensing home-security innovator, and a major US telecom provider.
471
Survey responses over three months
Managed a longitudinal study with 40 drivers for a leading
global rideshare platform, correlating motivation drops with
GPS failures and unclear bonus structures, and charting a
retention path built on navigational reliability and earnings
transparency.
2
Diary-study rounds on invisible security
Co-led a comparative seven-day diary study testing Wi-Fi
sensing security against camera-based systems. Identified a
"Silent Entry" failure loop that broke users' mental models
of safety.
1
Diagnostic tool, proposed and adopted
Cross-functional work with engineering produced a
pre-installation diagnostic to filter out bad ISP data, plus
a floor-plan motion visualization to bridge the trust gap of
cameraless coverage.
E2E
Activation journey, documented
Walked a major US telecom's device activation end to end,
from identity verification to first dashboard, delivering the
friction-annotated flow diagram that seeded their journey
mapping program.
Sector · Real Estate & PropTech
From first visit to AI-assisted home search.
Work at Flyhomes as the in-house researcher across acquisition,
onboarding, home search, and AI trust.
+60%
Homepage engagement
Two-phase research revealed almost nobody realized they could
search for homes on the site. A search-centered redesign
matched buyers' mental models and lifted engagement, booked
calls, and activation.
87.5
SUS for AI home search
Interviews, listing analysis, card sorts, and usability
testing shaped an AI search experience that translated
subjective buyer priorities into explainable match scores.
+46%
Tour adoption
Better discovery and clearer calls to action turned browsing
behavior into real-world home tours, with booked calls up 30%
from research-led onboarding changes.
1
Research operation, built from zero
Company-wide ResOps infrastructure, recruitment pipelines,
templates, and a cross-functional repository, scaled research
capacity and democratized testing for product managers and
designers.
Promotions, payments, and the journeys between bet and checkout.
Work spanning a global sports-betting platform and a global gaming
entertainment storefront—always anonymized under NDA.
14
Bettors, six competitors, one acquisition map
Unmoderated competitive UX with screen-recorded onboarding across
six global betting products. Banner blindness, inconsistent
promotion names, and deposit walls emerged as the drop-off
pattern—met with recommendations to A/B test literal naming and
centralize offers in a dedicated hub.
2
Surfaces mapped for UK alternate checkout
Flow investigation of a regional alternative-payment Happy Path
on web and mobile web for a global gaming platform, including
pre- and post-video checkout states, delivered as a full visual
payment-journey breakdown.
During COVID, Helping Hands Community coordinated volunteers to
home-deliver food boxes to at-risk neighbors. As contract UX
researcher and part-time designer, I stood up formal research,
ran interviews and mobile onboarding tests, and mapped why so
many volunteers delivered once and never returned.
When
Role
UX Researcher · Contractor
Scope
Volunteer journey + retention
Methods
Interviews · Usability · Service blueprints
Selected work from this role
From one-time helper to returning volunteer.
NonprofitVolunteer retentionQualitative
research
Why volunteers deliver once and disappear.
Interviews, mobile onboarding tests, and service blueprints
surfaced six friction themes across the volunteer journey,
translated into POV statements, a future-state flow, and 18
concrete recommendations.
02 · UX Researcher · Former employer · Real estate &
mortgage
Flyhomes
UX Researcher · Real estate & mortgage
As the in-house researcher, I led work across acquisition,
onboarding, home search, and AI trust, connecting user evidence
to product, design, and brand decisions.
When
Role
Lead UX Researcher
Scope
Product + brand + AI search
Methods
Mixed methods
Selected recommendation
What a Flyhomes product
leader
says
“Zack is a UX super star.
His customer-driven insights made an immediate impact on our entire product team.
He pairs strong customer empathy with an ability to pinpoint the
most important customer problems for the team to go solve.”
A two-phase research program identified why qualified
leads abandoned before searching, then tested homepage and
brand concepts that made search the center of the
experience.
We turned unstructured listing language into searchable attributes
and paired it with weighted buyer preferences to make every result
more relevant and explainable.
At Winston Francois I owned end-to-end research operations for
B2B SaaS, MedTech, and FinTech clients. I independently sourced,
recruited, and managed 46 highly specialized participants across
three verticals, then led Final Research Handoff presentations
that turned raw qualitative data into personas, decision
frameworks, and product recommendations for C-suite, Product,
and Engineering partners.
When
Organization
Winston Francois
Selected work from this role
Clinical AI Adoption
MedTech AIClinical AIInternational research
Clinical AI Adoption
Interviews with 15 international embryologists and lab managers exposed black-box distrust, HIPAA friction, and a product that graded embryos when clinicians wanted a conversational clinical partner, then redirected the roadmap and cut sales friction by about 60%.
