Outricher / research / brighty-app / ideas for the next move

Where to dig next — ideas we want to help with.

This isn't a sales pitch — it's a map of directions: what we've already assembled for Brighty, and which other angles we see, each framed as a hypothesis with a data check. We tried to be useful proactively; some of it will land, some will miss. We'd love your feedback: tell us what's valuable and what isn't — and where to look next. On a few of these ideas we're missing context from inside Brighty (we're upfront about that at the end), and there the best next step is a short conversation.

11
datasets already assembled and ready to use
4
new directions for your review
8,700+
profiles in the ready datasets — people, not rows
0
invented contacts · where there's no data, we say so honestly

prepared 2026-06-28 · MEASURED · Outricher data · draft for discussion

01What's already ready — open it and get to work

These aren't plans — they're assembled, enriched and scored datasets, each with an analysis report right beside it. Open them, check them, tell us what's useful.

DatasetVolumeWhat's inside
Full team archive60 peoplecurrent + departed, with tenures, roles and "where they are now"
P1 · crypto-card competitors929 in sampleemployees of Crypto.com / Nexo / Bitstamp and others — a hot B2C audience
P2 · neobanks971 in sampleemployees of Revolut / N26 / Monzo — early money-app adopters
P3 · crypto income in the EU1,052 in sampleemployees of crypto/Web3 firms — the largest hot audience
P5 · diaspora · P6 · relocators600 + 934migration segments — the most nuanced, differentiating signal
Hiring: AML/MLRO · CISO · CFO · UX · CS822·216·170·302·587candidates for 5 hard-to-fill roles, two tiers, named and scored
How to read this. Each dataset lives inside its own report — with the analysis, the method and a way to request it. Start with the research home page: reports #1–6 + every ready dataset. If you need a segment in a different cut (your filters, your geo, different scoring), we can rebuild it quickly.

02Five directions we see next

Each is a hypothesis about value for Brighty. Next to each we honestly flag the readiness level: proven — the method is already demonstrated on your data; strong hypothesis — the logic is solid, volume to be confirmed on a trial sample. Tell us which ones resonate — that's where we'll start.

DIRECTION 1 · GROWTH OWNER

Head of Growth candidates — dataset ready

ready · assembled

109 senior growth leaders with contacts — a dataset for the biggest gap from the competitor research, already built

Hypothesis → assembledIn the competitor research we measured it: marketing/growth at Brighty is 1 role, even though acquiring customers is priority #1. The logical first step is to hire a growth owner. We didn't stop at the observation — we built the dataset: current senior growth leaders (Head of Growth / VP Growth / CMO / Head of Marketing) at nine relevant fintechs, in your hiring geo. After cleaning out false matches — 109 people with contacts, 74% with a work email. The ready file and analysis are in the Head of Growth dataset.
Why it's usefulSame logic as the MLRO/CISO/CFO datasets — just for the growth role. 38 of 109 are from Revolut, the largest block, on a warm path: Brighty's engineering core already came from Revolut, so shared background lowers the outreach barrier. 87 candidates at the "can lead growth right away" level. A full dataset with contacts, scoring and two tiers — just like the other ICPs.
What we need from youConfirm the role frame: pure performance/growth, brand marketing, or a mix; whether crypto-native experience is required; seniority (Head vs VP vs C-level). With that we'll narrow to the exact target and add targeted contact enrichment.
DIRECTION 2 · CUSTOMER ACQUISITION (B2B)

Which companies could become Brighty Business customers

measured

recently funded companies that would logically need a multi-currency account — a test of the product angle

Measured now250 EU companies that recently raised funding and could use Brighty Business · by stage (Seed 123, Series A 45…) · by country (UK 82, FR 32, DE 25…) · 44 crypto-native + 31 payments · median round $3.5M. An honest funnel: from the "fat" list of ~500 we removed giants refinancing debt (Capgemini/AXA/UBS) — leaving only those who actually need the product.
Why it's usefulA first pass toward sales: which companies fit, why they have a need, and how to reach them (a "congrats on the round" hook, the cross-border payroll pain). It can be refreshed to catch new rounds.
What we need from youMainly — is the B2B angle even interesting given your current focus (or is the priority retail customers?). If yes — narrow the frame (stage, countries, crypto) + add live monitoring of fresh rounds.
Open analysis
DIRECTION 3 · EARLY MARKET SIGNAL

