Case Study, Part 1

Segmentation of Pregnant Women at Risk of Malaria

Four women waiting with their infants at a health facility.
Women waiting with their infants at the health facility (PMI)

Case Study

Malaria in pregnancy remains a major health problem with critical risks for pregnant women and their babies. While antenatal care (ANC) services and trained personnel are vital for preventing and treating malaria among pregnant women, counseling during ANC services does not always cater to the unique needs of the many different sub-groups of women who seek this care, including, for example, adolescent and/or single mothers. Often ANC counseling is seen as one size fits all, or at best, women are given varying levels or types of counseling based on their age. But a more precise and potentially impactful counseling will be tailored to the woman’s actual beliefs, attitudes, and feelings towards pregnancy, malaria, ANC, intermittent preventive treatment during pregnancy (IPTp), whether she has had other pregnancies or if she feels supported by her community.

These are all examples of needs, beliefs, etc., attributes that can be used to develop a psychosocial segmentation of pregnant women. This audience segmentation can then guide more personalized counseling.

The following case study reviews the segments that emerged from an analysis of pregnant women at risk for malaria in Cameroon, Côte d’Ivoire, and Malawi. The insights presented serve as the foundation for tailored interventions and recommendations developed for each segment, which are described in detail in Session 3.

Key Questions & Analysis


The Breakthrough ACTION project utilized Malaria Behavior Survey datasets from Cameroon (2019), Côte d’Ivoire (2018), and Malawi (2020) to conduct a psychosocial segmentation analysis to understand pregnant women’s ANC attendance and IPTp acceptance and use behaviors.

Scope of the Malaria Behavior Survey data used for the ANC segmentation

Cameroon

Cameroon

2019 survey

2 survey zones


2,756 households

4,514 respondents

Côte d’Ivoire

Côte d’Ivoire

2018 survey

4 survey zones


5,969 households

8,675 respondents

Malawi

Malawi

2021 survey

3 survey zones


3,862 households

5,485 respondents

FOCUS: Women with a live birth in the last two years = 4,646

Breakthrough ACTION reviewed the datasets and selected variables for the analysis that provided insights into three main research questions related to pregnant women and women who had a live birth within the last two years:

  • How many times did women go for antenatal care during their pregnancy? (Outcome variable 1: ANC attendance)
  • Do women believe that ANC service providers in their community generally treat pregnant women with respect? (Outcome variable 2: Perception of health providers)
  • How many times did pregnant women take the medicine to prevent them from getting malaria during pregnancy? (Outcome variable 3: IPTp uptake)

Approach


Click each phase to learn the three-step process Breakthrough ACTION followed to conduct the analysis and determine the segment personas.

Phase I – Identify factors that influence ANC attendance and IPTp acceptance and uptake

Phase I

Identify factors that influence ANC services, experience, and IPTp uptake among pregnant women and women who had a live birth within the last two years.

Women’s responses were analyzed across the three MBS datasets in Cameroon, Côte d’Ivoire, and Malawi through a Chi2 correlation analysis to identify which factors showed a strong correlation with the three research questions. This resulted in uncovering five key drivers of attendance to ANC and IPTp uptake.

  1. Perception of providers
  2. Trust in malaria treatment and insecticide treated nets (ITNs)
  3. Spouse/partner discussion
  4. Social norms
  5. Perception of the risk of malaria

A description of each key driver is presented in the section titled, Factors Influencing ANC Attendance & IPTp Uptake.

Phase II – Conduct a quantitative analysis and identify opportunities

Phase II

Conduct a quantitative segmentation analysis and identify opportunities for positive behavior change.

Then, a psychosocial segmentation analysis was conducted using a latent-class analysis (see Introduction to latent class analysis to learn more). Five segments emerged from the analysis and are presented below in the section titled, Meet the Segments. 

Once the segments were finalized, we then developed the segment identification tool. More information is presented below in the section title, How to Identify Segments in a Given Population.

Phase III – Develop a malaria-focused ANC counseling tool for health providers

Phase III

Develop a malaria-focused ANC counseling tool for health providers.

Following that, a pretest of the Malaria ANC counseling tool was conducted in Malawi. The pretest workshop uncovered additional insights into the behavior of the segments regarding ANC and helped refine the design and messages of the tool. More information regarding the counseling tool is available in Session 3.


Factors Influencing Uptake


5 Factors

The five key factors associated with women’s ANC attendance and IPTp uptake are: perception of providers, trust in ITNs & treatment, partner/family discussion, social norms, and risk perception. Flip each card to learn more.