As a UX researcher at Applause, I run agency research across
AI, healthcare, finance, food and beverage, gaming,
entertainment, and other sectors. Each team has its own
culture, pace, and product maturity, so I adjust my approach to
fit the room.
Methodology
Spans both quantitative and qualitative, including diary studies, heuristic evaluations, user
interviews, usability studies, and surveys, supported by tools like Qualtrics, Lookback, Condens,
and Google Workspace, alongside whatever else the client already uses.
Responsibilities
I partner on recruitment, run the end-to-end study, lead the analysis and synthesis, meet with
participants, write the reports, and lead readouts with stakeholders.
Selected work from this role
Agency research across AI, healthcare, finance, and gaming
I research the moments that decide whether a product earns trust or loses it.
01
Learn-Iterate-Launch
Driving Engagement at Flyhomes
Flyhomes · Former employer · 2022
62% of qualified leads abandoned the platform before completing
their first search or tour, and the home search feature, Flyhomes'
key experience, was only engaged with by 11% of traffic. Usability
testing exposed why: almost nobody realized they could search for
homes on the site. A second phase tested the rebrand and a redesigned
homepage centered on search to better match buyers' mental models.
+60%homepage engagement
+30%booked calls
+20%activation rates
Read the full case study
Driving engagement
A two-phase research program spanning onboarding, lifecycle
communications, brand, and the homepage experience.
RoleLead UX Researcher
Timeline2022
FocusActivation + engagement
MarketsEnglish + Mandarin
ApproachTwo-phase mixed methods
Key business problem
Strong acquisition. A broken first mile.
Flyhomes faced a critical business challenge: 62% of
qualified leads abandoned the platform before completing
their first home search or tour. Analytics showed decent
top-of-funnel conversion, but those gains evaporated during
activation.
The home search experience, a key activity for every
homebuyer, was engaged with by only 11% of traffic.
Key insight
The defining “oh $hit” moment.
During usability testing, almost every participant failed
to realize they could even search for homes on our website.
Less than a quarter noticed the search icon in the top-right
corner; those who did thought it searched a database.
I also discovered that excessive communication and a long
activation process were pushing new users away, compounding
the discoverability problem.
Why are they hiding the home search? I just want to browse like on Zillow!
Results
Research moved the homepage and the customer journey.
Strategic insights and post-study collaboration informed a
comprehensive rebrand and website redesign, making search
the cornerstone of the experience. I coordinated with
product development, marketing, brand management, and
creative design to carry the evidence into execution.
+60%Homepage engagement
−30%Customer communications
+30%Booked calls
+20%Activation rate
+60%SMS open rates
+359%Lost-lead SMS engagement
We brought lifecycle marketing, product marketing, and sales
together across English and Mandarin markets. Guided by my
customer journey map, the teams used data-driven insights to
create more resonant content and optimize communication
cadence through rigorous experimentation.
Research as a team sport
Alignment was built into the process.
By involving stakeholders from beginning to end through
1:1s, group meetings, and participant-viewing invitations,
I built alignment throughout the study. I also broke down
silos so the research could drive holistic impact across
design, lifecycle marketing, sales, and art and brand.
Embedded team structure across the research program.
Phase one · Customer quotes
The experience felt hidden and overwhelming.
I think if they lead with letting me browse instead of contacting me over and over, I would have
been happier upfront.
This search looks like a database search, not a home search bar.
Nothing important should ever be more than two clicks away…
There was a lot… When I first signed up, I felt like I was getting a ton [of emails].
ThemesOverlooked functionalityOutreach frequency
Teammates reviewing and building on the research findings.
Our response · Phase one
Make every touchpoint earn its place.
We developed a new content strategy that prioritized search
visibility, deeper product education, and clear customer
value in every communication.
I introduced a customer journey map to clarify who was
sending what and when, then optimized sequencing and cadence
to reduce overload. We also redesigned the homepage to make
search the focal point, which led me to initiate a second
research round to test design options using observational
and attitudinal feedback.
I started with stakeholder interviews to understand the
problem space, time constraints, and assumptions. A kickoff
aligned the team and established a communication plan. I
then presented study options, offered recommendations, and
partnered with stakeholders on the best approach.
01Key questions
02Learn
03Iterate
04Learn
05Launch
Phase 01
Map and improve new-user onboarding.
Diary study with pre- and post-interviews to track sentiment and goals.
