CX & Product Designer · Customer Journey Mapping · User Research · Design Systems · B2B SaaS · Delhi, India
i design customer journeys that cut real pain points, dashboards that don't make people cry, and design systems that survive sprints. user-centered work tied to conversion and business impact. 3+ yrs · Delhi · open to fun briefs ✿
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pairs that ship · serif × sans × mono × hand-drawn · with a real type ramp behind every dashboard.
a complimentary 20-min session where i'll review your UX in the kindest possible way and leave you with a roadmap. your competitors hope you scroll past this.
grab a free slot calendly.com/siya-cxdesigner/connect ↗A self-initiated product-and-UX concept, plus design work for a live enterprise AI product.
Case study · PDF · 35 pages
Amazon remembers products. It doesn't remember decisions.
Amazon Decision Hub is a self-initiated product and UX case study that rethinks how shopping apps handle saved products. A wishlist today remembers the product but forgets the decision: why you saved it, what you compared, and how confident you were. Days later, shoppers cannot recall why they shortlisted one option over another, so they restart research or abandon the cart. This project designs a decision-memory layer that captures shopping intent at the moment of saving, so people can resume a purchase decision later instead of starting over.
Grounded in qualitative user research, the work shifts the experience from product recall to decision recall. A Decision Snapshot surfaces goals, budget, confidence and comparison history first; an optional, AI-assisted Save Decision infers context with minimal effort; and every AI-inferred field stays editable, so the user stays in control. It runs end to end: problem framing, competitive analysis, user flows, low-fidelity wireframes, a design system and an interactive prototype, plus the success metrics that would prove decision resumption, context recall and decision confidence.
Live product · spiderbrain.ai
Making a deterministic AI memory layer understandable and trustworthy.
Spiderbrain is an enterprise AI product from Perform Digital: a deterministic memory and context layer that gives agents reproducible answers, blast-radius analysis, and governed, versioned knowledge instead of guesswork. The hard part is not the technology, it is comprehension. The value lives in abstract ideas (a context layer, a live dependency map, decision memory that survives the session), and enterprise buyers do not adopt what they cannot picture or trust.
The CX work focuses on making that abstraction legible: shaping the narrative and information architecture so each layer builds on the one beneath it, framing the shift from "no shared brain" to "one shared brain" in plain business terms, and giving memory, dependencies and blast-radius risk a consistent visual language. The throughline is trust: show impact before it ships, and make every governed answer feel understandable rather than magical.
designing how an AI agent guides visitors through a warm, low-friction journey that captures leads conversationally instead of a cold contact form.
AI tools ship generic layouts in seconds, and good models can get specific, but only when they are fed the right product context. That context is the actual job: your brand identity, the real pain points in the customer journey, the branches a flow genuinely needs, the emotional highs and lows users hit. I bring the user research, discovery interviews and design-thinking judgement that turn a generic AI draft into a customer experience built for your business and your conversion goals. AI is a faster pencil. The thinking is still mine.
Personalization is not a first name dropped into an email. It is designing an experience that adapts to intent and segment: a returning enterprise buyer sees a different user journey than a first-time trial user, a power user wants shortcuts, a hesitant one needs a bit more hand-holding. I map those segments through user research, design the variant states, and define the rules behind them. Done well, a personalized journey lifts activation, retention and conversion rate, because the product finally feels built for each person.
Most revenue leaks between screens, not on them: a confusing handoff, a dead end after signup, an empty state with no next step. With customer journey mapping I chart the end-to-end experience, mark every friction point and emotional dip, then redesign the moments that gate growth: onboarding, the aha-moment, upgrade and renewal. Fewer pain points means higher conversion, lower support load and a measurable design impact you can take to your board.
It is a loop, not a one-way handoff. Discovery: I learn your business, users and goals. Need & gap analysis: where the current experience fails real people. Blueprint: information architecture, user flows, journey maps and wireframes. Demo: an interactive prototype tested with real users and stakeholders. Refine: act on the feedback. Then the cycle repeats as your product and market move, so the experience keeps improving instead of going stale.