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Overview

Turning a Heavy Data Product into a Trustworthy Consumer Experience

OKTY is a US-based “data bank” that lets people trade their spending and location data for real economic value — cash, rewards, and incentives — instead of having it silently monetised by platforms.

Context

I joined the project as principle Product Designer to work across the consumer app and, later, the vendor platform. Tasked with solving a disruptive introduction to data trading, and an egregiously long and invasive onboarding.

Users were being asked for highly sensitive data (SSN, bank feeds) before they could see any value, in a domain (data trading) they barely understood.

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Role

Defined UX direction and interface refinement:

Product Design on the consumer app; later extended to the vendor platform.
Partnered with clients + legal to balance compliance, feasibility, and experience.
Owned solution framing, flow architecture, interaction patterns, and UX copy across onboarding, first-use, and trade journeys.

Problem

OKTY sat at the intersection of three difficult tensions:

Unfamiliar value proposition

Most users had no mental model for “trading data” or receiving dividends from it. Education was necessary, but lengthy explanation risked bloat and drop-off.

High-friction onboarding

The product front‑loaded ~27 items of sensitive information (identity, bank feeds, financial data) before showing any value. This created anxiety and early attrition.

 New behaviour, no patterns

Data trades are neither a shop, nor a form, nor a survey. Borrowing existing patterns too literally risked misleading expectations; inventing entirely new ones risked cognitive overload.

The existing experience was technically correct and legally compliant, but it didn’t help users understand, trust, or stay.

Project Constraints

Deep KYC & banking Requirements

Sensitive data asks were non‑negotiable — only when and how we asked could change.

A 2 Sided Marketplace

The product needed to be legible to both first-time consumers and brands running campaigns.

Information and Instruction

Compliance rules restricted copy and flows around identity verification and payouts.

Disruptive but trustworthy Identity

Visual identity was already in place; the work had to fit within it rather than replace it.

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Strategy

I anchored the design work around three principles:

Trust through sequencing, not just messaging — Reduce initial commitments and move sensitive asks closer to moments of clear value.
Time-to-value as a first-class metric — Let users experience the core value (data dividends and trades) as early as possible.
Make new behaviours feel grounded — Use familiar interaction patterns (stories, cards, skeuomorphic rewards) while keeping the underlying transaction honest and clear.

Interventions

Progressive, Contextual Onboarding

Split onboarding into four phases mapped to feature areas (account creation, data banking, trade wallet, coupons).

Phase 1: Bare essentials only.

Email/phone, password, basic profile.
Designed so users could drop off and resume later without losing progress.

Phase 2-4: Feature-gated requirements

Banking setup surfaced when users tried to withdraw or enable data dividends.
Additional profile and preference data appeared when starting specific trade types.

Every sensitive ask now came with a clear “because”: we need X so you can do Y (withdraw cash, unlock higher-value trades, etc.).

Proving the Value of Data, Early

Simply telling users they’d be paid for data was not enough to overcome skepticism — and educational content only made onboarding longer.

Injected two small reward moments into onboarding, crediting users’ trade wallets after key steps.
These balances were visible but locked until users completed the banking setup.
Framed this with the internal principle: “If we want users to get paid for data, we should pay them for the data they give us — even during sign-up.”

The rewards were funded from OKTY’s existing monthly data dividend model, so it created behavioural lift without new cost.

This naturally prompted the right questions: “How much is my data worth?” and “What do I need to do to unlock this?”

Designing Data Trades as a Learnable Pattern

In the Marketplace, adopting a “stories-style” media format for browsing multiple trades from a brand quickly, emphasising user value on each slide. Trade previews maintained a pattern that always surfaced:

Campaign subject,
Trade value (cash, discounts, rewards)
Data points requested

Trade Screen

Created a scannable details view balancing brevity and clarity; i.e Key terms, timing, and reward, plus discrete data-point components.
Used skeuomorphic visual cues for coupons/discounts so outcomes felt tangible.
Kept the interaction short by design — avoiding long forms or nested agreements.

Users could learn the trade model quickly and make decisions at low cognitive cost. Brand-wise, this pattern made it easier to reuse existing campaign assets when creating listings.

Vendor Platform Design

Once the consumer flows stabilised, I extended the system into a vendor platform where brands manage listings and rewards:

Designed flows for creating and editing campaigns, setting data requirements, and configuring reward structures.
Aligned the terminology and data structures with the consumer experience to avoid mismatched expectations.
Surfaced analytics around the three core stages of interaction (view, engage, complete) to help brands tune offers over time.

This ensured that what brands thought they were offering and what users believed they were agreeing to stayed tightly in sync.

Outcome

What began as “fix a long onboarding” evolved into defining how users first experience the idea that their data is an asset — and designing a system where that idea is expressed consistently across flows, behaviours, and business mechanics.

I reframed the work around trust, time-to-value, and behavioural fit. By restructuring onboarding into progressive, value-led steps and redesigning data trades to feel familiar and scannable, we reduced early abandonment and increased the ability for higher completion in key setup flows.  Notably also counteracting a key problem in education by taking OKTY’s philosophy — “your data is an asset” — and making it tangible in the product before users even really entered the app.

Impact

Higher completion of initial account creation due to a lighter, resumable first phase.

Stronger qualitative trust signals in testing and stakeholder reviews — users better understood why information was needed and what they got in return.

Reduced early-stage drop-off by letting users explore and see value before heavy data asks.

Clearer, more repeatable patterns for both users and brands, making OKTY’s unfamiliar value proposition feel understandable and actionable.