Walk-the-store interviews to analyze first impressions and the onboarding journey.
“Break-up letters” to understand departures and identify opportunities.
Phase 02
Evaluate rebranded website engagement.
Walk-the-store testing to gather qualitative feedback on rebranded prototypes.
A/B tests to compare engagement across versions.
Identification of the design most effective at driving interaction.
What I learned
Participation works best when it is intentional.
01
Strategic stakeholder involvement
Involving too many people in every meeting slowed
decisions. I limited follow-up attendance and invited the
stakeholders most relevant to each research session and readout.
02
Tailoring insights for different teams
Marketing preferred a dedicated report for deeper
collaboration, while other teams benefited from targeted
readouts. Adapting the delivery improved engagement and actionability.
Our next steps
Testing the rebrand in phase two.
During phase two, I tested homepage design, brand content,
and messaging as part of the rebrand. This approved
highlight reel outlines part of that approach and my
communication style.
●
My colleague's face has been hidden as an additional privacy measure at her request.
02
Two-Phase Research
Disrupting Real Estate Search with AI
Flyhomes · Former employer · Nov 2022 – Jun 2023
Traditional search could filter price, beds, and baths, but not
natural light, architectural style, or neighborhood ambiance. We
turned unstructured listing language into searchable attributes
and paired it with weighted buyer preferences to make every result
more relevant and explainable.
+83%feature completion
+46%tour requests
+44%sign-ups
Read the full case study
An AI-assisted search experience built around the way
homebuyers describe their lives.
RoleLead UX Researcher
TimelineNov 2022–Jun 2023
ScopeDiscovery through launch
MethodsInterviews · Testing · A/B
Overview
A home search should understand more than a spreadsheet can.
Finding the right home is about lifestyle, ambiance, and
personal preferences, signals traditional search tools
often miss. In November 2022, I led the research and
contributed to the implementation of an AI-powered
Flyhomes search feature designed to bridge that gap.
We used natural language processing to turn unstructured
listing descriptions into structured home attributes, then
paired them with a personalized match score. The experience
helped buyers surface relevant homes faster and understand
why each one matched what mattered to them.
The work was featured by Business Wire and
USA Today.
The problem
The details buyers cared about were hidden in paragraphs.
Most real estate websites prioritize structured
data, price, beds, baths, and square footage, while
overlooking preferences like natural light, architectural
style, neighborhood ambiance, or proximity to grocery
stores.
Buyers had to read every property description manually,
making search feel like trying to spot the right tree in a
dense forest. Paid social campaigns were driving traffic,
but only a fraction of visitors found homes they loved or
booked a tour, the critical next step in engaging with
Flyhomes.
The solution
Three connected moments made search personal, fast, and clear.
01
Personalize the experience
Buyers select the home features they care about and set
how important each one is, creating a profile with room
for both must-haves and nice-to-haves.
View animated preference setup
02
Save homebuyers time
Listings are ranked by a personalized match score,
reducing the number of irrelevant homes buyers need to
review without hiding lower-scoring options.
View animated match scores
03
Make every listing easier to scan
Feature tags appear directly on listing detail pages so
buyers can quickly understand which parts of a home
align with their preferences.
View animated listing details
Approach & timeline
Two research phases carried the idea from discovery to launch.
Phase 01 · FormativePhase 02 · Evaluative
Nov ’22User interviews
Dec ’22Listing analysis
Jan ’23Journey mapping
Feb ’23Questionnaire design
Apr ’23Card sorts
May ’23Usability tests
Jun ’23A/B testing
01
Started Nov 2022 · 3 months
Discovery & design
Identify the preferences missing from traditional
search, then build a model that could connect those needs
to the language in real listings.
01
User interviews
I interviewed prospective homebuyers and current
customers to understand which meaningful attributes
typical filters missed. Participants repeatedly cited
grocery access, neighborhood ambiance, architectural
character, and the feeling of natural light.
02
Listing analysis
We analyzed more than 10,000 property listings, focusing
on unstructured agent remarks. This showed how frequently
the attributes buyers valued appeared in real inventory
and what the product could reliably support.
03
Questionnaire design
I synthesized the evidence into a preference flow that
balanced high-coverage attributes such as proximity to
schools and modern style with lower-coverage, high-value
needs such as natural light and nearby restaurants.
Journey mapping
Mapping the end-to-end experience revealed where
personalization could remove effort without taking
control away from buyers.
Our hypothesis
Structured preferences would make relevant homes surface faster.
Higher engagementRelevant results would give buyers a reason to keep
exploring.
