WeatherXM Mobile App.
Turned WeatherXM’s consumer app into a quality-control layer for its data network, contributing to 667% growth in stations producing sellable-grade data.
Sole principal designer with four developers and no PM. I co-created QoD and built Derecho, the design system behind the redesign.
Key results
- -63% — Tickets in redesigned categories — owners self-served quality problems. (Measured)
- +54% — Perceived utility (UMUX-lite), corroborated by community feedback (Measured)
- 667% — Growth in QoD-passing stations — the sellable share of the network grew roughly fivefold. (Reconstructed)
What I measured
- Stations producing sellable-grade data — 667% (QoD V1 pass rates; baseline reconstructed from ticket categorization + data-team analysis. Definition: stations whose data met the QoD threshold for B2B readiness.)
- Support tickets in redesigned categories — -63% (Support-team ticket categorization. Operational proof that owners could self-serve quality problems.)
- Perceived utility — +54% (UMUX-lite scores before/after)
The bottleneck wasn’t station count — it was B2B-ready station count.
Every bad install added inventory WeatherXM couldn’t sell.
I've been waiting 9 months for this station. And now I can't figure out how to connect it.
My rewards dropped 40% yesterday and I have no idea why. Is something broken?
Contextual inquiry, station installation
Community feedback
Reframing the app around sellable inventory
One commercial question replaced the UI-fix list: how does the app convert more stations into B2B-ready inventory?
“Redesign the app: fix broken flows, add missing features.”
“Turn the consumer app into a quality-control layer that protects the B2B data product and grows revenue.”
Support tickets were the symptom. Unsellable station inventory was the problem.
Weather Research wanted every data point surfaced. I pushed back.
I grouped 11 observations into overview, details, analysis — depth on demand, not overload.
With no PM, I aligned the teams myself.
Make data quality visible to the people who can fix it
QoD became actionable: owners could diagnose problems, understand lost rewards, and fix issues themselves.
Show the reward loss beside each QoD problem, with a direct fix path — a recurring support question became self-service.
Onboarding required buggy manual input
Unexplained reward drops bred conspiracy theories
No signal when a station malfunctioned
The same support questions, hundreds of times
Guided onboarding, manual entry automated away
Every reward change explained in plain language
QoD flags failures instantly, with a fix path
Self-service fixes cut repeat tickets 63%
Company-growth impact, with support as a proof point
QoD-passing stations increased 667% on a reconstructed baseline. A 63% ticket reduction shows the same mechanism cut support workload.
What worked · what I'd do differently
What worked
Moving the story from cost reduction to value creation.
Connecting station health to owner incentives made data quality actionable.
What I'd do differently
Push harder for instrumentation earlier.
Instrument QoD and onboarding per station from day one — impact shouldn’t rest on reconstructed baselines.
FAQ
What does the 667% increase in sellable-grade stations (QoD-passing) actually measure?
The stations whose data met the QoD threshold for B2B readiness and reward eligibility. The network grew about 50% (5,000 to 7,500+), so the sellable share grew roughly fivefold. Source: QoD V1 pass rates, baseline reconstructed from ticket categorization (QoD V1 didn't exist before).
How did you measure the 63% reduction in support tickets?
The support team categorized tickets by type; I redesigned the top-category flows and compared monthly volume. The 63% reduction is across redesigned categories, not all tickets. Cost model: 63% × 12,000 estimated annual tickets × $15/ticket (Forrester benchmark) = $113,400/year avoided.
What's the business model connection between station quality and company success?
One chain: healthy stations, quality data, B2B-ready product, revenue. Break any link and the model fails while the company keeps paying rewards on worthless data. Installation guidance and QoD indicators protected that asset. Technically B2C, the app is infrastructure for the B2B revenue model.