Tokenized Asset Platform (NDA)  |  Coleman Advisory  |  2022

The Interface Was Clear.
The Users Were Still Afraid.

Research lead and strategic advisor on a 2022 engagement with a tokenized asset platform navigating the intersection of TradFi compliance and DeFi mechanics. The audit identified 17 distinct friction points, the majority tied to transaction state legibility, and produced an executive roadmap that treated regulatory communication and UX as a unified problem.

Platform Tokenized Asset Platform (NDA)
Engagement 2022
My Role Research Lead and Strategic Advisor
Organization Coleman Advisory

Helping innovators move fast without breaking the things that matter most requires knowing which things matter most before moving.

A product at the edge
of two financial worlds

The client built a tokenized asset platform that let users invest in real-world assets through blockchain-based instruments, under a compliant and regulated framework. The pitch was genuine: DeFi-level accessibility with the structural rigor of traditional finance. What nobody had tested was whether users could tell which world they were in at any given moment.

Tokenized asset platforms occupy a specific and strange middle space. They carry the design conventions of traditional finance: clean account dashboards, familiar transaction flows, recognizable compliance disclosures. But the mechanics are blockchain-native, which means settlement is asynchronous, states change in layers the interface does not expose, and the timeline for a "completed" transaction has no equivalent in anything a typical user has encountered before.

In a conventional banking app, that ambiguity is minor. Users have cognitive frameworks for navigating it. In a platform where real money moves into positions that do not carry the familiar backstop of traditional financial infrastructure, the same ambiguity becomes a different category of problem entirely.

The Brief

Audit the onboarding experience and full transaction flow. Identify the friction points threatening user retention and document failure modes before launch.

The engagement was scoped as a research and advisory project, with deliverables including a friction audit and an executive roadmap prioritizing findings by combined UX and regulatory risk.

Mapping the experience against
the mental model users actually had

The research started with a deliberate reframe. This was not primarily a usability problem. The interface was technically well-built: buttons did what they were supposed to do, navigation was clear, nothing was visually broken. A usability-first audit would have generated a list of minor UI improvements and left the underlying problem completely intact.

The audit focused instead on the gap between what the interface communicated and what users interpreted. That distinction shaped both the methods and the framing of findings. Fixing the wrong thing, in this context, would have made the problem invisible rather than solved.

01
Transaction Flow Audit
End-to-end walkthrough of every state a user encounters from initial deposit through position management and withdrawal, documenting what each state communicated and what a user without blockchain experience would plausibly interpret.
02
Mental Model Mapping
Structured research surfacing the prior frameworks users brought from traditional financial products and identifying the specific points where those frameworks would fail to map onto how this product actually worked.
03
Onboarding Journey Analysis
Step-by-step analysis of the onboarding flow with attention to sequencing, disclosure placement, and cognitive load at each stage, assessed against what users needed to understand before making their first transaction.
04
Regulatory Communication Review
Assessment of disclosure language and compliance messaging against user comprehension, with specific attention to where regulatory boilerplate introduced ambiguity rather than reducing it.

Pending didn't mean pending
to the people using it

17
Friction points identified
11
Transaction state failures
1
Central finding that reframed the rest
Findings — Friction Distribution
17 Friction Points. 65% in One Category.
The audit identified 17 discrete friction points across the onboarding and transaction flow. The concentration was itself a finding — not distributed risk, but a single systemic failure with a clear name.
Transaction State Legibility
11
Pending states, settlement windows, failed vs. in-progress states, balance display during settlement, network errors indistinguishable from rejections
11 of 17  ·  65%
Onboarding Flow
4
Wallet and account creation conflated; asset explainer sequenced after wallet creation; TradFi mental model assumed at first deposit
4 of 17  ·  24%
Regulatory Communication
2
Generic boilerplate not calibrated to tokenized assets; regulatory status of tokenized positions not distinguished from conventional securities
2 of 17  ·  12%
17
friction points with severity ratings and ownership classification
The interface was not broken. The mental model users arrived with was built for a different product category entirely, and nothing in the flow told them otherwise.