More tour requestsA tailored shortlist would make the next step feel
more confident.
Better lead generationA personalized entry point would convert more
visitors into leads.
From raw text to relevant homes
The product connected listing intelligence to buyer intent.
Input · Listing data
AI-processed listings
ChatGPT and Scale AI parsed agent remarks for attributes
hidden in free-form text. A dedicated back-end service
converted phrases into fields such as “lots of natural
light” or “big backyard.”
Output · Personal ranking
Match score algorithm
Questionnaire responses became a weighted preference
profile. The system scored every property and prioritized
top matches without excluding lower-scoring homes,
reducing fear of missing out.
02
Started Apr 2023 · 2 months
Iteration & launch
Test how people interpreted the experience, refine the
information architecture, and validate that
personalization improved real product behavior.
01
Usability testing
I ran three rounds with five users per round. Iteration
between rounds simplified question wording and added
tooltips for terms such as “open concept,” improving
clarity without slowing the flow.
02
Card sorting
I conducted card sorts with 10 homebuyers to organize a
broad set of home attributes around user mental models
rather than internal real estate terminology.
03
A/B testing
We compared the AI-based search with the existing
experience, measuring completion, satisfaction, sign-ups,
and in-person tour requests.
Key insights
Buyers wanted personalization without losing control.
Insight 01Tags looked like filters.
Participants worried that preferences would hide
listings because their established filter mental model
implied strict exclusion.
Insight 02Not every preference is equal.
Buyers naturally separated must-have fundamentals from
nice-to-have features, but a binary interaction could
not capture that nuance.
Iterative refinements
We changed the model from selection to prioritization.
Multiple design reviews and testing rounds simplified
the questions, expanded the attribute set, and made the
results easier to understand without overwhelming
buyers.
Rebalanced match-score weighting so nice-to-haves would not overshadow location and
price.
Compared completion, satisfaction, and tour-request behavior with the existing search.
Replaced binary toggles with importance weighting for every preference.
Design decisions were traced directly to observed buyer behavior.Final validation
Participants reported that the refined experience could
save significant time, the outcome the team set out to
create.
How the solution works together
Listing details and user-defined priorities combine into
a match score for every home. The score ranks
recommendations while visible tags explain why each
result is relevant.
The impact
AI made search feel more human.
By making subjective preferences searchable and showing
buyers why a home matched, Flyhomes reduced search effort
and helped more people take the next step.
Fifteen international embryologists and lab managers did not want a
binary embryo grader. They wanted a proactive clinical partner that
could explain itself. Black-box scores, HIPAA anxiety, and slow
system speed were quietly teaching labs not to trust the product.
The research reframed the roadmap and cut sales friction by about
60%.
~60%sales friction reduction
15EU + US clinical experts
60-mindepth interviews each
Read the full case study
The shock
The product was optimized to grade. The users were optimized to
reason. Across Europe and the US, embryologists and lab managers
described the AI they would actually trust as a conversational
"super brain" that educates them and analyzes the whole clinical
picture. A reactive binary score fought that mental model and
made distrust feel like good clinical judgment.
How we got here
A MedTech AI generative tooling company needed to understand
clinical adoption barriers for IVF and embryology workflows. As
lead researcher through Winston Francois, I owned the study
end to end: specialist recruitment, 60-minute semi-structured
interviews with 15 international experts, synthesis, and a Final
Research Handoff for C-suite, Product, and Engineering partners.
The investigation
The protocol mapped mental models of clinical AI, then pressure-
tested black-box transparency, HIPAA and data privacy concerns,
system speed, error states, and training expectations. This was
not a preference test on screens. It was an evaluation of whether
the product architecture matched the way labs make high-stakes
decisions.
What kept blocking adoption: unexplained scores,
privacy anxiety, slow results that forced manual double-checks,
high-friction error states that created IT tickets, and an
enablement gap. Clinical leaders did not prioritize software
training, so the product had to earn trust in the language of
published science.
What we found
1. Partner, not grader. Experts expected AI to
act as a proactive conversational partner. The binary grader
framed the product as a judge instead of a collaborator.
2. Transparency is a clinical requirement.
Black-box algorithmic opacity and HIPAA concerns were not edge-
case objections. They were active adoption blockers.
3. Speed debt becomes workload debt. Poor system
speed forced users to manually double-check AI scores, increasing
labor instead of reducing it.
4. Trust starts before the UI. Aligning the tool
with published scientific papers and offering vendor-led video
training created immediate credibility with clinical leaders.
