Social Impact Measurement Toolkit CEB

Social Impact Measurement Toolkit

A practical guide for Microfinance Providers in Europe

An interactive guide to help microfinance providers improve social impact measurement and management

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Welcome to the Social Impact Measurement Toolkit

The Social Impact Measurement Toolkit is the result of a collaboration between the Council of Europe Development Bank (CEB) and M-Pensa Impact & Development Services. It was developed to support Microfinance Providers (MFPs) in Europe in strengthening their capacity to measure, manage, and report on social outcomes and impact in a practical and actionable way. The toolkit is grounded not only in solid theoretical frameworks, but, more importantly, on the voices and experiences of institutions and practitioners who are committed to making financial services more inclusive and impactful. This is not a one-size-fits-all manual. Rather, it offers a step-by-step guide with multiple entry points, allowing users to navigate the process of understanding, collecting, analysing, and using social outcome and impact data in a way that fits their own institutional context. We hope you find the toolkit useful and relevant to your work. Your feedback is important and will help us continue improving it over time. Please feel free to share your thoughts or suggestions with us at ceb-it-com@coebank.org.

Navigation Guide

How the toolkit was developed

About the toolkit

Why this toolkit? Measuring impact is no longer just a reporting requirement, but is essential for:

• Demonstrating value to funders and partners
• Improving service quality
• Strengthening institutional learning and strategic decision-making

MFPs face challenges in measuring impact, including limited resources, inconsistent reporting demands, and lack of clarity about what to measure and how. Some also see impact assessment as too complex or costly, or fear uncovering disappointing results.

The toolkit addresses these barriers through a step-by-step approach grounded in the realities of MFPs in Europe. It draws on peer practices, aligns with international standards and is designed to help MFPs build on existing capacity. The toolkit is intended as a practical resource to generate insights about what works, for whom, and why.

“We need a toolkit that speaks the language of practitioners" European Public Institution

Self-assessment: Where to begin

Modules

1. Framing impact in European microfinance

2. Building the basis to measure social impact

3. Designing a measurement system

4. Using impact data for accountability and learning

5. Innovation: the role of machine learning and AI

01

Framing impact in European microfinance

01

Framing impact in European microfinance

Module explores how European microfinance providers define, measure, and use social impact in their work. It begins by identifying the key social impacts that matter most in the European context. The module then highlights why defining impact at the institutional level is essential, ensuring that mission, strategy, and operations remain aligned and meaningful. Finally it looks at how institutions turn outcome and impact data into practical tools—shaping the way they serve clients, design financial products, train staff, and build trust with stakeholders.

What is Impact in microfinance?

In microfinance, impact refers to the longer-term and meaningful changes resulting from financial and non-financial interventions. Not simply the delivery of services and products, but the improvement they generate in the lives of individuals and communities.Financial and non-financial services provided by an MFP can lead to immediate outputs, short- to medium-term outcomes, and long-term impact. Understanding the diffference between these levels helps MFPs to:

Avoid “impact-washing” through actual effects, not just intentions

Track progress at multiple levels (operational, client , strategic)

Communicate clearly with funders and other stakeholders

Set realistic targets and timelines for change

Outputs, outcomes, and impact

How to differentiate them?

Outputs, outcomes, and impact

Why the distinction matters?

Whether: identifies who benefits or does not from microfinance services and to what extent. How: explores pathways and mechanisms that lead to the observed changes, whether intended or unintended, positive or negative.

The distinction between outcomes and impacts is not always clear-cut as observed changes can be either outcomes or impacts, depending on timeframe, context, and evidence available. What distinguishes impact is the notion of causality, or at least plausible attribution, to the microfinance intervention. Impact measurement aims to understand social and economic changes on intended beneficiaries and capture whether and how microfinance contributes to broader development objectives over time.

Guiding question for MFPs: “How can financial products and services meaningfully contribute to lasting changes in the lives of clients?”