Perception of Providers

Women’s perception of providers and how she believes she will be treated by the provider (e.g., if she thinks she will be treated with respect, or sent away if she arrives without her husband).

Trust in ITNs & Treatment

The level of trust pregnant women and women with a live birth in the last two years have regarding insecticide treated nets (ITNs) and malaria treatment obtained at the health facility.

Partner/Family Discussion

The frequency that each segment spoke with their spouse or family member about attending ANC, and their involvement in the decision to attend ANC visits.

Social Norms

Whether women believe that other women in the community also attend ANC and take IPTp.

Risk Perception

How each segment perceives the threat of contracting malaria during pregnancy, whether it is of little, moderate, or of great concern.

Meet the Segments


Pregnant Women at Risk of Malaria

Five segments of pregnant women at risk of malaria emerged across Cameroon, Côte d’Ivoire, and Malawi. Each segment differs in their level of ANC attendance and IPTp uptake, as well as the 5 factors described above, which help us understand what drives those behaviors. This section summarizes the key characteristics of each ANC client segments personas. Click the thumbnail image for a downloadable table.

Personas thumbnail

Segment 1
Active Modernists

ANC Attendance

5+ visits

IPTp Adherence

Uptake is moderate

Perception of Providers

Mostly positive

Trust in ITNs & Treatment

High

Partner/Family Discussion

Discuss ANC with spouse

Social Norms

Believes other women go to 4+ ANC visits

Risk Perception

Believes malaria is a moderate threat

Segment 2
Unhurried Informed

ANC Attendance

1-4 visits

IPTp Adherence

Uptake remains low to moderate

Perception of Providers

Mostly positive

Trust in ITNs & Treatment

High

Partner/Family Discussion

Sporadically discusses ANC with spouse

Social Norms

Believes women should wait before going to ANC visits

Risk Perception

Believes malaria is a moderate threat

Segment 3
Cautious Moderates

ANC Attendance

1-4 visits

IPTp Adherence

Uptake remains low to moderate

Perception of Providers

Believes she will be sent away without spouse

Trust in ITNs & Treatment

High

Partner/Family Discussion

Extensively discusses ANC and jointly decides with spouse

Social Norms

Believes few women go to 4+ ANC visits

Risk Perception

Believes malaria is easy to treat and not a threat

Segment 4
Uncertain New Mothers

ANC Attendance

0-4 visits

IPTp Adherence

Uptake remains low to moderate

Perception of Providers

Believes she will not be treated with respect

Trust in ITNs & Treatment

Moderately high

Partner/Family Discussion

Decides alone or is influenced by a family member

Social Norms

Believes other women go to 4+ ANC visits

Risk Perception

Believes malaria is a moderate threat

Segment 5
Seldom Adopters

ANC Attendance

Rarely attends ANC

IPTp Adherence

Unlikely to receive or to take IPTp

Perception of Providers

Neutral

Trust in ITNs & Treatment

Moderate trust in ITNs and malaria treatment

Partner/Family Discussion

Least likely to discuss ANC with spouse

Social Norms

Believes few women go to 4+ ANC visits

Risk Perception

Believes malaria is a moderate threat


Representative Quotes

The following quotes were developed based on the key factors, beliefs, and behaviors of each segment. These stories were refined based on stakeholder experiences during workshops in Malawi.

Active Modernists

“My spouse and I are aware of ANC benefits during my pregnancy. I go to ANC early and as many times as I can, as do other women in my community.”

Unhurried Informed

“I know ANC is useful but I’m not in a hurry to go to my first visit. I’m less convinced about IPTp.”

Cautious Moderates

“I discuss key decisions with my spouse, such as going to ANC visits. I’m not too worried about malaria, and people in my community don’t really go to ANC visits.”

Uncertain New Mothers

“I’m a single mother. i don’t have much experience with ANC providers but I’m not sure they will treat me with respect.”

Seldom Adopters

“My partner generally decides for me. I don’t go to ANC visits or take IPTp.”


After reviewing the percentage of segment per country, click to learn more about key parameters by segment.

Percentage of segment per country

The same five segments exist across the two countries but with different distributions within the populations, reflecting each country’s local context. The proportion of each segment across Cameroon, Côte d’Ivoire, and Malawi is found below.

Some segments comprise a smaller percentage in some countries (e.g., Cautious Moderates in Côte d’Ivoire (1%) and Malawi (3%). When developing programs and interventions, it is important to account for the size of the segment in the country and prioritize segments not only based on the opportunity to improve specific behaviors (e.g., IPTp uptake), but also the size of the segment in the population and how easy it will be to reach them and change behavior. Click the figure for a downloadable PDF.