Seventeen distinct friction points emerged from the audit. The distribution was striking. Eleven of the seventeen were concentrated in a single area: transaction state legibility. The interface was technically accurate at every step. The problem was that accuracy and comprehensibility are not the same thing.

The central finding: users consistently interpreted pending transaction states as evidence of asset loss. A transaction in settlement, processing normally and on schedule, looked to users like a failed transaction. Or one that had simply disappeared. The interface was showing exactly what was happening. Users understood something different.

Core Finding

The interface was not broken. The mental model users arrived with was built for a different product category entirely, and nothing in the flow told them otherwise.

This failure mode gets worse as the stakes increase. A user who cannot tell if their grocery order went through hits refresh. A user who cannot tell if their asset position is processing or lost does something more costly: they abandon the transaction, contact support, or do not come back. The cost of the same information gap scales with what the user believes is at risk.

The same finding costs more
in some contexts than others

In most products, a confusing loading state is a minor annoyance. Users have mental frameworks for navigating uncertainty during a transaction. In a tokenized asset platform, the same ambiguity activates a different category of concern entirely.

Traditional financial infrastructure has spent decades building cognitive safety nets that users have absorbed without realizing it. FDIC coverage, monthly statements, customer service lines, the ability to walk into a branch and speak to someone. None of these protect a user against a confusing interface in any direct sense. What they provide is a backdrop of institutional accountability that quietly mutes anxiety during moments of uncertainty. Users do not think "I am protected." They feel protected, without thinking about it at all.

That infrastructure does not exist in DeFi-native products, and users know it, even if they cannot articulate it. A tokenized asset platform may carry legitimate regulatory standing, but users bring their associations from the broader DeFi landscape: irreversible transactions, no customer recourse, self-custody risk, the familiar stories about assets lost to a mistyped address or a wallet that cannot be recovered. When a pending state appears and the interface offers no context for how long, why, or what it means, the worst interpretation fills the space immediately.

The Gap

The finding was not novel as a UX observation. Mental model mismatches between product mechanics and user expectations are common. What made this finding consequential was the context it landed in.

This was a platform where that specific gap, users misreading a normal pending state as asset loss, could translate directly into permanent user attrition, support volume the team was not staffed for, and reputational risk at exactly the moment a new product most needs positive word of mouth.

What the audit
surfaced

The 17 friction points broke across three categories. The concentration in transaction state legibility was not a random distribution. It reflected a product that had invested heavily in building a technically sound system and had not yet invested in making that system legible to users who arrived without blockchain-native experience.

Transaction State Legibility
11 of 17
Pending deposit states used TradFi language ("processing") without mapping to blockchain settlement stages
Settlement window duration not communicated at transaction initiation
"Processing" and "pending" used interchangeably for distinct system states
No differentiation between blockchain confirmation pending and platform-level processing
Failed and in-progress transaction interfaces near-identical visually
No proactive notification on extended settlement beyond the expected window
Position balance during settlement showed pre-transaction value without contextual explanation
Transaction history compressed state data, making past pending states unverifiable retroactively
Network delay errors indistinguishable from rejected transaction errors
Session re-entry mid-flow provided no state summary
Withdrawal initiation did not surface the position lock during the processing window
Onboarding Flow
4 of 17
Wallet creation and account creation presented as a single flow without distinguishing their different functions
Tokenized asset explainer sequenced after wallet creation, when user comprehension needed it most
First deposit flow assumed a TradFi mental model without bridging to blockchain settlement expectations
Progressive disclosure not applied to regulatory consent, creating friction and likely incomplete comprehension
Regulatory Communication
2 of 17
Risk disclosure language used regulatory boilerplate not calibrated to tokenized asset-specific risk profiles
Regulatory status of tokenized positions not clearly distinguished from conventional securities in interface copy

Two problems that
turned out to be one

The executive deliverable was a prioritized roadmap covering both product changes and regulatory sequencing. The framing was deliberate. It was a departure from how the leadership team had been thinking about the work.

