Outricher / research / brighty-app · pull P1

Pull P1: refugees from competitor crypto cards.

This is the first live pull built on a persona from consulting report No.3. We took the P1 persona — someone who already carries a competitor's crypto card — found every such person in Brighty's operating region, drew a balanced sample, enriched it with a paid API, scored it, split it into segments, and packaged it into a downloadable dataset. Below: how many we found in total, how we built the sample, what we enriched with, how the scoring works, which segments came out, and where to get all the data.

5,353

total found in Brighty's region

929

in the sample (enriched, scored)

294

hot A+/A leads

461

profiles enriched via API

delivery-grade · prepared 2026-06-28 · MEASURED · Outricher data · P1 persona from report No.3

01Who we looked for, and why

P1 is Brighty's warmest lead: you don't have to convince them that a crypto card makes sense at all. They already work inside the category — at a competitor.

PERSONA P1 · FAMILY I (COMPETITOR DISPLACEMENT)

Refugee from a competitor crypto card

HOT

current employee of a competing crypto-card platform, resident of Brighty's operating region

Why a customerThese people already spend crypto with a card and put up with a competitor's friction: staking a token to earn cashback, an over-complicated ecosystem, the "borrow against collateral" model. Fee-free Mastercard + EUR/USD/GBP IBAN + earn without a token is a direct upgrade pitch, not a from-scratch explanation of the category.

Who's in the setCrypto.com · Nexo · Bitstamp · Mercuryo · Wirex · Young Platform · Plutus · Bleap

Geo gateEU/EEA + Switzerland/Andorra/Montenegro — the region where Brighty actually operates

What is measured vs. what is inferred. Measured (from career data): the person works right now at a competing crypto-card company, inside Brighty's geo. Inferred (strong but indirect signal): an insider on a crypto-card product is almost certainly close to the category and crypto-native — but whether they personally carry a card is something we infer, not observe. We sell this as a high-probability fit, not as confirmed behavior.

02How many we found in total

First, the full size of the pool. This isn't the sample — it's everyone we can see in our database matching the P1 criteria.

5,353

current employees across 8 competitors in the EU

anchor companies (crypto cards / spend)

EU/EEA+CH countries in the pool

Competitor	Current in EU	Type	In sample
Crypto.com	2,336	platform + card	389
Nexo	1,348	platform + card	220
Bitstamp	881	exchange + card	146
Mercuryo	423	payments layer	72
Young Platform	182	crypto card	47
Wirex	144	crypto card	29
Plutus	25	crypto card	18
Bleap	14	crypto card	8
Total	5,353		929

03How we built the sample

The 929 people out of 5,353 aren't random. The sample is balanced so all 8 competitors are represented proportionally, not "whoever came up first."

A quota per competitor. Each share is proportional to the size of its EU team; the small ones (Plutus, Bleap) are taken in full. Without this, Crypto.com alone would have crowded everyone else out.
Current employees only in Brighty's operating region (EU/EEA+CH). Former employees are a separate, colder layer; this is current staff only.
Deduplication by profile. Anyone listed under several roles is counted once: 1,025 rows → 929 unique people.
Full field set from the first query — role, location, career, education, skills, contact sources — in a single canonical format compatible with enrichment and packaging.

Why 929 and not exactly 1,000. After deduplication, 929 genuinely distinct people remained. We don't pad the count with duplicates — 929 clean records beat 1,000 with repeats.

04What we enriched with

Two layers of enrichment: free, from our database, then a paid API for the profiles that were short on data. The goal is maximum depth and contactability, with nothing fabricated.

96%

passed free enrichment from the database

461

topped up via paid API (full career)

116

fields on average per person (max 141)

Layer	What it added	Cost
Free enrichment from the database	+25 fields, doubled contact coverage, career history, education, skills — across 96% of profiles	$0
Paid API top-up	full career depth (experience, education, income estimate, industry) on the 461 profiles that were short on data	497 requests
Deep enrichment from the database	positions/education/skills via an internal key — raised depth to avg 116 / union 148 fields	$0

Honest about contacts. 36% have an email (331 of 929) — a realistic reach for an audience of large-platform employees, where personal email is less often public. We never fabricate addresses from a template. In return, every profile is "reachable" (email / phone / direct profile link) — 100% — and carries a full career picture for personalizing the first touch.

05How the scoring works

Every person gets a transparent p1_score (0–18) and an A+/A/B/C label. The formula is explainable: you can see why a lead is hot.

