World Data Lab

Find demand before it shows up in the data.

Every engagement starts from a decision someone has to make, and works back to the number that settles it. The same forecasts sit behind all of them: 194 countries to 2050, more than 9,400 cities to 2040, and 200+ categories.

194countries, 2000 to 2050
9,400+cities, to 2040
200+spending categories
16 yearsof forecasts checked against outcomes

Trusted by teams at

DeloitteMarsHenkelBrown-FormanBoltonCabotUberTapestryCoca-ColaColgateSpotifyL'OréalDeloitteMarsHenkelBrown-FormanBoltonCabotUberTapestryCoca-ColaColgateSpotifyL'Oréal

Five decisions we help you get right.

Market entry & prioritisation

Go where the consumers are forming

We rank every market to 2050 and every city to 2040 by the consumers you sell to, and how fast that base grows, so you expand where demand is forming.

Informs

where to enterwhere to double downwhere to wait.

Market entry & prioritisation

Go where the consumers are forming

We rank every market to 2050 and every city to 2040 by the consumers you sell to, and how fast that base grows, so you expand where demand is forming.

Informs

where to enterwhere to double downwhere to wait.

See them worked in the case studies →

From a global model to your decision.

An illustrative engagement: a beauty brand deciding where to launch premium skincare next.

Illustrative example

Forward-looking, granular and consistent.

4.67bn 20267.17bn 2050
World consumer class, billion people, 2026-2050. Source: World Data Intelligence.
See the data
World consumer class, billion people, 2026-2050.
YearConsumer class (billion)
20264.668
20274.791
20284.914
20295.037
20305.158
20315.28
20325.401
20335.521
20345.639
20355.756
20365.869
20375.98
20386.09
20396.199
20406.309
20416.42
20426.529
20436.629
20446.713
20456.774
20466.807
20476.832
20486.878
20496.979
20507.168

Forward-looking

Demand before it arrives

Because every consumer is placed and then forecast each year to 2050, you can see where demand is forming long before it reaches a sales report, and decide where to be ready for it ahead of the competition.

Modelled to 2050, every year

Indonesia47%
Jakarta99%
West Sulawesi9%
Share of people in the consumer class. Source: World Data Intelligence.
See the data
Share of people in the consumer class.
MarketConsumer-class share (%)
Indonesia47
Jakarta99
West Sulawesi9

Granular

An average hides consumers

National figures bury the people who matter most to a strategy: the affluent households inside a lower-income country, the squeezed ones inside a wealthy one. Indonesia’s figure, 47% of its people in the consumer class, is an average of provinces that run from 99% in Jakarta to 9% in West Sulawesi: two different markets inside one country number.

200 categories · 9,400+ cities

See the full story in the insights gallery
World map showing over 9,400 city nodes with highlighted markers for New York, Sao Paulo, London, Lagos, Dubai, New Delhi, Shanghai, Tokyo, Ho Chi Minh City and Jakarta
Source: World Data Intelligence.

Consistent

Apply consistent definitions across more than 9,400 cities

One harmonized city framework worldwide, so London, Lagos and Ho Chi Minh City are measured the same way, and comparable side by side. The same method runs across every country, and Homi Kharas's 2010 forecast of the middle class came within a few percent of what happened.

16 years of validated forecasts

Read the paper →

Decisions it has settled.

Three clients, three questions, and what each one changed.

Where to open

24

more stores in one city

A coffee chain found a city with room for 24 more stores, and now opens where the gaps are biggest.

Read the case

What to charge

8% to 78%

of adults in its poorest market who could afford the price

An app marketplace priced market by market: 8% of adults in its poorest market could afford one global price, 78% a local one.

Read the case

Who to target

Last to first

Gen Z in the brand's plan

An oral care brand ranked age groups on spending growth, and Gen Z went from last in its plan to first.

Read the case

Soft drinks

Scenario modelling

Consumer spend scenarios under shocks like a sugar tax or a recession, by country.

Real estate

City footprint

Based on consumers and category spend, are you present in the right cities?

See all case studies →

Four ways to work with us

Pick the entry point that fits how your team makes decisions.

01 - The platform

World Data Intelligence

Self-serve, one login. Screen every market, size the opportunity and price to what each one can afford.

  • Seats scoped to your markets
  • Explore, Affordability, Data Catalog
  • Re-run in full four times a year
  • Free demo, then an annual license

02 - The feed

API & raw data

The same numbers, inside your own stack, for teams that would rather query than click.

  • API endpoints, queried on demand
  • Raw data drops for your warehouse
  • Refreshed with every model run
  • Docs, SDKs and support included

03 - Our analysts

Analyst partnership

Our team does the analysis with you, so the answer arrives as a decision rather than a table.

  • Analyst hours included in the license
  • Bespoke cuts and one-off deliveries
  • Reports, decks and briefings
  • A named contact for your category

04 - Pilots & bespoke

A build of your own

When the question is bigger than the product, we build the dataset or the platform for it.

  • Three-month pilots on one decision
  • Advisory retainers with your team
  • Multi-year bespoke data projects
  • Funded custom platforms

Credentials deck

Get the World Data Lab credentials deck

A concise overview of who we are, what we do, and how our data powers decisions for governments, foundations and Fortune 500 clients.

  • Who we are and what we build
  • The methodology and dataset in brief
  • Selected client work across sectors
  • Ways to engage - from platform to bespoke
Talk to our team

Let's talk through your market question.

Tell us the decision you are trying to make, and we will show you the forecasts that bear on it.