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To better understand customers in emerging markets, we developed a three-dimensional research framework that reveals the contextual, behavioral, and psychological dimensions of their financial lives.

We built our segmentation approach around the concept of financial health. This enabled us to generate a more realistic and actionable understanding of people's financial lives.









What are people like and what's their context?


Age, gender, household 

context, education, income sources, earnings, asset ownership, etc.


How do they use their money and manage their finances?

How individuals plan and prioritize their finances,

shape income and expenses,

build reserves, and cultivate receivables



What is their personality like, and how does it motivate them?

People's sense of control,

efficacy, self-esteem openness, trust, optimism, dependability conscientiousness, etc.

Why start with financial health?

We believe products designed to strengthen financial health are more salient and valuable to customers, expand markets, maximize customer lifetime value for providers, and drive the positive human development outcomes we seek.

People are financially healthy when they use available tools and strategies to effectively meet their basic needs, remain resilient in the face of unexpected shocks, and cultivate economic opportunities.

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Process & Methodology


How can we more deeply understand the financial lives of real people to design a powerful survey and employ well-grounded analysis?

This work differentiates itself by integrating methods from multiple research and analysis traditions—such as human-centered design (HCD), cognitive psychology, behavioral science, and large-scale survey-based market research.

Initial human-centered design (HCD) research was crucial for understanding the context of people's financial lives. Through HCD research, our team developed analytical models that identify key contextual, behavioral, and psychological variables to be measured in subsequent national surveys.  We also produced robust user profiles that provide an unprecedented, in-depth look at people's financial lives. These profiles and analytical models informed our survey design, guided our data analysis, and, ultimately, brought our segments to life with rich storytelling.

We designed the foundational HCD research to include a range of activities, from household financial mapping to scenario-based provocations.

Our HCD learning agenda included:

  1. Contextual elements that shape financial lives

  2. Financial behaviors and strategies

  3. Deeply felt needs driving behaviors and strategies

  4. Psychological motivations behind financial decision-making


How can a survey capture a more holistic portrait of people's financial lives?

Using the insights and analytical models developed through our initial HCD research, we created a global survey tool comprised of contextual, behavioral, and psychometric variables. The survey was adapted, based on each country’s context, to factor in local nuance on media, cultural norms, and the input of financial service providers. 


We used a rigorous, stratified sampling method to achieve nationally representative pools.​ Our method included contextual questions that went beyond demographics — for example, we explored financial decision-making roles within households. 


We examined generalized financial behaviors that go beyond the use of specific products. For instance, we investigated people's financial priorities and plans. Our psychometrics draw from academically proven survey questions as well as new, experimental questions that we designed. 


All questions were tested and refined by the Busara Center for Behavioral Economics to ensure their applicability to emerging market contexts.

Survey Design


How did we make sure that the collected data is representative of the target countries?

The sample sizes selected for the 6 countries are typical for nationwide representative surveys and in line with or larger than those used by other surveys, such as the Gallup World Poll / Findex. Kenya, Myanmar, Nigeria, and Tanzania were all covered with a sample of n=1,200. India and Pakistan were covered with a sample of slightly above n=3,000. The sampling approach was adjusted in each country based on the best available information. Some areas of active conflict were excluded from the survey.


Multistage stratification and/or probability proportionate to size (PPS) were key elements of the sampling approach. Country and context appropriate rules were used to randomize the sampling of individual households and the selection of individual respondents within those households. From each sample household, one eligible individual was randomly selected for interview.

Data Collection


How do we make sense of

5.5 million demographic, behavioral

and psychological data points?

To identify the segments in each country we used numerous data analysis techniques as well as the behavioral and decision-making models we developed through initial HCD research.


We identified clusters with similar characteristics based on the K-medoids approach, which groups respondents based on common survey responses. We ran descriptive statistical analysis and regression analysis on each cluster and then used our contextual, behavioral, and psychological models to interpret findings and describe the segments.


We included profiles of representative individuals from each segment to enrich the segment analysis and bring it to life.

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Cluster Analysis

a preliminary algorithmic sorting based on common survey responses

Download a sample segmentation plot analysis



How can we tailor offerings

to better support people's

varied lifestyles and experiences?

The ultimate goal of this work is to ensure that the insights garnered from segmentation inform the real-world work of financial service providers, policy makers, regulators, and development actors. These stories, statistics, and insights act as starting points. They complement tailored research and inform design and investment decisions. As such, each of the segments include: insights and opportunities as well as product, channel, and messaging design principles. For India and Kenya, we also developed a set of segment-specific, white label product concepts.

Development actors and financial services providers can use our data in a variety of ways:


Expand our research to other development sectors.

Use our approach to test the impact of development programs on the contexts, behavior, attitudes, and financial health of other individuals.

Evaluate impact on development interventions.

Use our data and approach to better understand other areas of interest such as gender, agriculture, and entrepreneurship.


Create segment-aligned digital financial products.

Develop products that speak to the needs, aspirations, behaviors, and personalities of segments (e.g. by combining information on segments with an HCD sprint).

Quickly expand knowledge about customers.

Utilize a mini-questionnaire to rapidly segment existing users, deepen customer insights, and improve design and uptake.

Cross-reference data.

Match our data with call records and transaction data of mobile network operators to learn how different segments use each provider's products and services.

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