What are the key social impacts?

In Europe microfinance supports employment, promotes social inclusion, and enables entrepreneurship among vulnerable or underserved populations. MFPs in Europe frequently work with migrants, long-term unemployed individuals, youth, people with disabilities, and others who face systemic barriers to economic participation.

“Outside Europe, microfinance is seen more as a poverty-alleviation tool. In Europe, it’s about employment, integration, and entrepreneurship.” European Public Institution

The CEB, European Investment Fund (EIF), and European Investment Bank (EIB) also highlight alignment with broader public policy objectives—such as gender equality, green transition, and digital inclusion—as key components of impact.

Why is it important to define impact?

There is no universal definition of impact.Impact should be defined by MFPs based on institution- and context-specific characteristics:

• Social and economic characteristics of the market where the institution operates

• The institution’s mission and values
• The characteristics and needs of its target groups
• The institution’s medium-to-long-term strategic priorities

Impact-path hypotheses differ across institutions

Guiding question for MFPs: "What are the critical problems and barriers that clients face that prevent them from achieving full inclusion in the social, economic, or financial system?"

The social and economic context often shapes all other elements of a microfinance institution’s approach

Making impact measurement useful

Framing impact as a tool for learning and decision-making makes it more valuable to MFPs. Several MFPs in Europe have shown that a clear, operational definition of impact can inform day-to-day management and long-term strategy, and help institutions to:

Train staff to prioritize client success

Strengthen relationships with stakeholders

Support strategic decisions

Refine products and services

Identify service gaps

Making impact measurement useful

Several European MFPs use outcome and impact data to inform how they serve clients, design products, train staff, and engage with stakeholders. Click on each icon to learn more:

02

Building the basis to measure social impact

02

Building the basis to measure social impact

A robust impact measurement system starts with a clear foundation—an explicit articulation of what impact means for the institution, how it is expected to occur, and what is required to track progress. This section introduces the essential building blocks: Theory of Change, the logical framework, and a set of indicators that capture activities and expected results, aligned with international standards.

Building or reviewing a Theory of Change

Developing a Theory of Change builds directly on the guiding question in Module 1. A Theory of Change translates identified challenges into a structured framework that explains how an institution’s services are expected to respond and contribute to meaningful change.:

• Is a visual or narrative model that outlines the steps, activities and services that MFPs deliver in order to bring about positive change to their customers.

• Identifies the resources and the role of actors required to enable change.

• Helps institutions assess which interventions are most appropriate by considering comparative advantages, feasibility, effectiveness, and the uncertainties that are part of any change process.

• Makes explicit the underlying assumptions and risks that must be recognised and revisited over time to ensure that the approach contributes to the desired impact.

There is no single correct way to develop a Theory of Change. The process can be tailored to each MFP's specific context, products and services.

Elements of a Theory of Change

A Theory of Change provides a roadmap for understanding the underlying logic and assumptions that guide the design, implementation, and evaluation of financial and non-financial products and services. MFPs identify a problem or a need for specific segments, and based on that they develop their mission and design their services and products to address the problem. In this respect, the following are key questions to answer:

Activities, services and products

Short/medium term outcomes

Mission

Expected outputs

Long-term impact

Target population

Problem statement

Assumptions

Elements of a Theory of Change

Answering the questions in the previous slide is important to build the elements of a Theory of Change.

Intermediate outcomes

Inputs

Outcomes

Impact

Outputs

Activities

Assumptions

Practical tips for a strong Theory of Change

Design

Communication and Learning

Foundations

Map causal pathways

Create a visual representation

Use available evidence

Identify assumptions and risks

Engage stakeholders

Write a narrative of the Theory of Change

Be realistic and consider feasibility

Define long-term goals

Foster a learning culture

Be specific about activities

Example of a Theory of Change

Problem statement: Migrant populations often face significant barriers to economic participation and legal stability, including lack of access to finance, limited legal protection, and inadequate livelihood opportunities, which together hinder their long-term integration into host communities. Causal pathway:

Intermediate Outcomes

Inputs and Outputs

Outcomes

Assumptions

Activities

Impact

Developing a logical framework or logframe

Once a Theory of Change has been established, the next step is to translate it into a measurable structure, which involves answering two key questions:

• How can it be verified that the planned activities, outputs, outcomes, and impacts are being achieved?
• How can the Theory of Change be expressed in a format that allows systematic monitoring and reporting?