Segment percentage by country
Figure 5. ANC clients segment representation per country
Key parameters by segment

Below you see a visual representation of the segment across the five key factors influencing the behavior of pregnant women and women who had a live birth in the last 2 years. Each segment is mapped across the five axes in the spider-chart below and represented by their name and their color. The spider chart enables us to visually identify areas of strengths and weaknesses for each segment and is complementary to the text description provided above on each segment. For example, the Cautious Moderates (yellow), have a good perception of health workers and high trust in ITNs, as represented by their high score on the chart below. However, they have a low score on “Risk Perception” of malaria (severity) and “Social Norms” reflecting their underestimation of the risk of malaria and their perception that other women in the community do not go to ANC visits. For more details on each axis you can refer to the text on the left side of the spider-chart. Click the figure for a downloadable PDF.

Figure 6. Relative performance on key characteristics for each segment

Partner/Family Influence

Represents spousal/family influence in decision-making regarding going to ANC visits (higher = less autonomy to make decision on her own)

Social Norms

Perception of how many women in the community take preventative care and go to at least 4 ANC visits (higher = believe more women goes to ANC and take IPTp)

Trust in ITNs & Treatment

Represents trust level in ITNs and preventive/treatment drugs coming from the health facility (higher = greater trust)

Perception of Providers

Represents the perception of health workers at the facility (higher = more positive perception of health workers)

Risk Perception

Represents perception of the gravity of malaria care and how easily it can be treated (higher = greater awareness of malaria risk)

How to identify the segments in a given population


Now that we have identified segments, it is important to have a tool that can be used to identify them in a given population.

A segment identification questionnaire is a brief set of questions that allows us to determine what segment the ANC client is categorized. These questions were selected using the MBS datasets and a Chi-squared automatic interaction detector (CHAID) model. Download a more detailed PDF of the following segment identification questionnaire.

1.

How many ANC visits should a woman attend during their pregnancy?
How important is attending ANC during pregnancy?

Answers:

  • 0-1 visits
  • ANC is not important
  • Continue to 1a

Answers:

  • 5+ visits, as many as possible
  • ANC is very important
  • Continue to 1b

Answers:

  • 4 or less visits, some visits
  • ANC is somewhat important
  • Continue to 2

1a.

Discuss ANC decision making with her spouse

  • If there is little to no discussion, and her spouse largely makes the decision, confirmed Seldom Adopter.
  • Otherwise, go to 2

Seldom Adopter

1b.

Discuss ANC decision making with her spouse

  • If there is some discussion & she has agency in decision-making, confirmed Active Modernist.

Active Modernist

2.

Who makes the decision to go to ANC in your household?
Yourself, your spouse, or another individual?

Answers:

  • Myself
  • Mother
  • Another individual
  • Continue to 2a

Answers:

  • Myself and my spouse
  • My spouse
  • Continue to 3

2a.

Discuss her current marital status

  • If she is widowed, separated, divorced, or single, confirmed Uncertain New Mother.
  • If she has a partner, go to 3

Uncertain New Mother

3.

Have you ever seen or experienced a pregnant woman that has been sent away or reprimanded when she goes to the health facility without her husband/partner?

Answers:

  • No, she has not
  • Unlikely
  • Doesn’t know
  • Continue to 3a

Answers:

  • Yes, except in special circumstances
  • Yes, at most facilities
  • Continue to 3b

3a.

Discuss her perception of malarial threat level

  • If she worries about malaria and thinks it is difficult to treat, confirmed Unhurried Informed.

Unhurried Informed

3b.

Discuss her perception of malarial threat level

  • If she worries about malaria but thinks it can be easily treated, confirmed Cautious Moderate.

Cautious Moderate

Using this tool allows SBC programmers, providers, or other stakeholders to identify client segments by asking a limited set of questions, with a high level of accuracy. In the next session, you will see how this tool was incorporated into segment-specific counseling cards for ANC clients.

Key Takeaways

It is vital to start any segmentation process by identifying the malaria-related issue and population of interest.

A segmentation process has numerous aspects and requires a wide range of expertise. Having a strong team of diverse skills, experiences, and connections to the target population is essential for a successful segmentation process.

Review existing research on the target population to gain a better understanding of what patterns and trends exist in the group, and what reasonable segments may look like. This background research will help inform the rest of the segmentation process, including developing research questions, determining the most viable segmentation model, and even brainstorming potential solutions for social and behavior change.

While quantitative analysis helps uncover precise insights from existing data, qualitative research is beneficial for supplementing segment personas with a nuanced understanding of behavioral drivers.