Signal	Points	Rationale
Has email	+5	reachable right now
Has phone	+1	an additional channel
Seniority: C-level / Head	+4	makes decisions, shapes the stack choice
Seniority: Lead / Senior	+2	weight inside the team
Function: product / growth / ops / support / BD	+3	feels the product's UX pain daily
Function: engineer / data	+1	crypto-native, but further from the UX decision
Direct card rival (Wirex/Plutus/Bleap/Young)	+3	product is an exact analogue of the Brighty card
Broad platform (Crypto.com/Nexo/Bitstamp/Mercuryo)	+1	category is familiar, but not a pure analogue
Profile active (≈12 months)	+1	a live contact, not a dormant one

A+ — contact immediately (≥12)

239

A — high priority (≥9)

337 · 298

B · C — nurture · watchlist

294 "hot" leads (A+/A) — people with a contact, weight, and a role that feels the product. Outreach starts here.

06Segments

The sample is sliced into ready-to-use cuts — each one a separate file in the dataset. Take the one that fits a specific campaign.

Segment	People	Use for
hot-leads (A+/A)	294	where to start — contact + weight + role
with-email	331	reachable by email right now
product-growth-ops	329	feel the UX pain — best fit for the "frictionless card" message
leadership (C-level/Head)	76	decision-makers (including for a B2B conversation)
direct-card-rivals	102	direct analogues of the Brighty card (Wirex/Plutus/Bleap/Young)
per competitor	8 files	Crypto.com 389 · Nexo 220 · Bitstamp 146 · Mercuryo 72 · …

Where they are located

Geography is heavily concentrated — this maps where competitors run real operational hubs in the EU.

Country	People	Reading
Bulgaria	509	Nexo and Crypto.com hubs (Sofia) — the largest node
Slovenia	116	Bitstamp's engineering/operations hub
Italy	63	Young Platform (Turin)
Cyprus	61	Mercuryo + a crypto jurisdiction
Spain · France · Germany · Netherlands	24·19·19·18	distributed teams
the other 20 EU countries	~120	a long tail — LU, PT, IE, LV, BE, PL, SE, CH…

07Who's at the top (preview)

The top rows by score — hot A+ leads with a contact. The full list with profiles and contacts is in the dataset.

Role	Currently at	Geo	Score	Email
Head of Performance Marketing	Young Platform	IT	16	✓
Head of Business Development	Young Platform	IT	15	✓
Chief Product Officer	Bitstamp	SI	13	✓
VP of Business Development	Nexo	BG	14	✓
Global Head of Brand & Marketing	Bitstamp	NL	14	✓
CTO & Co-Founder	Young Platform	IT	14	✓
Head of Business Development EMEA	Bitstamp	LU	13	✓
Head of Security Operations	Bitstamp	SI	13	✓

★ Showing 8 of 294 hot leads. The full list is in the dataset (XLSX/CSV/JSONL).

★Get the dataset

All 929 people, in every format, with scoring and segments. This is what you own after the pull.

Request this dataset: Request this dataset ↗ — a full delivery (~15 MB) contains:
• leads.xlsx — an Excel file with all fields for 929 people
• leads.csv / leads.jsonl / leads.json — the same data for CRM and programmatic processing
• segments/ — 13 ready-made cuts (hot-leads, with-email, product-growth-ops, leadership, by company)
• README.md — a description of the fields, scoring, and coverage

Each row is a person: name, role, current competitor, location, career, education, skills, contact sources, the p1_score, and the p1_label.
The p1_segments field lists which cuts a person landed in — filter by campaign.
The data is delivered as a secure package on request; this is the accompanying analytical report.

08What this pull proves

Persona → a real pool — 5,353 people

We turned the abstract "P1" into a concrete, measurable list of current competitor employees inside Brighty's operating region. MEASURED

Pool → an enriched, scored sample — 929 at 116-field depth

Balanced it, enriched it for free and paid, scored it on a transparent formula, sliced it into 13 segments. ENRICHED

Sample → a work-ready file — 294 hot leads

A downloadable delivery with every format and cut. From "customer persona" to "outreach list." ACTIONABLE

The next persona. We work through the other 7 ICPs the same way (crypto salary earner, relocator, B2B founder, diaspora, web3 studios, sharia network). Tell us which is next — or we run them in order.

Want a report like this for your company?

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

Request your report — hi@outricher.com ↗

Outricher · a professional graph of 1.17B profiles · @outricher · hi@outricher.com
MEASURED · Outricher data · pull P1 (refugees from competitor crypto cards) · 2026-06-28 · from public professional data