The logical framework, or logframe, is a planning and management tool that converts the narrative of the Theory of Change into a concise and measurable format. A logframe summarises the project’s objectives, activities, outputs, outcomes, and impacts in a clear matrix, making it easier to track progress, identify risks, and demonstrate results. While the Theory of Change explains how and why change is expected to occur, the logframe sets out how that change will be measured and managed over time.

What can the tool be used for?

What should be kept in mind when developing a logframe?

Elements of a logframe

A logframe typically includes the following elements:

• Overall objective (goal): a concise statement of the intended long-term impact or desired change. It reflects the overarching purpose aligned with the organisation's mission.
• Outcomes (specific objectives): statements of the intermediate results or outcomes that directly contribute to achieving the overall objective.
• Outputs: tangible and measurable products, services, or deliverables that result directly from activities.
• Activities: All the interventions, or actions carried out to produce the desired outputs.

Means of verification

Indicators

Risk mitigation strategies

Timeframe

Responsibilities

Assumptions

Practical tips to develop a strong logframe

Use SMART indicators

A strong logframe is an iterative process that requires collaboration, consideration of context, and ongoing refinement. These tips support the development of a robust logframe that serves as a powerful tool for planning, implementation, and evaluation.

Link activities to outputs and outcomes

Address assumptions and risks

Watch this video!

Engage stakeholders

03

Designing a measurement system and selecting relevant international frameworks

03

Designing a measurement system and selecting relevant international frameworks

Building on the Theory of Change and logical framework developed in the previous section, the next step is to design a measurement system that translates institutional priorities into practice. This process involves defining a clear set of indicators to track progress, balancing quantitative and qualitative approaches, and identifying suitable data collection methods. This module provides guidance on how to choose meaningful and feasible indicators, align them with international standards, and make effective use of existing data sources.

Selecting indicators

Indicators are central to impact measurement. They convert a Theory of Change and logframe into practical tools to monitor progress, evaluate success, and communicate results. A well-structured set of indicators helps track whether microfinance activities, outputs, outcomes, and impacts are being achieved as planned.As mentioned in Module 1, in microfinance, the line between outcomes and impacts can be blurred, i.e., creating stable jobs for migrants may be both an outcome and a meaningful impact. Flexibility should be considered when selecting indicators, as outcome-level changes often best capture the transformative results the organisation seeks, and they are generally easier to measure than impacts.

Start with a small and focused set of indicators that is both manageable and meaningful. Prioritizing quality over quantity will help ensure that a measurement system supports learning, decision-making, and strategic communication.

Selecting indicators

Well-chosen indicators should meet the following criteria:

Aligned with mission and Theory of Change

Able to capture also client perception

Understandable to key stakeholders

Feasible to collect and analyse

Easy to communicate to the general public

Selecting indicators

When defining your indicators, consider the following:

1. Which specific changes are intended to be measured, and at which level—activity, output, outcome, or impact?
2. How can it be determined whether those changes have occurred, and what measurable evidence would indicate success?
3. Who is affected? Are the indicators disaggregated by relevant groups (e.g., women, migrants, MSMEs)?
4. Are the indicators Specific, Measurable, Achievable, Relevant and Time-bound (SMART)?

Examples of types of indicators that can be used across different levels of a ToC.