The behavior of ANC clients in Cameroon, Côte d’Ivoire, and Malawi is influenced by factors such as their trust in malaria treatment, their beliefs related to social norms, their perception of the risk of malaria (severity), the discussion with their spouse/partner or a family member, as well as their trust in insecticide-treated bed nets (ITNs).

Five segments of pregnant women at risk of malaria emerged from our segmentation analysis in Cameroon, Côte d’Ivoire, and Malawi: 1) Active Modernists, 2) Unhurried Informed, 3) Cautious Moderates, 4) Uncertain New Mothers, 5) Seldom Adopters.

All segments are found across the three countries where the study was conducted but in different proportions.

Check Your Understanding

Thank you for completing the second session of Audience Segmentation for Malaria. Next is an ungraded quiz to test your understanding of Session 2. Click the Knowledge Check button to get started.

Conducting Audience Segmentation

Conducting Audience Segmentation

Session 2

The purpose of this session is to describe the steps of conducting audience segmentation in more detail and provide an example of a segmentation effort developed to inform malaria SBC programming. Through a case study of pregnant women at risk of malaria in Cameroon, Côte d’Ivoire, and Malawi, this session will describe the segments identified through a psychosocial (focusing on needs, behaviors, and attitudes), as well as the segments’ defining characteristics and the factors influencing their behavior.


Learning Objectives

List the steps and resources required to conduct an audience segmentation with a quantitative foundation and complementary qualitative research.

Describe a psychosocial segmentation conducted among pregnant women at risk for malaria.

List key distinguishing factors of each segment.

Describe tools to segment members of a target population to tailor SBC interventions.

Steps to Create a Segmentation


Session 1 introduced the concept of audience segmentation, defined types of segmentation, described the role of audience segmentation in malaria SBC, and outlined the steps required to conduct an audience segmentation. Session 2 will describe the first seven steps required to conduct an audience segmentation in greater detail. (Steps 8-11 are covered in Session 3.)

  1. Identify the priority behaviors
  2. Define the target population
  3. Enlist key stakeholders
  4. Develop research questions
  5. Select a dataset
  6. Define segments
  7. Refine your segments
  8. Develop intervention elements
  9. Pilot solution
  10. Evaluate & Refine
  11. Adapt & Scale

Step 1. Identify the Priority Behaviors


Audience segmentation provides great insight into how certain behaviors vary across a population and can be used to identify and prioritize groups for social and behavior change. To leverage audience segmentation, start by identifying the priority behaviors. For example, what malaria-related behavior needs to be addressed in your local context? What is the desired behavior change that will result in improving case management or reducing malaria incidence?

Below is a list of several malaria prevention and control priorities. Use these as a starting point for brainstorming the desired social or behavior change for your segmentation.

  • Use an ITN correctly every night / Increase correct and consistent use of ITNs
  • Attend ANC early and frequently / Increase early and frequent ANC attendance
  • Accept and use IPTp / Increase acceptance and use of IPTp
  • Seek quality care for fever within the same day or next day of fever onset / Increase prompt seeking for fever
  • Adhere to national malaria case management and malaria in pregnancy guidelines / Increase adherence to national malaria case management or malaria in pregnancy guidelines.

Step 2. Define the Target Population


Second, determine which population you want to encourage the desired behavior change within. Looking at DHS data, for example, we can determine which populations may be particularly vulnerable to malaria or impacted by malaria. Examples of populations of interest to focus on malaria behavior change include pregnant women, caregivers of children under 5, health providers, farming communities, and more. Priority populations for malaria interventions are most commonly pregnant women and caregivers of children under 5.

Step 3. Enlist Key Stakeholders


Next, identify individuals, including experts in the research methods required to conduct segmentation analyses. It is important that stakeholders are aligned to the objective of the audience segmentation identified in steps 1 and 2, as they will be closely involved at different points in the process.

It is important to include a mix of stakeholders in the process, ensuring that they have an equal voice in providing feedback and decision-making. Ensuring a diversity of voices in the decision-making process is vital to designing inclusive solutions as they have direct impacts on people’s lives. Flip the functional group cards below to reveal their potential roles. Consider the functions that already exist on your own team, then fill in the gaps.

knowledge icon

Knowledge

People with knowledge of national malaria trends, data analysis, or primary data collection. Examples may include researchers, statisticians, vector-borne infectious disease experts, or malaria control experts.

experience icon

Experience

People with experience with in-country malaria control and elimination programs or in implementation and evaluation of interventions. Examples may include program implementers, staff from NGOs, or health personnel working directly with the population of interest.

influence icon

Influence

People with influence over policy and quality improvement efforts for health facilities or at the health system level. Examples may include policy makers, Ministry of Health officials, or individuals from the National Malaria Program (NMP).

