About Costlas

Costlas aggregates publicly available cost of living data for 140 countries and 1,377 cities — surfaced through an interactive globe, side-by-side comparisons, a relocation score, and live currency conversion.

Data sources

All price points are aggregated from open community-maintained living-cost databases. Every record stores its original source URL so any figure can be independently verified.

Trust score (0–100)

Every country and city gets a confidence rating shown as a colored badge:

• 80–100 High — broad coverage, recently verified
• 60–79 Good — solid sample with minor gaps
• 40–59 Fair — partial data, treat as indicative
• 0–39 Low — sparse data, use with caution

Inputs: number of data points, presence of a summary monthly cost, category coverage (rent · food · transport · utilities), and city diversity for countries.

Relocation score

A single 0–100 ring shown on every country and city page. Blends three signals:

• Affordability (50%) — logarithmic decay over the summary monthly cost in USD
• Confidence (30%) — the trust score above
• Diversity (20%) — log2 of tracked cities, capped at 100

Higher scores mean a cheaper, well-documented place with multiple city options — a good shortlist candidate, not a verdict.

Currency conversion

USD is the canonical storage currency. The header switcher converts every value live using daily FX rates from a free public source (open.er-api.com). The footer shows the last refresh timestamp.

How we calculate & estimate

Wherever possible, we show verified figures pulled directly from our sources. When a specific number isn't available for a city or country, we fill the gap with a clearly-labelled estimate so the page stays useful instead of empty. Every estimated value is prefixed with ~ and tagged "Estimated".

• Single vs. Family of 4 toggle — the header switch reframes every cost on the site. When a verified family-of-4 figure exists, we use it. When it doesn't, we apply a ×2.7 multiplier on the single-person cost (the commonly-cited family-of-4 ratio excluding rent). Switching back to "Single" reverses the same math.
• Average salary (after tax) — when a city has no local salary survey, we compute the median salary ÷ cost ratio across other cities in the same country, then apply it to that city's cost. If the country itself has no salary samples, we fall back to a global median ratio (~4.3×). The result is an order-of-magnitude estimate, not a payroll figure.
• Currency conversion — every number is stored in USD and converted live in your chosen currency using daily FX rates. Local-currency values shown on country/city pages come straight from source data.
• Family-of-4 multiplier — based on widely-used cost-of-living conventions (Numbeo, Expatistan, OECD equivalence scales land in a similar range). It's a sensible default, not a precise household budget.

Please do a reality check

Costlas is a research head-start, not a relocation contract. Before making any real-life decision (a job offer, a move, a visa application), please:

• Cross-verify against Numbeo, Expatistan, Nomad List, and local subreddits / Facebook groups for the city.
• Talk to one or two people who actually live there — neighborhood, lifestyle, and family size move costs by 30–50% easily.
• Add your own line items we don't track yet (childcare, private healthcare, debt repayments, car ownership, pets).
• Treat anything marked "Estimated" with extra caution — it's a model, not a measurement.

Found a number that looks wrong? Hit the Report button next to any item. Once enough people submit values inside a tight range, the figure auto-updates and shows a "Community updated" badge.

Limitations

• Aggregated community data — individual prices can vary by neighborhood and lifestyle
• Summary costs exclude rent and assume a modest lifestyle; family-of-4 figures may be derived from single-person data
• Average salary is estimated for cities without local survey data
• FX rates update daily, not intraday
• Relocation score does not account for visa, safety, healthcare, or climate (yet)

Roadmap

• AI relocation assistant (RAG over our database)
• Saved comparisons and favorites
• Visa, tax, safety, and internet-quality layers
• Public API

Meet the creator

I am Gobinda Tarafdar — a WordPress product marketer by trade, a stubborn problem-solver by habit, and a lifelong Harry Potter devotee by heart. Somewhere between Hogsmeade and a half-finished launch plan, this broadsheet was conjured into being.

By day I am the Product Marketing Specialist at WPBakery — the page builder that quietly powers a sizeable corner of the WordPress universe. Before that, I helped a single plugin cross 400,000+ active users through positioning, user research, and a relentless focus on what actually moves the needle.

When the day-job owl flies home, I tinker on my own little workshop of spells: Docscriber (documentation, conjured), TheRecaller (a memory charm for the things you keep forgetting), TheEditra (a video editing cauldron of my own brewing), and the newest addition The Quill Press — a tech news platform styled after the Daily Prophet itself. Costlas is the side-quest I refuse to put down.

Why Costlas exists

It started, as most decent ideas do, over a long conversation with friends and family. Someone was weighing a move abroad, another was daydreaming about a quieter city, and a third just wanted to know if their salary would stretch further somewhere else. We kept circling the same wall: hours of scattered tabs, half-trustworthy numbers, and no clean way to compare one place against another.

That night I scribbled the first sketch of Costlas — a single place to do the basic research, see the numbers side-by-side, and walk away with enough clarity to actually plan. Not a verdict, just a head start. A small spell of support for anyone standing at the same crossroads we were.

Get in touch

The best way to reach me is on Twitter — @Gtarafdarr. DMs are open for questions, feedback, corrections, or just to say hello.

Costlas is free and will stay that way. If it saved you a few hours of research and you'd like to chip in toward keeping the data fresh, you can buy me a coffee here. Every bit helps — thank you.