Practical tips for defining indicators

Below, find practical considerations for defining indicators:

Combine qualitative and quantitative indicators

Disaggregate indicators

Align with international frameworks

Alignment with global standards

Over the years, numerous international initiatives have emerged to support financial and non-financial organizations in shaping their impact assessment strategies. Aligning an MFP's impact measurement and indicators with global standards is relevant because it adds comparability and a degree of standardisation in the approach to measuring impact. MFPs in Europe can draw on a variety of European and global frameworks that offer guidance on how to define, measure, and track impact in a consistent and meaningful way. Click on each framework/tool to learn more:

Alingment with global standards

These frameworks can support European MFPs in designing more effective and credible impact assessment strategies. An MFP can use the CERISE+SPTF client questionnaires to collect outcome data on financial resilience and satisfaction, align its indicators with the European code of good conduct for microcredit provision and IRIS+ for reporting to policy makers and investors, and map key results to relevant SDGs for communication with public funders. Meanwhile, HIPSO indicators can guide institutions working with DFIs to ensure data comparability, and the Operating Principles for Impact Management (OPIM) can help align internal processes with the expectations of impact investors. For smaller MFPs, the key is not to adopt all frameworks, but to identify where alignment is useful and feasible. For example, a basic outcome like “increased household income” can be reported using an IRIS+ indicator or mapped to SDG 1 (No Poverty).

Indicator Menu (based on European Code of Good Conduct for Microcredit Provision, SPTF, IRIS+, and practices from European MFPs)

“It’s not about building the perfect framework—it’s about building one that fits your mission and capacity.”

- Microfinance Provider

Alignment with EU's strategic priorities

This section proposes a basic set of outcome and impact indicators that are closely aligned with the European Union’s strategic priorities for inclusive and sustainable development. They reflect the multidimensional nature of social and financial exclusion, as defined in the European Pillar of Social Rights, which emphasizes access to employment, adequate income, healthcare, housing, and essential services as fundamental rights. Indicators on employment, income stability, and access to financial products align with Eurostat and Social Protection Committee metrics. Business indicators such as revenue growth, job creation, and access to support services reflect the EU’s SME strategy and Cohesion Policy, with a focus on vulnerable groups like migrants, women, and youth. Metrics on healthcare, housing, and emergency funds echo the ESF+ priority of reducing deprivation. Tracking these indicators helps microfinance providers assess effectiveness, align with EU funding priorities, support national inclusion strategies, and access public mechanisms.

Set of outcome and impact indicators aligned with the European Union’s strategic priorities

Quantitative vs. qualitative indicators

While quantitative indicators capture measurable numerical values—such as income, earnings, or number of jobs—qualitative indicators provide information about attributes or perceptions that are not directly measurable, or assessed using scales, such as client satisfaction, or empowerment. Quantitative indicators are usually easier to collect and measure than qualitative indicators. However qualitative indicators can be critical for the following reasons:

“Quantitative data has its place,but without narrative and context, you don’t understand why change happens. That’s what matters.” - European Academic

For example, two years after receiving their first loan, your business clients may have created an average of two jobs. However, without exploring the underlying drivers, it remains unclear how this happened.

Most of impacts are not quantifiable

Clients satisfaction provides insight

Only qualitative data help explain why

Mapping existing data sources

Client transaction and interaction data

Client onboarding data

“A lot of useful information is already there—you just need to look at it differently.” - European Microfinance Provider

Before launching new data collection efforts to build indicators, an institution should start by identifying and evaluating the secondary data already available. By mapping what is already available, the institution can make smarter decisions about what new data is truly needed, reduce reporting fatigue, and ensure that the impact measurement system is grounded in the MFP's actual operations. While these sources can provide most of the quantitative, and to some extent also qualitative indicators, they might say little about “why” outcomes or impacts occurred. Please refer to the “Quantitative vs. Qualitative Indicators” section for more information.

