Hostinger, from the customer's seat

ArteLonga runs its entire network with Hostinger at the door — DNS, hosting, and now Horizons. We came as users and we stay as customers. Every small business we bring online is one more domain on Hostinger: horizontal scaling for Hostinger. This is the Data Analyst application, told from that seat.

the case study ↓ the role ↗ my technical portfolio → Hostinger principles ↗

Case study — Retro Umarizal: menu → live Horizons domain

A cold lead with a single restaurant menu became a paying Hostinger customer in ~24h — from a shareable draft to a domain live on Hostinger Horizons.

Jun 2 —arrive

Retro Umarizal arrives with one asset: a restaurant menu. A new lead enters the network.

Jun 2 —instant MVP

A self-hosted staging MVP goes live on a shareable subdomain — no purchase, no DNS for the client to touch. The owner sees a working site within the hour.

Jun 2 —validated

Client approves on the staging URL → buys retroumarizal.com.br. Investment follows validation, not before.

Jun 3 —converted to Horizons

Rebuilt on Hostinger Horizons; the customer compared both and chose the Horizons build. Live on the apex with a Let's Encrypt cert; the self-hosted MVP retired.

Every partner is one more funnel — and every funnel that lands is more horizontal scaling for Hostinger. Retro Umarizal is data point #1 of the Horizons funnel: real, dated HORIZONS_PROMPT → APP_GENERATED → PUBLISH events, ready to measure.

Read the full study — funnel, Wilson CIs & insights →

A user journey worth measuring

From first contact to a site live on its own domain, the path a customer travels reads as a funnel — a simple, shared way to see where Marketing Impact, activation and retention actually happen, with a number on every step. I built it as an interactive dashboard; it makes the case better than this paragraph can.

What the numbers are — and aren't. The demo runs on two small samples: the Retro case study above, and my own inbox receiving Hostinger's emails. The second is a sample of one — no general proxy for anything — so the figures speak to engagement (did a message arrive and get opened), not churn or conversion. The point is the method and the honesty about its limits, not the counts.

Open the dashboard →

Customer feedback on Horizons — what I'd report as the analyst

First-hand signal from building retroumarizal.com.br on Horizons — the honest product feedback this role turns into roadmap.

👍 Worked well

Quick intake, feedback incorporated effectively — credit-cheap to a working prototype. Approved within 24h, final edits on free credits. The completion sound is genuinely satisfying. Far easier than deploying and tuning DNS by hand.

🔧 Friction

Initial chat hides the start of the conversation at 100% zoom (recording ↗); some early instructions skipped (e.g. "scrape this site for content"); content needed structured HTML — a URL or pasted copy didn't take (3 exchanges, credit-heavy for content); unclear how to edit after publishing; English by default.

📊 Analyst ask

Surface build telemetry from the start — credits per stage, exchanges-to-prototype, edit-after-publish rate: the unit economics the Horizons dashboard needs.

Stats & dashboard

The numbers behind the network — and a live dashboard, built in Tableau. Method and raw measurements live in the studies: DNS findings · API reference.

1,473commits

286merged PRs

9web services

6partners

Tableau dashboard renders here once published.
Set data-src on this element to the Tableau Public view URL.

Technical portfolio — its own thing

The case study above is told from the customer's seat. The engineering behind it — the platform that produces this data — is a separate artifact: a System Portfolio with two timelines (data and systems), each running to today. It stands on its own; this page does not depend on it.

Open the technical portfolio — the two timelines →

Clarifications — requirements, met

Every line of the posting, matched to the timeline and the record — evidence, not claims. Each links to its proof.

2+ yrs in data

14 years on the data path (2012–2026) — 7× the bar.

Hands-on SQL

SQL on Spark / Delta Lake at Propz; AWS (S3, EMR, QuickSight) + GCP.

Dashboards & reporting

Tableau (above) and R figures published in peer-reviewed papers; multilingual.

Python / R

Python (scikit-learn, TensorFlow, NLP: UMAP, DBSCAN, spaCy); R across the publications.

A/B testing & statistics

Peer-reviewed behavioral statistics; Wilson CIs + experiment validity in the funnel study.

Raw data → insight

Built & shipped ArteLonga solo; real-time quant pricing on live markets.

Before ArteLonga: Senior Data Scientist, Quant, and years of research. Full history in the résumé, publications in the bibliography. Already at the door as a customer — applying to build from the inside.

Yuri Y. Vieira Sugano · São Paulo · yuri@artelonga.com.br · back to yuri