Step 4. Develop Research Questions


It is now time to develop 2-3 research questions to guide your audience segmentation. With your team, particularly those knowledgeable about national malaria trends, determine the main factors related to the objective that you want to better understand. It is helpful to conduct a search for peer-reviewed published articles and papers written on behaviors, beliefs, and attitudes towards malaria in your country to ensure your research questions are not duplicative and are driven by existing data of what is already known. Consider the following:

  • Which factors influence the target population’s practice of malaria-related behaviors?
  • Among members of the target population, what are the characteristics of the individuals who are most likely to practice the priority malaria-related behavior?  What are the characteristics of the individuals who are least likely to practice the priority malaria-related behavior?
  • How can the factors that influence the target population’s practice of the priority malaria-related behavior be addressed through SBC interventions?
  • What is the likelihood that a member of the target population will adopt the practice of the priority malaria-related behavior?

Research questions should primarily be behavioral and will act as the outcome variables for your analysis. Examples of research questions from the case study presented in this course are listed in the next lesson under Key Questions & Analysis.

Step 5. Select a Dataset


To conduct an audience segmentation using quantitative techniques, a survey dataset is required. At baseline, this dataset should have the following parameters:

  • Come from a fairly recent survey, administered in the last 1-10 years, with a representative sample of the target population.
  • Report data for each survey respondent individually, not in aggregate.
  • Contain data on the factors that influence the practice of the priority malaria-related behavior among members of the target population.
  • Contain data on individuals in the specific population identified in step 2 (i.e., age, gender, occupation, etc.).
  • Contain variables that can be used as proxies for the outcome variables identified in step 4.

Because segmentation is intended to describe segments and identify the drivers or influencers of behavior, your chosen dataset should also contain variables that are related to the outcome variables you identified in step 4. The boxes below contain examples of variables that your chosen dataset may include. Each type of variable has a different purpose for your audience segmentation dataset.

Demographic Factors

Characteristics of a population that have been categorized by distinct criteria, typically a vital or social measure.

Behavioral Factors

The way in which someone behaves towards the identified objective.

Attitudinal Factors

A way of thinking or feeling about someone or something, that is sometimes reflected in a person’s behavior.

For malaria, high quality datasets such as the Malaria Behavior Survey (MBS) or health facility survey datasets can be used. Both of which were utilized for the case study presented in this course. You may also consider exploring the Demographic & Health Surveys (DHS) datasets to see if they would work for your audience segmentation.

Types of variables that may be present in datasets

Demographic

Use case

Best for simple segmentation or when combined with other variables as an additional descriptor.

Example characteristics

Age, location, gender, religion, number of children, rural/urban, literacy/numeracy, socio-economic status, household income, level of education, employment status or type, health history/risk factors, marriage status, etc.

Behavioral

Use case

Helpful for determining group actions and behaviors. Best when combined with attitudinal variables.

Example characteristics

Seeks information regarding diseases through specific channels, uses social media, goes to health center for illness or for preventive treatment, seeks care with traditional practitioners, involved in community activities, uses certain tools or methods (e.g., bed nets, diagnostics), etc.

Attitudinal

Use case

Use when trying to understand rationale for behaviors. Best when combined with behavioral variables.

Example characteristics

Trust in authority (government, health institutions, health care professionals) and perceived: access to resources, safety or effectiveness of treatment, consequences of disease, social norms (e.g., believes others practice certain health behaviors or not), role of fate/divine will, etc.

Step 6. Define Segments


At this point, it is time to analyze the data and define the segments. Quantitative segmentation analysis occurs in a 4-step process. Click each step to learn more about the process. It may be helpful to partner with your national statistical institute or a research firm to conduct these analyses.

1. Identify factors that are the main influencers or drivers of the research questions.

Step 1

Run a Chi-squared correlation analysis to identify which variables showed a strong correlation with your research questions.  This will identify the key drivers of the behaviors described by your research questions. These key drivers will be your primary covariates in the analysis.

2. Conduct a quantitative segmentation analysis and identify opportunities for positive behavior change​.

Step 2

Analyze the entire dataset using one of the standard statistical methods for segmentation, which include cluster analysis and latent class analysis. These techniques help identify commonalities and trends among groups based on the variables in the data and selected outcome variables. This analysis will produce different options of segments in your dataset.