Recurring client-reported data

Routine client feedback and satisfaction surveys

Public registries

National and regional statistics for benchmarking

Practical steps for mapping data

List all data touch points across the client lifecycle

Consult key staff

Create a data inventory table

Evaluate external data options

Review past reports and forms

Prioritize high-value, low-cost data

Building on what is already available

Once the institution has completed the mapping of available data sources, and has built a data inventory table, encompassing both actual and potential data from existing internal and external sources, the next step is to build a measurement system around the existing strengths and identify priority gaps that require new data collection.

Decide what to adapt, drop or formalize

Classify data by type of indicator and purpose

Plan for new data collection—Only where needed

Assess data quality and gaps

Data mapping template

Data collection - surveys

As outlined in earlier sections, mapping internal and external data sources and compiling a data inventory table helps identify which data is already being collected and which data is missing to track desired outcome and impact indicators. Quantitative surveys should only be used to fill gaps with measurable data that cannot be gathered through existing systems.

Sampling and representation

Quantitative surveys rely on sample-based data collection to generate statistics that are representative of the MFP's client base or subgroups of interest.

How to avoid biased data

How to ensure data is useful

Some institutions choose to administer surveys to their entire client base in order to maximize the number of responses, which can be a cost-effective approach, especially when using digital tools like SMS, email, or mobile apps. However, response rates are typically low, often ranging between 10% and 20%, particularly if the survey is not incentivized or requires significant time from the respondent. In these cases, it is also crucial to assess the representativeness of the responses received. A low response rate can introduce bias if certain client groups (e.g., more educated, digitally connected, or financially stable clients) are more likely to respond than others.

Ultimately, even with lower response rates, broad outreach can generate useful insights, provided that attention is paid to the diversity and balance of the responding sample.

Survey administration (How and Who)

Quantitative surveys can be conducted via phone calls (especially for short or follow-up surveys), face-to-face interviews (during loan disbursement, renewal, or site visits), digital surveys via mobile forms or email (if clients are digitally literate). It is common practice among several MFPs to use multiple channels for conducting client surveys in order to increase reach and improve response rates. These channels may include:

• In-person surveys during regular visits by loan officers
• Online surveys sent via email or shared through client portals or institutional websites
• Telephone interviews for clients conducted by external market research companies or academic research centres.

The collaboration with external market research companies or academic research centres can ensure a minimum sample size is achieved and to lend credibility and rigor to the process. External partners can assist with:

• Survey design and testing to reduce bias and improve clarity
• Sample selection and stratification to ensure key client groups (e.g., by gender, region, product type) are adequately represented
• Monitoring of response rates and identification of any underrepresented segments
• Follow-up strategies—such as reminders or targeted outreach—to improve sample balance and reliability
• Data cleaning and analysis to support meaningful interpretation

Survey design: Length and content

Quantitative surveys should be:

• Short and focused—typically no more than 10–15 minutes.
• Focused on essential indicators that are not already captured through other data sources, or to validate key outcome or impact indicators, for instance, to confirm whether business revenues have increased or if the number of employees has grown.
• Designed for efficient data entry and analysis (using numeric values, tick boxes, or scales).

Avoid collecting data “just in case”and ask only what is necessary and usable.

Key design principles for survey questions

When designing survey questions to track outcomes or impact, keep your questionnaire practical, focused, and easy to understand. Follow these concrete principles:

Use simple, direct language

Avoid questions that encourage socially desirable answers

Offer opt-out options

Avoid confusing or abstract phrasing

Be specific with timeframes

Balance closed and open-ended questions

Question types

When designing a survey, selecting the right type of question is essential to ensure clarity, relevance, and usability of the data collected. Below are common question types and their practical applications:

Pilot the questionnaire before launching

Before rolling out the survey widely, conduct a small-scale pilot with a sample of 10–15 clients that reflect the diversity of target respondents (e.g., by gender, age, sector, or region). This step is essential to:

• Identify ambiguous or confusing questions
• Assess the length and flow of the questionnaire
• Test how well the survey format works across different channels (e.g., phone, digital, in-person).