What changed
I advised pivoting the product roadmap toward a holistic,
predictive AI simulator, made transparency and performance debt
explicit for Engineering, recommended automating paperwork-heavy
error recovery, and reframed enablement around science-backed,
vendor-led training. The documented result: about a 60% reduction
in sales friction once the trust story matched how clinicians
actually evaluate tools.
A user opens the rewards screen, taps "redeem," and bounces. That
single abandoned flow hid a usability problem worth millions. We
benchmarked it, redesigned against the data, and proved the lift
with the same numbers leadership trusted.
58 → 81System Usability Scale
+53%task completion
−47%redemption drop-off
Read the full case study
The moment
We watched the bounce happen live, a real customer
mid-redemption, giving up three taps from success. Starting
there, instead of a clean benchmark intro, made the business
cost viscerally clear to stakeholders within the first minute.
What we did
A baseline usability benchmark (SUS + task analytics), a
heuristic teardown, and three rounds of moderated testing on
redesigned flows. Every change was validated against the same
metrics the baseline established.
What changed
SUS climbed from 58 to 81, task completion rose 53%, and
redemption drop-off fell 47%. Because we measured before and
after with the same yardstick, the redesign was unkillable in
review, the numbers did the persuading.
05
Three-Act Structure
Three Months of Proof: How Field Research Reversed a Restaurant's Decline
Le Pain Quotidien · Former employer
A Le Pain Quotidien location in Brentwood, LA was bleeding sales
and customers in late 2019. As Assistant General Manager, I treated
it like a research problem, direct customer interviews, mental
model mapping, evidence-based pitches to management. Sales climbed
20–30% for three consecutive months. Then COVID forced the
closure. The restaurant didn't survive, but the research
methodology did.
+20–30%sales for 3 months
−6%regional churn
1location reversed
Read the full case study
Act I, The problem (late 2019)
A Le Pain Quotidien in Brentwood, LA was in trouble. Sales
were down, regulars were fading, and shutdown rumors were
circling. As Assistant General Manager I could have guessed at
fixes, new menu items, discounts, more marketing, but I
chose to treat it as a research problem instead.
Act II, The research & action
Over several weeks I conducted direct customer interviews to
understand their mental models. Three findings emerged:
1. Quality perception gap. The actual product
quality didn't match the "high-quality" mental model customers
held of the Le Pain Quotidien brand.
2. Missing personalization. The experience
lacked the individualized touches that competitors like
Starbucks offered as standard.
3. Menu ceiling. Customers wanted higher-end
options the menu didn't carry, and were going elsewhere to
find them.
I retrained staff on personalized communication, pitched
management with evidence from the interviews, and secured
approval for cost-effective localized product changes that
closed the quality gap.
Act III, The results
Sales increased 20–30% for three consecutive months. Regional
churn dropped 6%. Positive customer feedback surged. The
research worked, the location had reversed its decline.
Then COVID-19 forced the closure in early 2020. The
restaurant didn't survive the pandemic.
The pivot
This experience didn't end with the building. It proved I
could uncover root causes through direct user research,
translate insights into business action, and deliver measurable
outcomes, core UX research skills I carried into roles with
Helping Hands Community, Flyhomes, Winston Francois, Applause,
Orbello, and beyond. The restaurant closed, but the methodology
survived.
06
Hero's Journey
Why Volunteers Deliver Once and Disappear
Helping Hands Community · Nonprofit contract · Jul–Dec 2021
During COVID, Helping Hands Community — a tech nonprofit founded by
ex-Google and Lyft leaders — mobilized volunteers to home-deliver
food boxes to at-risk neighbors. Deliveries were happening, but
volunteers were quietly churning after a single shift. As contract UX
researcher (and part-time designer), I stood up the org's first formal
research practice, prioritized the work by business and user impact,
and treated retention as a journey problem. Interviews, mobile-first
usability tests, service blueprints, and synthesis produced six
friction themes, POV statements, a future-state volunteer flow, and
18 concrete recommendations the team could ship against.
6friction themes uncovered
18recommendations delivered
50%+volunteers arriving via mobile
1stformal research practice at HHC
Read the full case study
End-to-end research arc I used at Helping Hands — from framing
the right questions through stakeholder-ready deliverables.
The call to adventure
Home delivery was the program's hardest-working channel and its
leakiest. People signed up with good intentions, completed one
delivery run, and never came back. Nobody knew exactly why.
Recruiting harder would not fix a broken experience — so I
treated retention as a journey problem, not a headcount problem,
and went straight to the volunteers themselves.