3. Review each segmentation model and determine the final model.

Step 3

Review model results of the segments identified in your dataset. Use the Bayesian information Criterion (BiC) indicator, to determine which models are statistically significant, with a lower BiC indicating a better model. Additionally, try and aim for a model with three to six segments. Finally, consider other factors to choose the best model:

  • How do the outcome variables and drivers of the outcome variables differ between various groups?
  • Does each group have clear differences or are the differences barely noticeable between some of the groups?
  • Does the model tell a strong story about different groups within the population and their attitudes, behaviors, and beliefs around malaria?
4. Write a segment “persona” for each segment in the final model.

Step 4

Once a viable segmentation has been chosen, write a “persona” for each segment that describes the key distinguishing characteristics of the segment identified in analysis. Choose a name for each segment as well. The descriptive personas should be brief and easily digestible for dissemination and feedback. It primarily describes the segment in terms of the outcome variables and/or drivers of outcome variables.

Step 7. Refine Your Segments


The segments identified through quantitative analysis can be further refined using qualitative data collection and by speaking directly with individuals from each segment to gather additional information about the factors that shape the behaviors most characteristic of their segments.

Segment Identification Questionnaire

First, use a segment identification questionnaire to determine how to categorize individuals in the target population into the different segments. This will enable you to recruit individuals to participate in interviews, focus groups, or workshops for their segment.

A segment identification questionnaire can be developed using a Chi-squared automatic interaction detector (CHAID) algorithm in the R Studio or SPSS programs. This algorithm considers each variable used in the segmentation analysis as well as the final determined segments and identifies the variables that were most influential in forming the segments. This set of statistically significant variables may be asked in a brief, ordered quiz to members of the target population to determine which segment they can be categorized as.

Complementary Qualitative Research

Finally, conduct qualitative research with members of each segment to develop a more comprehensive understanding of their behavioral drivers. Using the segment identification tool, invite members of the target population to participate in segment-specific focus groups or one-on-one interviews about behaviors and attitudes surrounding the identified objective. Consider partnering with a local research firm to recruit participants, facilitate the interviews or focus groups, and analyze the findings. Aim to have 5-15 research participants for each segment.

Segmentation of Pregnant Women at Risk of Malaria

Now, let us put segmentation steps 1-7 into practice with the case study in the next lesson.

Click the “Mark Complete” button to proceed.

Posttest: Audience Segmentation for Malaria

Thank you for completing Sessions 1-3. Please take a brief posttest, so we can see what you have learned in Audience Segmentation for Malaria. Click the Final Assessment link, below, to get started.

Why Segmentation Matters for Malaria

Why Segmentation Matters for Malaria

Session 1

The purpose of this session is to audience segmentation and begin to describe how audience segmentation can be used in social and behavior change (SBC) for malaria. This session describes the potential utility of audience segmentation to improve malaria outcomes.


Learning Objectives

Define segmentation, demonstrate different types of segmentation, and provide a high-level overview of the steps to create a segmentation.

Describe how segmentation can be used to inform SBC programming.

Malaria and the Role of SBC


According to WHO’s World malaria report 2021, there were an estimated 241 million malaria cases and 627,000 malaria deaths worldwide in 2020. This represents about 14 million more cases in 2020 compared to 2019, and 69,000 more deaths. Approximately two thirds of these additional deaths (47,000) were linked to disruptions in the provision of malaria prevention, diagnosis, and treatment during the pandemic. Malaria burden was heaviest in the WHO African Region, with an estimated 95% of cases and 96% of deaths; 80% of all deaths in this region are among children aged under 5 years (WHO, 2022).

Death rate from malaria, 2020

Map showing global deaths due to malaria per 100,000 persons.
Figure 1. Global deaths due to malaria per 100,000 persons

The imperative to focus on malaria is clear, and in the past years, substantive investments in malaria programs, surveillance, and research have made great strides in the fight against the disease. Since 2000, there has been a 60% decrease in malaria mortality globally (RBM Partnership, 2017). However, funding remains insufficient and further work is needed. To quote Dr Tedros Adhanom Ghebreyesus, Director General of the WHO, “We face many challenges, but there are many reasons for hope. By strengthening the response, understanding and mitigating the risks, building resilience and accelerating research, there is every reason to dream of a malaria-free future.”

While malaria programming can be strengthened at a systems level, human behavior plays a critical role in its prevention, control, and elimination. SBC initiatives can address the barriers and facilitators of malaria-related behaviors such as sleeping under an insecticide treated net (ITN) and taking preventative malaria treatment during pregnancy. Coalitions such as the RBM Partnership to End Malaria understand that evidence-based SBC interventions are a vital part of disease prevention and treatment, and must be integrated into malaria strategic plans to significantly improve behaviors.