Collect feedback from both respondents and survey administrators about any difficulties encountered. Use the insights to revise wording, remove redundant items, or adjust response options.

A well-conducted pilot ensures higher data quality, better response rates, and smoother implementation.

Integration into the CRM system

Many survey platforms can be seamlessly integrated into your Customer Relationship Management (CRM) or Management Information System (MIS), enabling more efficient and automated data collection. Tools such as KoboToolbox, Google Forms, and SurveyMonkey offer APIs and plug-ins that allow you to link surveys directly to client records, track responses in real-time, and automate distribution based on specific client actions (e.g., loan disbursement, renewal, or product review). Tap the icons to access these tools:

Surveys can be triggered automatically after a loan cycle ends, after a specific time period from the first loan disbursement or after a client attends a training session. Some platforms, like SurveyMonkey, also offer built-in analytics and dashboards to quickly analyze results, monitor completion rates, and assess data quality.

Integrating surveys into the existing systems can save time, reduce duplication, and make it easier to ensure that essential outcome or impact data is collected consistently—without overburdening staff or clients.

Data collection: Client interviews

Client interviews are primarily used to gather qualitative insights into the factors that explain the observed changes—such as increased income, business growth, or improved resilience—and to understand how the services and products contributed to those outcomes or impacts. Client interviews can be conducted every few years and should follow a purposive sampling strategy, in which clients with diverse characteristics and varying types of outcomes and impacts are intentionally selected (e.g., those who improved significantly, those who remained stable, and those who experienced setbacks). A large sample is not required —6 to 8 interviews per cohort or client segment (e.g., by gender or migrant status) can provide valuable, actionable insights if carefully selected and conducted.

Client interviews: Step by step

The following provides step-by-step guidance into conducting clients interviews to understand the “Why” behind outcomes and impacts:

Clear impact hypothesis

Identify contribution

Open-ended questions

Select a sample

Listen for mechanisms

10

Capture contextual factors

Identify the “stories of change”

Triangulate data

Use small samples

Reflect

Example: Client interview by cohort

A microfinance provider in southern Italy offering microloans and business development training to informal entrepreneurs wanted to better understand the outcomes of its services.

To make sense of these results, the MFP conducted in-depth interviews with 24 clients, divided into four cohorts based on gender and migrant status (6 clients per group):

• Migrant women
• Non-migrant women
• Migrant men
• Non-migrant men

The interviews explored business trajectories, challenges faced, and perceptions of the services received. The cohort comparison revealed important differences:

The MFP used these insights to:

• Adapt training modules to better address legal and formalization issues for migrants
• Offer tailored support for women with caregiving responsibilities Communicate more differentiated and realistic impact stories to funders
• Reconsider its targeting and outreach strategies

This cohort-based approach gave the institution a deeper, more nuanced picture of what was driving impact and for whom.

Analysis: Individual client tracking

Individual client analysis focuses on tracking changes in a single client’s outcomes over time—for example, comparing income, employment, or business growth at onboarding, after one year, and after loan renewal. Changes experienced by individual clients can then be analysed across the entire client base (e.g., average or median change) or within specific cohorts. This approach can offer better insights, but also presents some challenges:

• It requires consistent data collection over time, which can be difficult if clients leave the institution early, miss follow-up surveys, or if recordkeeping systems aren’t standardized.
• It works best when the institution has strong case management or CRM systems that allow for regular updates to client profiles.

Despite these limitations, individual-level tracking can be very powerful when done well. It allows institutions to identify specific success stories, troubleshoot why some clients do not improve, and tailor services more precisely. It is especially useful for in-depth case studies or to validate findings from broader cohort-level analysis.