Most product teams in this space treat UX design and regulatory compliance as separate workstreams. Different owners, different timelines, different definitions of what "done" looks like. The audit produced evidence that they could not be separated here. The specific communication gaps making pending states feel like asset loss were the same gaps that would create regulatory exposure if users misunderstood the nature of their positions. Fixing the interface without fixing the disclosure language would paper over the problem. Fixing the disclosures without improving the interface would bury the solution in legal text nobody reads.

The roadmap gave the leadership team a sequenced plan: 17 friction points ordered by combined UX and regulatory risk, with clear ownership and decision points across both tracks. The single most important output of the engagement was the reframe itself. This was not a UX problem with a compliance annex. It was a user trust problem that happened to have both UX and regulatory dimensions, and it needed to be solved as one thing.

The Reframe — Core Finding
Two Tracks. One Problem.
UX design and regulatory compliance had been treated as separate workstreams. The research showed they were the same problem — and had to be solved as one thing.
UX Track
Communication gaps made pending states feel like asset loss
Ambiguous state labels mapped onto worst-case interpretations
Balance display during settlement read as balance gone
No contextual guidance at the moment of confusion
Visual design could not distinguish recoverable from terminal states
Regulatory Track
The same gaps created regulatory exposure if users misunderstood their positions
Generic risk disclosures not calibrated to tokenized asset risk profile
Regulatory status of positions undefined at point of decision
Consent architecture did not match the complexity of what users were agreeing to
Misunderstood positions = misunderstood exposure
Where they converge
A User Trust Problem with Both UX and Regulatory Dimensions
The deliverable reframed this as a single problem requiring a single roadmap — sequencing both tracks together by combined UX and regulatory risk, with explicit decision points and dependencies across both.
Deliverables

Full friction audit documenting 17 friction points with severity ratings and primary ownership (product vs. compliance vs. content).

Executive roadmap sequencing the 17 findings by combined UX and regulatory risk, with decision points and dependencies surfaced explicitly across both tracks.

The methodology choices
worth revisiting

Parallel analysis
Run the onboarding and transaction analyses simultaneously from day one

The onboarding finding arrived later in the process than it should have. I prioritized the transaction flow because that is where the retention signals pointed, and it was the right call for urgency. But the onboarding sequencing failures had downstream effects on how users interpreted everything that came after. Users who arrived at a transaction without the right mental model were more likely to read a pending state as failure than users who had been properly oriented. Running both analyses in parallel and sharing findings between them earlier would have surfaced that connection sooner.

Depth on disclosure
Go deeper on the regulatory communication finding

Two points in the friction map does not reflect how important the regulatory communication finding actually was to the overall problem. The boilerplate disclosure issue was flagged clearly in the roadmap, but a more thorough review, including comprehension testing of the disclosure language specifically, would have strengthened the recommendation considerably. That was a resource constraint more than a judgment call, but it is worth naming. The finding deserved more evidentiary support than it got.

Research in high-stakes financial contexts is different not because the methods change but because the cost of a wrong interpretation is higher and faster. The core challenge here was a familiar one: users arrive with mental models built for a different product, and the interface has to bridge that gap or they leave. Every research engagement I have worked on involves some version of that problem.

What made this one distinct was that "they leave" meant something more consequential than a bounced session. On a platform where user trust is the actual moat (not the technology, not the compliance infrastructure, not the asset selection), a UX finding is also a business continuity finding. The two are the same thing, even if the teams responsible for each one are not used to thinking that way.

That reframe was the real deliverable. The roadmap documented it. But getting a leadership team to see a user trust problem as a unified product and regulatory challenge, rather than two separate workstreams that occasionally overlap, is the harder and more durable outcome.