Mastercard Center for Inclusive Growth
Release, June 2025
Deepening the partnership to track 1.1 billion people on their way into the middle class, and where the gaps remain.
Case studies
See the decisions clients made with our data.
Four decisions our clients bring us, each with the case that answered it.
Trusted by global brands
What clients decide with us.
Four decisions, each with the case that answered it, then the global beauty brand whose questions became five of our datasets.
01 Where to open next
A footprint decision. Rank every city by the stores its consumers can keep busy, then open where the gap to today is widest.
City A-01 had room for 24 more stores.
A global coffee chain ranked its cities by sales per store. We ranked them by how many stores each city's consumers could keep busy. City A-01 had 18 and could carry 42. The chain now plans its openings starting from the cities with the biggest gaps.
- How we worked
- Data support and insight
- Who else brings it
- Restaurant groups, Pharmacies, Gyms, Hotels
Swipe to see the full chart.
Each hexagon is a neighbourhood of City A-01. The darker it is, the more young adults with money to spend live there. City records simulated.
02 What to charge in each market
A price tier decision. Set the price each market's adults can carry and count how many more of them can buy.
One price reached 82% of adults in one market and 8% in another.
An app marketplace charged the same $2.99 subscription in all five of its markets. We checked that price against what adults in each market can spend. Four markets needed a lower price and the richest could take a higher one. In the poorest market, the share of adults who could afford it went from 8% to 78%.
- How we worked
- Pilots and bespoke work
- Who else brings it
- Streaming, Software, Subscriptions, Financial products
Can afford the one $2.99 priceAlso can afford a price set for the marketAdults in the market, by what they can spend
Swipe to see the full chart.
Each curve is one market's adults, from least to spend on the left to most on the right. Market records simulated.
03 Which cohort to grow with
A targeting decision. Rank the age groups on the spending they will add, and let the plan follow the ranking.
Gen Z went from last in the plan to first.
An oral care brand ranked four age groups by how fast their numbers grow. That put the over-45s at the top and Gen Z at the bottom. We ranked them by how fast their spending on oral care grows instead, and Gen Z came first.
- How we worked
- Data support and insight
- Who else brings it
- Personal care, Nutrition, Healthcare, Financial services
Average yearly growth to 2035, from our model. Cohort records simulated.
04 Whom to build the data with
A partnership decision. Four organisations put the model to work in public, on the middle class, on generations, on payments and on poverty.
NIQ
Five joint reports
Five reports together, from Spend Z to Spending Longer and Living More, on retail and shopper data set against our model.
Case study and webinar
Market sizing for its expansion into Africa, India and Southeast Asia, and a webinar on payments in emerging markets.
GIZ
Two public clocks
The World Poverty Clock and the Water Scarcity Clock, underwritten for the first and the sixth Sustainable Development Goals.
05
A global beauty brand's questions became five of our datasets.
Each dataset below began as a planning question from a global beauty brand's teams. Every client can use it today in World Data Intelligence.
They askedIt became
They asked
Which cities next?
2021
It became
Cities
Spending for 9,400+ cities, so a market can be entered district by district.
Explore CitiesThey asked
How big is beauty, market by market?
2023
They asked
Which generation carries the category?
2025
It became
Generations
Spending by birth cohort, ranked on what each cohort will add.
Explore GenerationsThey asked
How many homes can afford the premium tier?
2026
It became
Households
Homes by size, income and life stage, so a tier can be sized in households.
Explore HouseholdsThey asked
Who in the home does the buying?
2026
A client story in full
Fintech & Payments
Charting a Path Into Emerging Markets
EBANX, a Brazil-based payment company built for emerging markets, needed a centralized, reliable source of consumer spending and market-sizing data, along with visibility into financial inclusion and payment preferences.
Bring us the question your team is working on.
Every case on this page started with a single question. Send us yours and we'll show you what our numbers say about it.