NPS and CSAT are the standing pulse of how customers feel — one measuring loyalty, the other satisfaction. Tracked consistently, they turn sentiment into a number with drivers behind it.

NPSTracked CSATPer touch DRIVERSAnalysed TRENDWatched

D01.1 · NET PROMOTER

The loyalty question.

NPS asks the one question — how likely are you to recommend WCN — and tracks the promoter-minus-detractor score over time. It’s a blunt but durable loyalty signal.

D01.2 · SATISFACTION

The moment question.

CSAT measures satisfaction with specific interactions — support, onboarding, a release. Where NPS is the relationship, CSAT is the individual moment.

D01.3 · DRIVERS

Why the score moved.

A follow-up asks why, and responses are themed. The score tells you the temperature; the drivers tell you what to fix — which is the part that matters.

D01.4 · THE TREND

Direction over headline.

Both metrics are watched as trends against benchmarks, not as one-off headlines. A moving score with known drivers is a roadmap; a static number is a vanity stat.

Surveys capture answers to questions you thought to ask. Social listening captures what people say when no one’s asking — the unfiltered, real-time voice of the market about WCN.

SOURCESSocial · reviews THEMESExtracted SENTIMENTScored ALERTSOn spikes

D02.1 · SOURCES

Where the talk is.

Listening spans the platforms where crypto communities actually gather — plus reviews and forums. Coverage follows the audience, not just the easy-to-scrape channels.

D02.2 · THEME EXTRACTION

Patterns, not just posts.

Mentions are grouped into themes — recurring praise, complaints, confusion. Themes turn an unreadable firehose into a short list of what the market is actually saying.

D02.3 · SENTIMENT

Tone, at scale.

Each theme carries a sentiment read, so the brand sees not just what’s discussed but how people feel about it. This feeds the sentiment metric in the health cluster.

D02.4 · SPIKE ALERTS

Catch it early.

Sudden spikes — a viral complaint, an impersonation scam — trigger alerts so the brand and security teams respond fast. Listening is an early-warning system, not just a report.

Metrics tell you what changed; interviews tell you why, in a human voice. Regular one-to-one conversations with users surface the motivations and frictions no survey scale can capture.

CADENCEOngoing FORMAT1:1 SYNTHESISThemes OUTInsights

D03.1 · CADENCE

A steady drip.

A few interviews every month beats a big batch once a year. A steady cadence keeps the team continuously in touch with real users, not periodically surprised by them.

D03.2 · FORMAT

Open, and quiet.

Sessions are semi-structured — a few guiding questions, then listening. The goal is to hear the user’s framing, not to lead them to the answer the team expected.

D03.3 · SYNTHESIS

From talk to themes.

Notes are synthesised into recurring themes across interviews. One person’s opinion is an anecdote; the same point from five users is a finding.

D03.4 · INSIGHTS

Quotes that stick.

Output is a short set of insights, each backed by user quotes. A vivid quote moves a roadmap discussion in a way a chart rarely does.

Support tickets are the largest, most honest dataset of customer pain the company has — and usually the least mined for brand signal. This turns that backlog into themes worth acting on.

SOURCETickets MININGThemes TOPIssues SIGNALBrand

D04.1 · THE SOURCE

Honest, and huge.

Every ticket is a customer telling you something is wrong, in their own words and at volume. It’s the cheapest, most candid voice-of-customer data available — already paid for.

D04.2 · THEME MINING

Group the noise.

Tickets are categorised and clustered into themes — recurring confusions, bugs, requests. Volume per theme reveals what matters most to the most people.

D04.3 · TOP ISSUES

The recurring few.

A short list of top issues is surfaced each cycle, with volume and trend. The point is focus — the handful of themes driving the most contacts.

D04.4 · BRAND SIGNAL

Pain becomes insight.

Themes feed product, support and brand — confusion about messaging is a brand problem as much as a support one. The loop closes when a theme drives a fix.

Every decision to adopt WCN — or a competitor — carries a reason. Win/loss analysis gathers those reasons systematically, so the brand learns what tips the choice and what loses it.

WONWhy LOSTWhy PATTERNSFound FEEDSBrand · product

D05.1 · WHY WON

What tipped it.

For wins, the analysis captures what actually decided it — a feature, the brand’s trust, a relationship. Knowing your real strengths lets you lean into them.

D05.2 · WHY LOST

The honest no.

Losses are mined just as carefully — price, missing capability, a competitor’s brand. Losses are where the most uncomfortable, useful truth lives.

D05.3 · PATTERNS

One loss vs a pattern.

Individual deals are anecdotes; patterns across many are strategy. Recurring loss reasons point to real gaps — in product, positioning or perception.

D05.4 · FEEDING BACK

From reason to roadmap.

Findings route to product (capability gaps), brand (perception gaps) and sales (messaging). Win/loss is only worth doing if it changes what those teams do next.