To develop more targeted and effective SBC interventions, audience segmentation can be used to uncover the underlying attitudes and beliefs among population groups with regards to malaria-related behaviors.

In considering how to use audience segmentation findings to inform SBC and service delivery interventions, it is also important to take a systems approach and think about each interrelated component within a system that influences social and individual-level behavior change. The malaria service ecosystem model defines six interrelated, embedded components of a system: client, provider, facility level, community level, district/regional/national and the international level.

What is Segmentation?


According to the Advanced Audience Segmentation for Social and Behavior Change How-to Guide, “segmentation divides a population or market into subgroups that have, or are perceived to have, meaningfully similar characteristics, and significant differences from other subgroups.” Figure 2 is a simple illustration of how segmentation can help us to understand a heterogenous population by organizing them into subgroups based on various factors and commonalities. In this illustrative example, they are grouped by colors; however, an audience segmentation for malaria might include segments focused on the practice of prevention behaviors in pregnant women at risk of malaria, as highlighted in the case study presented in Session 2.

Graphic showing target population sorted into segments
Figure 2. Visual representation of segmentation

Segmentation allows for a nuanced look at a population and a deep understanding of what holds value for each group. This in-depth understanding can help stakeholders, such as national malaria programs, community-based organizations, faith-based organizations, service delivery partners, private sector partners, and other implementing partners develop targeted SBC interventions and/or improve service delivery for every segment, to increase the adoption of positive health behaviors.

Below are definitions for two terms that will arise throughout the rest of this course

Types of Audience Segmentation


There are several types of audience segmentation: psychosocial, behavioral, psychographic, attributional, and demographic. Each type uses a different set of information to group a population into segments.

Psychosocial (needs, behaviors & attitudes)

Segmentation that identifies sub-groups within a population with different needs, attitudes, and willingness to change behavior. (optimal segmentation)

Behavioral

Segmentation based on observable behavior, such as consumer activity or media use. This segmentation often relies on self-reported or observed behaviors related to the outcome variables.

Psychographic

Segmentation based on broad attitudes or personality traits, such as introversion or values. Psychographic segmentation provides insights into the intrinsic drivers of behaviors (the why of one behavior).

Attributional

Segmentation based on a single attribute, such as life-stage, or property status. Single attribute segmentation can be based on variables beyond demographics, thus providing more interpersonal insights than demographic segmentation.

Demographic

Segmentation based on a census or demographic factor, such as gender, urban/rural, or age.


As illustrated in Figure 3, the simplest and most common method is demographic segmentation, which uses demographic data to create segments with different age groups, genders, or geographies. However, while individuals may be of the same demographic group, they likely still have significant differences requiring unique SBC approaches.

A more advanced audience segmentation method will be based on psychographic and behavioral variables (i.e., attitudes, beliefs, needs*, behaviors) but will typically require more in-depth research to create the segments, which in turn can provide important insight into those segments’ potential for behavior change.

*Needs is related to individual willingness to access a specific service, product, or reported unmet need by the individuals in the audience.

Segmentation types organized by depth of research methods needed and impact on behavior. Greatest to least: psychosocial, behavioral, psychographic, attributional, demographic.
Figure 3. Segmentation types organized by depth of research methods needed and impact on behavior

In particular, a psychosocial segmentation (focusing on needs, behaviors, and attitudes) maximizes the opportunity for successful SBC and service delivery interventions. This type of segmentation can be used to understand the unique individual, social, and structural factors that influence the practice of the key behavior by members of the segment. Knowledge of the behavioral drivers that influence each segment can be leveraged to develop more tailored and effective SBC interventions for each segment.

To provide a very simple example of how this type of segmentation might show up in data, consider the following table with hypothetical data. (Note that steps to conducting a segmentation will be covered in more detail in Session 2, this is meant to provide an illustrative example.)

 Performs positive health behavior (N=500)Does NOT perform positive health behavior (N=500)
Women who believe X85%5%
Women who believe Y5%85%
Women influenced by Z90%10%
Table 1. Hypothetical illustrative example of analyzing data for segmentation

Based on the table above, we can see that women who “believe X” are significantly more likely to perform the positive health behavior. Women who “believe Y” are statistically more likely NOT to perform the positive health behavior and are less likely to be “influenced by Z”. Given the large sample size (N=500) for each column, these differences are statistically significant (meaning not due to chance).