Analysis: Cohort tracking

Cohort tracking involves comparing, over time, groups of clients who share similar characteristics, such as demographics, geographic location, type of service received, or length of time with the institution. It offers several advantages:

• Tracking individual clients over time is often difficult, especially if they remain with the institution for only a few years or do not consistently participate in data collection activities. Cohort-level comparisons allow for meaningful analysis even when individual tracking is limited.
• Client characteristics play a key role in shaping outcomes and impacts. By analysing results across different cohorts (e.g., migrants vs. non-migrants, men vs. women), institutions can better understand which groups benefit most from specific services and why.

Cohort tracking can also be particularly useful when individual clients change over time (e.g., some drop out, new ones enter), but the group characteristics remain consistent allowing the institution to still observe trends and patterns across stable cohorts. For example, the institution can compare how average income or business profits change over time among female-headed migrant households or young men entrepreneurs, even if the specific individuals vary.

Individual client tracking and cohort tracking are complementary approaches—they don’t exclude each other. Cohort comparison can be used both cross-sectionally (at one point in time) and longitudinally to track how different cohorts evolve over time.

Creating client cohorts

Creating cohorts means grouping clients who share specific characteristics.By analysing outcomes and impact across these groups, institutions can identify who benefits most, who may be left behind, and how programs can be refined to better meet client needs. Client cohorts for impact data analysis can be formed by combining key output indicators, such as:

• Demographic characteristics (e.g., gender, age, education level, migration status)
• Geographic location (e.g., urban vs. rural, by branch, or by market)
• Service characteristics (e.g., loan size, type of loan, maturity, Business Development Services or training)
• Client tenure (e.g., recently onboarded clients, those with 1 year of history, 2+ years with the institution)

The latter is particularly important, as outcomes such as financial stability, business growth, or resilience often improve gradually. Segmenting clients by how long they have been with the institution allows you to better understand the trajectory of change and the likely timeline for impact. Other characteristics to consider in business lending include the size and sector of the enterprise, provided the business was already established prior to receiving services, as the creation of a new enterprise would otherwise be considered an outcome.

Creating client cohorts

The objective is not statistical precision but practical insight: which client segments are improving, which are stagnating, and how your services might be adapted to better serve them. Analysing data by cohorts also facilitates more targeted storytelling, reporting, and decision-making, linking outcomes back to both client needs and service design. Below is a set of hypothetical client cohorts defined using four key characteristics:

• Migration status (Migrant / Non-migrant)
• Gender (Male / Female)
• Geographic area (Urban, Peri-urban, Rural)
• Business loan combined with Business Development Services (BDS) (With BDS / Without BDS)

Creating client cohorts

To keep things manageable and practical, six distinct cohort examples are provided, illustrating how intersecting client and service characteristics can shape differentiated outcome analysis:

Rural migrant women with BDS

Rural native women without BDS

Urban migrant women without BDS

Urban native men without BDS

Peri-urban migrant men with BDS

Peri-urban native men with BDS

Analysis: Making sense of data

After collecting data—whether through surveys or client interviews—analysis helps uncover patterns, trends, and insights that support both internal learning and external reporting. Below is a practical guide to analysing different types of data, showing how to combine all-client analysis, cohort comparisons, and already collected qualitative evidence to deepen understanding.

Open-Ended

Cardinal / Numeric

Ordinal Scales

Closed-Ended

Yes/No, Multiple Choice

e.g., Satisfaction, Confidence

e.g., income, business revenue

Data can then be triangulated to produce a more comprenhensive analysis

How MFPs in Europe do it in practice

MFPs in Europe apply impact measurement in diverse ways, often combining internal data with client surveys, and aligning results with broader development goals such as the SDGs. Despite differences in size and institutional model, several have developed robust approaches adapted to their mission and client base: Click on each MFP to learn more:

These cases illustrate that even relatively small or specialized MFPs can design and implement impact measurement systems that are strategically aligned, operationally feasible, and responsive to both client realities and stakeholder expectations.

04

Using impact data for accountability and learning

04

Using impact data for accountability and learning

Collecting outcome and impact data is more valuable if it leads to action. This section provides guidance on how to use the data in more meaningful ways, not just for accountability, but for internal learning to strengthen your services and strategic positioning.