Helping Hands sat at a B2C and B2B intersection: at-risk
neighbors receiving food, home-delivery volunteers, partner
organizations, and internal ops. My first move was not a single
study — it was a research portfolio. I listed every plausible
research project in a spreadsheet and scored each on business
impact, user-experience impact, resources, and time, then focused
on the highest-impact, lowest-waste work. For the volunteer
retention study I wrote a full research plan: discussion guide,
screeners, process outline, and participant criteria — the first
formal research plan the org had run.
Constraint No prior research baseline; lean nonprofit resources
I worked directly with stakeholders from a founding team with
Google and Lyft product DNA, which meant high expectations for
rigor and a real appetite for journey-level thinking — including
problems that lived off the screen.
Trials on the path · how the research ran
Finding the right people was half the work.
Some segments were narrow — especially home-delivery volunteers.
I recruited through Facebook groups and Reddit, then ran a second
filter most screeners miss: a short pre-interview call before any
session was booked. That kept the sample honest when the segment
was scarce.
Remote usability tests on volunteer sign-up.
Analytics showed more than half of volunteers arrived on mobile,
so every onboarding test ran on both desktop and mobile. I
focused on two segments pulled from prior volunteer data —
people aged 18–25 and people 55+ — because those cohorts
represented different device habits, physical constraints, and
expectations. Sessions were exploratory rather than timed: the
goal was conceptual models and failure points, not stopwatch
optimization.
Semi-structured interviews, recorded with consent.
With no research partner in the room, I recorded Zoom sessions so
I could stay present in the conversation and take structured notes
from the footage afterward. Because there was no prior research
corpus, the guide stayed semi-structured on purpose — tight enough
to answer the core questions, loose enough to chase surprising
turns. Each interview walked the full arc from “I wonder what
volunteering here is about?” to the quiet moment after the last
drop-off.
Service design beyond the UI. Drawing on UCLA
Extension service-design training, I mapped front-stage and
back-stage work in service blueprints across journey stages —
consent and rights flows, information checks, handoffs ops owned
that volunteers never saw. Several of the retention leaks only
showed up once the blueprint made those handoffs visible.
Off-the-screen process mapping — consent, handoffs, and checks
that shaped the volunteer experience as much as any screen.
Revelation · what volunteers told us
Synthesis used highlighter coding on transcripts, affinity
clustering to connect patterns, and 5 Whys on the sharpest issues
to separate symptoms from root causes. Six friction themes held
across the journey:
1. Flexibility comes first. Busy people needed
control over when they volunteered, where they delivered, and
how many boxes they took on. “There's just certain neighborhoods
that I'm not comfortable delivering to alone.”
2. Know before you commit. Volunteers walked in
blind to what the job actually required. “I don't recall being
warned about how heavy the boxes are.”
3. The job needs tools. Heavy boxes, stairs,
towing anxiety, and language barriers made shifts physically and
mentally harder than they had to be — especially for volunteers
over 55.
4. Volunteering felt lonely. “I think the
biggest thing missing is a sense of camaraderie. It's great
knowing it's not just you and that you're part of a group.”
5. There was no ending. Shifts ended with
silence instead of closure or impact.
It was just kind of like you finish and then you drive away.
No reporting back. Thought it was a bit odd, it did feel off.
I was just like, oh, what should I do?
6. Routing broke trust. “The first time when I
put in the link it didn't even show me the stops. And so I'm
like, I'm not going to bother with this.”
Synthesis made the emotional gap impossible to ignore —
volunteers wanted proof they were part of something, not just
a route on a map.
The return · recommendations and how insight traveled
The 18 recommendations mapped each theme to a fix the product and
ops teams could act on:
Availability schedules visible to partner organizations; box
counts volunteers choose themselves (3 to 10, with time warnings);
a four-step explainer carousel and wiki that answer most questions
before commitment; dolly-and-partner prompts at sign-up; shared
community spaces for volunteers; a “done” checkout that triggers
impact stories and recipient thanks; and just-in-time routing with
the stop order curated in advance.
Deliverables were built for mixed audiences: POV statements, a
future-state volunteer flow, service blueprints, and weekly
readouts that mixed video clips, audio, and verbatim quotes so
stakeholders heard volunteers in their own voice — a habit that
comes straight from my film background. Early, frequent sharing
kept founders and ops aligned while the study was still running,
not only at the final readout.
The strongest signal in the data was the one the program had
never designed for: volunteers stay when they can feel the impact
of their work.
When people directly thank you, that makes everything worth
it. It gave me the sense of THIS IS WHY.
What I would carry forward
Prioritize the portfolio, not just the study.