In the case of malaria, what this might look like is women who believe that malaria presents a high risk to their health (women who believe X) are more likely to take IPTp, whereas women who believe that most women in their community do not take IPTp (women who believe Y) are less likely to take it. And that women who trust health care providers for health information (women influenced by Z) are more likely to take IPTp. This is hypothetical data, but this example starts to lay out how analysis of data might lead to some initial hypotheses regarding segmentation.

Overview of steps to create a segmentation


According to the Social and Behavior Change (SBC) Flow Chart, designed by Breakthrough ACTION, there are three main phases to developing effective SBC interventions while engaging end-users and stakeholders.

Phase 1 Define: Mine existing knowledge, Intent statement, Deepen understanding; Phase 2 Design & Test: Imagine, Refine, Prototype, Test; Phase 3 Apply: Implement & Monitor, Evaluate & Refine, Adapt & Scale
Figure 4. SBC Flow Chart

The steps for conducting a new audience segmentation can follow this phased structure to ensure a meaningful and thorough co-creation process. The following table provides more detail on these phases. The steps for audience segmentation will act as an outline for this session.

DescriptionAudience Segmentation Steps
Phase 1: Define and understand the problemThis phase assesses the findings and insights that already exist and establishes mechanisms to deepen understanding of the problem. This is accomplished by establishing relationships with those familiar with the subject of interest with whom to work with and uncover new perspectives and insights to guide solutions.​1. Identify the priority behaviors
2. Define the target population
3. Enlist key stakeholders
4. Develop research questions
5. Select a dataset
6. Define segments
7. Refine your segments
Phase 2: Design and test potential solutions and conceptsGrounded in deeper understanding, this phase informs how social and behavior change will be addressed by involving end users in the solution ideation process.  8. Develop intervention elements
Phase 3: Apply successful prototypes as activities or interventionsOnce testing feedback has been synthesized into a prioritized suite of solutions, this phase marks their progressive implementation and evaluation.9. Pilot solution
10. Evaluate & Refine
11. Adapt & Scale
Table 2. SBC Flowchart phases and corresponding steps for audience segmentation

We will cover these steps in greater detail in Session 2.

Leveraging Audience Segmentation


There are a number of ways that segmentation findings can be incorporated into the design of SBC interventions. Tailoring each aspect of an SBC intervention to the segment of interest can aid strategic resourcing for malaria initiatives, helping to minimize redundancies and reduce inefficiencies in SBC project design for maximum impact when limited resources are available.

Segmentation findings can be used in malaria programs to:

  • Improve understanding of segment’s experiences, desires, concerns, and behaviors
  • Identify and estimate the potential for behavior change among a specific segment
  • Predict the most promising opportunities for behavior change
  • Tailor services, products, and interactions to specific groups
  • Shape efforts to effectively create a conducive environment and drive awareness, engagement, and mobilization of the positive behavior change
  • Identify key influencers

As noted above, segmentation findings can be used to determine which segments to prioritize. It may not always be feasible or necessary for a program to engage all segments; there may be situations in which a subset of the segments is strategically selected to optimally reach the program’s objectives. In deciding which population segments to focus efforts on, one may consider the following: size, ease of access, likelihood to change, and potential impact. Flip each card to learn more.

Size

Size of the segment

Ease of Access

Ease of access to reach the segments

Likelihood to Change

Segments with the greatest likelihood to change their behavior

Potential Impact

Segments with the greatest potential impact related to the outcome of interest

In this way, SBC programs can deliver highly tailored and targeted interventions that will best support audience segments to engage in the recommended behaviors.

The next session of this course presents an audience segmentation for malaria programming based on data from Cameroon, Côte d’Ivoire, and Malawi (Case study: Pregnant women at risk of malaria). The third session then describes how malaria SBC programming can be informed by audience segmentation.

Key Takeaways

Malaria is a major cause of mortality and morbidity in endemic countries. SBC programming can help to reduce this burden by understanding and addressing the human behavior, gender, and social and structural factors that intersect to create both barriers and opportunities for malaria prevention, control, and elimination.

Segmentation is a way to divide a population into groups with similar characteristics. It can be used to develop more informed, tailored SBC and service delivery interventions.

Psychosocial segmentation is a powerful methodology for understanding and encouraging positive behavior change because it helps us to understand the many factors that shape behavior.

Audience segmentation can be leveraged in designing SBC interventions and in determining what segments to prioritize for programming when resources are limited.

Check Your Understanding

Thank you for completing the first session of Audience Segmentation for Malaria. Next is an ungraded quiz to test your understanding of Session 1. Click the Knowledge Check button to get started.