I'd rather be
in the field.
Mid-session, headphones on — listening for the patterns no one says out loud.
The best research is the kind product partners can actually ship.
Five years deep in enterprise CCaaS — turning the quiet patterns of how people actually work into product strategy that ships the same week.
Data is the whisper of a behavior. Strategy is the world we build to house it. Research worth doing is research someone ships.
— Signed, the researcher.
What this means in practice
Research is not a phase that happens before strategy. It is the discipline that keeps strategy honest.
01 — Behavior first
Opinions are cheap. Observed behavior — what people actually do when no one is asking them to explain — is the only ground worth building on.
02 — Signal, not noise
More data does not make better decisions. Better framing does. I label every finding by its evidence type and confidence level so teams know what to weight.
03 — Ship the learning
A report that no one acts on is an artifact, not research. My work is measured by the decisions it enables: requirements written, roadmaps shifted, products released.
04 — Loop, don't land
Shipped work is the next study's input. The best research practice is one that makes the next cycle sharper, faster, and more grounded.
The Operating Model
Twenty-plus product pods, one researcher. That arithmetic only works if the method holds: every observation labeled by what kind of evidence it is, confidence scored separately by organizational level, and findings routed to the decision they actually belong to instead of pooled into a single report nobody can act on.
A continuous loop — define, execute, build — so shipped work feeds the next cycle.
Tooling is incidental: Plaud captures contextual inquiry with permission; AI assists synthesis, drafting, and prototyping. The judgment isn't delegated.
Most research loses its authority the moment a theme gets promoted to a fact on the strength of being compelling.
01 — Label the evidence type
Observed directly, stated by a participant, requested as an enhancement, proposed as a solution, or an open question with nothing behind it yet. Most of what a session produces sits in the bottom three. Collapsing them is how research quietly becomes a feature-request intake.
02 — Score confidence by level
A strong frontline finding is not an enterprise conclusion. Scoring the two separately keeps a well-evidenced local pattern from being read as organizational truth.
03 — Route before you recommend
Value realization first. Nothing becomes net-new product investment until existing capability, configuration, workflow, and enablement have been ruled out. Treating every issue as a product gap delays value already paid for; treating every issue as configuration buries real opportunity.
04 — Publish the boundary
Every fast readout opens with what it does not provide: no final findings, no validated requirements, no prioritization, no root-cause conclusions, no roadmap. Speed is a feature. Unearned confidence is a liability.
Where the work happens
Field research is a relationship business before it is a method business.
My work has taken me into BPO operations for a global consumer-electronics brand in India and the Dominican Republic, workforce-management research with a same-day delivery marketplace, and multi-day onsite studies with a national automotive service network. I've also run research and evangelized value realization at Sprinklr CX Connect events in New York and Chicago — working directly with account teams and customers. One of those conversations became the seed for a social-care program with a major beauty retailer.
01 — Build genuine trust
I'm not in a sales role, so I can be objective. That neutrality is an asset — participants and account teams both relax when they know I'm there to learn, not to sell.
02 — Set expectations early
Clear objectives, workflow, and logistics before wheels up. Everyone knows why we're there, what we'll capture, and how it will be used.
03 — Record with permission
Sessions are captured with Teams or Plaud — always with explicit participant permission. Images and video follow the same rule. Nothing ships without consent.
04 — Strip the PII
Final outputs are anonymized and scrubbed. The insight survives; the identifying details don't.
05 — Deliver fast insight
Rapid readouts while the context is still warm. Daily onsite guidance closes learning-objective gaps before the team leaves the building.
06 — Create value, not artifacts
Every onsite is judged by whether it moves a decision. The goal is impact — a sharper roadmap, a rescued launch, or a team that finally agrees on the problem.
Open to in-house roles now — full-time, contract, or advisory.
Senior UX Researcher moving toward Product Strategy. I own the path from ambiguity to shipped scope.
I focus on the hard part of product work — not just what users say, but what that means for what gets built, when, and how confidently. Research leader turning ambiguity into shipped outcomes — owning discovery, GA readiness, and roadmap execution across enterprise service platforms.
For five years at Sprinklr, I've worked across enterprise Service platforms: Voice/CCaaS, Workforce Management, Supervisor tooling, Social Care, and AI Copilot. My work isn't limited to research reports. I own discovery through to delivery — translating findings into prioritized Jira, GA readiness sign-offs, MVP frameworks, and release-aligned outcomes.
I'm most effective where the stakes are real: enterprise customers who can't afford a bad launch, product teams navigating scope tradeoffs, and cross-functional partners who need clear signal to make fast decisions.
Outside of work — avid swimmer, outdoors person, and deep lover of fantasy and adventure stories. The kind where the world-building is so thorough you trust every decision inside it. That's the standard I bring to product research.
Based
Austin, TX
Currently
Sr. UX Researcher → Product Strategy Partner, Sprinklr
Open to
In-house, contract, or advisory — available now
The customer asked which mobile features they were missing. Four store visits later, the question had changed.
A two-day onsite across four locations, an overnight directional debrief that named its own limits, and a two-track routing model that separates what existing capability can already solve from what is genuinely a product gap.
Multi-method generative research turned a fuzzy mobile ambition into a See → Decide → Act framework that became the product architecture and a ready engineering backlog.
Three deliberately sequenced methods turned a complex telephony product into a tiered GA decision — informed confidence, not optimistic shipping.
An SSO certificate expired. A carrier dropped calls. Tens of thousands of customer interactions failed. I ran the incident as research and turned the response into AI Copilot requirements.
Short, specific, opinionated. What I learned while doing the job — not after.