Scoring possible projects on impact versus cost kept a lean
nonprofit focused on the leak that mattered most.
Recruit like the segment is rare — because it is.
Community channels plus a live pre-screen beat a polished screener
alone when participants are specific and unpaid.
Retention is a service, not a screen. Blueprints
and off-the-screen handoffs explained churn that UI-only testing
would have missed — especially the missing ending after the last
drop-off.
Recommendations
What collaborators say about my work.
Leaders across growth, product, strategy, and AI on turning customer
insight into decisions that move teams forward.
“Zack is a highly insightful and tech-savvy UX leader known for his easygoing personality and
collaborative nature.
He helped me understand the Jobs To Be Done (JTBD)
framework when I was tasked with applying this method in a
study. He is particularly knowledgeable about AI tools and
shared his expertise by delivering a presentation on AI use
cases to our team as part of professional development
initiatives. Zack is truly a delight to work with.”
Tree HinesUX and Consumer Insights Researcher
“He’s the embodiment of turning insights into action
and an absolute pleasure to work with. He’s helped unlock insights
that’ve turned into company-wide messaging frameworks, personas,
communication strategies, and more.”
Matthew HelfrichSr. Director, Growth Marketing
“Zack is a UX super star.
His customer-driven insights made an immediate impact on our entire product team.
He pairs strong customer empathy with an ability to pinpoint the
most important customer problems for the team to go solve.”
Meredith HanVP of Product
“Zack isn’t afraid to challenge the status quo.
He’s adept at building trust within an organization, digging into the problems the team is
facing
& surfacing real world, tangible evidence that alter the
direction of a product – for the better!”
Andria JannettiProduct Manager
“Zack is a creative, thoughtful, empathetic, and engaging leader.
Any company would be fortunate to have him on their team, and I
offer my highest recommendation!”
Maggy WardellStrategy & Operations Leader
“Zack isn’t just good, he is shockingly good. Each time he
produced results something about it went above and beyond what
I expected, what was shocking was how consistently he did
that. He constantly demonstrated
a level of experience and expertise that I have only found in the most seasoned
veterans.”
Christopher FryerVP of Product & Brand
“I was always impressed by his great empathy for users, high
quality user reports and dedication for the company mission. He
is always passionate, curious and willing to contribute more!
Zack is truly the best researcher I’ve ever worked with.”
Elaine HeAI Product Manager
Method spotlight
The practice behind the studies.
Case studies are the visible output. These are the operating methods
that make research findable, shareable, and scalable across a whole
organization.
▤
The Knowledge Store
A research repository and ResOps infrastructure that turns
one-off studies into a searchable, tagged single source of truth, wired into product workflows so insight is
found when it's needed,
not buried in a deck.
↗
Democratizing Research
Stakeholder observation, monthly-business-review integration, and
mentorship programs that scale research literacy, so teams can
run solid studies themselves while research keeps the guardrails.
✦
AI-Augmented Research
Synthesis pipelines and automated ethnography, transcription,
clustering, and theme detection, that compress analysis time
while keeping a human in the loop on every interpretation.
Resource 01 · Inclusive design
Design for more ways of thinking.
An accessible field guide for reducing cognitive load, supporting
different sensory needs, and giving people more control over how they
experience a product.
5 min read
8 principles
1 goal: make experiences calmer for more people
Read the 8 principles
Field guide · 8 principles
Neurodiversity-Friendly Design Principles
Simple, practical design rules that make digital experiences
calmer, clearer, and easier for more people to use.
Remove anything that does not help someone move forward.
02
Build predictable patterns
Stay consistent and organized
Put similar information in similar places.
Use size and weight to show what matters most.
Create clear patterns, then apply them consistently.
Give every element a logical, expected place.
03
Support comfortable reading
Optimize readability and typography
Choose highly readable sans-serif typefaces.
Avoid all caps and long passages of italic text.
Use comfortable type sizes, line heights, and spacing.
Maintain strong contrast and a clear text hierarchy.
04
Lower sensory noise
Design with sensory sensitivity in mind
Use a calm, considered color palette.
Avoid flashing, sudden motion, and neon backgrounds.
Keep sound off by default and provide clear controls.
Reduce competing visual and audio signals.
05
Remove ambiguity
Communicate clearly and directly
Prefer literal language over metaphors or sarcasm.
Give each message one clear meaning.
Label controls with specific actions, such as “Send message.”
Avoid jokes or wordplay where clarity is essential.
06
Help people keep their bearings
Simplify and clarify navigation
Keep navigation compact, visible, and predictable.
Label every page and destination clearly.