Regulatory-hiring radar

proven

whoever hires an MLRO / compliance lead is about to launch a regulated crypto product

HypothesisWhen a company hires an MLRO or a head of compliance, it's preparing to launch a regulated crypto product. That hire is an early signal you can read three ways: a competitor entering your market (a warning), a prospective customer building crypto who needs rails, or a possible partner creating licensed infrastructure.
Why it's usefulBrighty sees market moves first — before the public announcements. We've already applied the same role-based search method in the AML/MLRO candidate dataset, so the detection is proven; here we simply watch how it shifts over time.
Live reading nowWe counted competitors' compliance openings by half-year: Revolut — 871 in the last 6 months (out of 1,258 for the year — meaning hiring is accelerating: 69% of the annual volume fell in the most recent half). This reads as "Revolut is actively opening up its regulatory perimeter right now" — preparing for new licenses/markets. For comparison: Crypto.com 28, N26 29, Bitpanda 27 over the same 6 months — steadily low. When a spike like that comes from a different player, that's precisely the early signal that it's entering your market.
What we need from youTell us what matters most first — tracking competitors, finding B2B customers, or partners. That determines how to set the filters and whose spikes to watch.
DIRECTION 4 · COMPETITIVE INTELLIGENCE

Competitor war map — already done

proven · ready

size, hiring and churn across 8 competitors — where Brighty lags, where the market is looking, who to poach

Hypothesis → confirmedA competitor's hiring is its public roadmap. We assumed you can read market strategy from team composition and job-posting dynamics — and we checked: Revolut holds 2,396 open roles and is actively staffing compliance and marketing; Ramp lost ~half its headcount and isn't hiring. And at Brighty itself, marketing/growth is 1 role, even though customer acquisition is priority #1.
Why it's usefulThis is already a standalone competitor research — you can open and read it today. It surfaces the structural gap (no growth owner), warm hiring channels, and a poaching pool at weakened competitors.
What's nextFor your specific task the competitor set can be expanded, and the dynamics can be put on a regular refresh (see direction 5).
DIRECTION 5 · REGULAR REFRESH

A live signal feed instead of one-off files

strong hypothesis

not one list, but a stream of changes — new rounds, new competitor hires, market moves

HypothesisAny list goes stale within a couple of months — the value of data is in its freshness and in the delta. If directions 1–4 become a regular digest (monthly or weekly), Brighty gets a live picture instead of a snapshot: newly funded buyers, new regulatory hires at competitors, changes across teams.
Why it's usefulGTM and hiring run on fresh signals, not on an aging file. It turns a one-off study into a standing tool.
What we need from youUnderstand which signals are genuinely useful in the team's routine, and at what cadence — so the feed is about substance, not volume.

03Where we need your input

Honest about the limits: from external data we see a lot, but not everything. Here are the questions whose answers will make the next datasets sharper — and where a short conversation beats any of our guesses.

Who's your ideal B2B customer?

Size, stage, markets, industry. We can find "similar companies," but only you know the criteria for a "good customer."

What counts as a "hot" lead?

We see who works where and in what role. Intent (is this person ready now) we infer indirectly — your experience from real deals will calibrate the scoring.

Which markets are in focus for 6–12 months?

Wherever you're expanding is where we'll point the audience and hiring search. It sharply narrows and cheapens the datasets.

What we CAN'T do — and say so upfront

We can't profile your retail users (that's not a B2B graph). Contacts that don't exist, we don't invent — we return an empty field. If something is important but unavailable in the data, we'll discuss how to get it another way.

04What we propose as the next step

1
Look at what's ready — 12 datasets + research
Open the home page, the competitor research and the new Head of Growth dataset. Tell us what's valuable.
2
Give feedback — what lands, what misses
We need to understand which segments and angles are genuinely useful to your team.
3
A short conversation — about the ideal customer profile
15–20 minutes of your context = noticeably sharper datasets next time.
4
Pick 1–2 directions — and build them for you
With a trial sample and real volume, before scaling anything.

We did this proactively to show how we can be useful — and we'll be glad if some of it helps already now. Tell us what you think: hi@outricher.com or on Telegram @outricher.

Want a report like this for your company?

Tell us your target company or ICP and we'll deliver the dataset + a short analysis in the same format.

Request your report — hi@outricher.com ↗

Outricher · professional graph of 1.17B profiles · @outricher · hi@outricher.com
MEASURED · Outricher data · draft of ideas for Brighty · 2026-06-28