Show progress during multi-step tasks.
Make the current location and route back easy to find.
07
Give people control
Offer personalization and flexibility
Let people adjust text size and color schemes.
Offer calm and vivid display options where useful.
Allow optional content, motion, or sound to be hidden or paused.
Remember and respect each person’s preferences.
08
Design with, not just for
Emphasize empathy and inclusive practices
Learn how neurodivergent people experience your product.
Include neurodivergent participants in research and testing.
Involve diverse people throughout the design process.
Treat inclusion as a product requirement, not a final check.
Resource 02 · Portfolio craft
Build a case study that earns the interview.
A practical field guide for turning thoughtful UX work into a
concise, evidence-led story hiring teams can understand quickly.
Opens your browser’s print dialog.
5 min read
3 layers of story
1 goal: make the impact clear
Read the six chapters
01
Why case studies matter
Strong work still needs a strong argument.
Case studies are crucial for landing interviews in a competitive market.
Weak studies can actively hurt your chances.
Memorable storytelling connects design decisions to business goals.
A portfolio with focused, credible studies builds confidence in your craft.
02
What compelling studies do
Answer the questions behind the hiring decision.
Frame it. Name the problem, user impact, and business relevance.
Prove it. Emphasize measurable outcomes, not output volume.
Connect it. Link the problem, your decisions, and the outcome.
Edit it. Aim for a focused read of less than five minutes.
03The Minto Pyramid Principle
Lead with the answer. Then earn it.
Structure the story from the most important result down to the
evidence. Open each layer to see what belongs there.
01Start with the answer
Present the single most impressive result first.
Include the timeframe and business impact.
Quantify the result with a key metric.
Connect the result directly to your contribution.
02Support with key arguments
Offer two or three insights that explain the result.
Show clear cause-and-effect relationships.
Include specific observations and supporting metrics.
Turn findings into actionable insights.
03Provide additional clarity
Use evidence to validate the argument and result.
Include the numbers and data that matter.
Explain testing methods and results, including A/B test specifics.
Make your methodical approach easy to follow.
04
Show your thinking. Validate your claims.
Explain the why behind decisions, not only the what.
Highlight the tradeoffs and challenges you navigated.
Back claims with research, analytics, and credible testing results.
Include implementation details and metrics when they add context.
Treat UX writing quality as part of the experience.
05
Avoid the familiar traps.
Don’t bury the point in an overly long process diary.
Don’t force every project into the same generic structure.
Focus on business impact, not a catalog of tools and workshops.
Write for hiring managers and answer their key questions.
Proofread carefully; the details signal how you work.
06The wider portfolio
Choose proof that matches where you’re going.
Show functional UX work. Prioritize apps, platforms, and meaningful product flows
over
static pages.
Early career? Demonstrate industry-style experience and sound decision-making.
More senior? Consider a concise deck centered on the problem, influence, and impact.
At every level: quantify business benefits when you can and maintain a professional
online presence.
The strongest case study is not the one with the most artifacts. It’s
the one that makes your judgment, and its impact, easy to understand.
Mentorship
Research gets stronger when researchers do.
I mentor UX researchers through difficult study decisions,
stakeholder dynamics, and career moves, the messy middle between
knowing the craft and making it matter.
01
Sharpen the work
Frame the decision, challenge the method, and find the
clearest story in the evidence.
02
Build influence
Connect findings to what stakeholders need to understand and
decide next.
03
Navigate what's next
Make career and portfolio choices with a practical,
experienced sounding board.
Looking for a researcher who helps the whole practice grow?
I'm Zack, a researcher who optimizes for adoption.
I've spent the last decade researching AI products, financial tools,
clinical workflows, and hospitality experiences across North
America, Europe, and Asia. The thread connecting them: I don't
consider a study finished until the insight has changed what a team
ships.
That means building the operations around research, repositories,
stakeholder rituals, and now AI-augmented synthesis, so findings
survive long after the report. I work in English with global teams
and lead research in plain language any stakeholder can act on.
Focus: AI / human-in-the-loop, international, FinTech & MedTech
🔒
Several case studies are anonymized per NDA. Confidential details
remain outside this public repository and deployment.
Beyond the desk
The Human Behind the Professional
When I'm not diving into UX research, you'll find me loving the
outdoors, whether I'm rock climbing for fun or recharging in
nature's calm. I'm a proud dog daddy, I'm often fueled by too much
espresso, and I absolutely love a good breakfast burrito. I also
perform in a local improv troupe, indulging my creative side as a
cinephile with a passion for storytelling on and off the stage.