“Our impact work gives us legitimacy—not only as a service provider but as a policy actor.” - European Microfinance Provider

Reporting to funders, board and the public

Using impact data is essential for accountability because it provides credible, evidence-based insights into whether the organisation is delivering on its mission and promises:

• For funders and investors, it demonstrates that resources are being used effectively to generate measurable social outcomes.
• For boards, it enables oversight, informed decision-making, and strategic adjustments.
• For the public, including clients and communities, impact data builds trust, transparency, and legitimacy, showing that the organisation’s products and services are not only operational but also making a meaningful difference.

It is important to note that depending on the target audience, a different level of detail will be required:

Boards

Public & clients

Funders & investors

Turning data into institutional learning

Collecting impact data is only meaningful if it drives internal learning and change.

BCR Social Finance in Romania provides a good example. They hold quarterly reviews of their outcome data, looking not only at repayment rates, but also at the success of clients' businesses and employment outcomes. When they see challenges, they discuss them openly and adjust lending criteria or coaching services as needed. This way, outcome data becomes part of how the organisation learns and improves, rather than just a static report. BCR Social Finance also uses business mentoring outcome data to improve support programmes. If survival rates of businesses improve after mentoring, it signals that these services add tangible value and justifies scaling them further. You can learn more about their approach at www.bcrsocialfinance.ro.

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Data for improved products and services

Outcome data is a powerful tool to assess whether the products and services are truly meeting the needs of clients. When MFPs track not just outputs like the number of loans disbursed, but real-life outcomes such as improved financial independence or business survival, they can identify product gaps and areas for redesign.

Look at PerMicro in Italy. By monitoring their outcome data, PerMicro realised that women entrepreneurs were experiencing higher repayment difficulties compared to other client groups. Further investigation revealed that these challenges were linked to structural factors such as care responsibilities and unequal access to economic opportunities. In response, PerMicro adjusted their loan products to include more flexible repayment schedules and grace periods, better suited to the realities of their female clients. You can read about PerMicro’s approach at www.permicro.it.

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Data for refining targeting and outreach

Targeting the right groups requires more than assumptions, it requires disaggregated data. By analysing outcomes across different demographics, MFPs can identify gaps in service uptake and adapt outreach efforts to ensure inclusivity.

For example, Qredits in the Netherlands uses client segmentation and outcome data to track which groups are being reached and how they are faring. When data shows that certain groups, such as youth or people in rural areas, face lower success rates or limited access, they adapt their marketing and support strategies accordingly. More on Qredits’ approach is available at www.qredits.com.

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Strenghtening non-financial services with data

While access to finance is essential, non-financial services such as training, mentoring, and advisory support can significantly enhance client success. Outcome data helps demonstrate the value of these services and guides decisions on scaling or adapting them.

In Poland, microfinance providers tracked business survival rates and discovered that clients who received business training and mentoring had a much higher likelihood of keeping their enterprises afloat. This evidence encouraged them to expand these non-financial services, recognising their critical role in supporting sustainable livelihoods. BCR Social Finance in Romania also uses outcome data to measure the effectiveness of business coaching. When data showed improved employment outcomes and business stability among clients who received coaching, the organisation strengthened these support programmes.

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05

Innovations: The role of machine learning and AI in impact assessment

05

Innovations: The role of machine learning and AI in impact assessment

While this toolkit is designed to offer practical, easy-to-implement strategies, it is also important to look ahead. Emerging innovations—particularly Machine Learning (ML) and Artificial Intelligence (AI)—have the potential to significantly transform the way social impact is measured, offering new possibilities for efficiency, accuracy, and insight.

Using ML for impact assessment

How can machine learning contribute to impact assessment practices?

ML can support MFPs by enhancing how impact data is interpreted, used, and even predicted. While full-scale implementation may currently be more feasible for larger or more digitally mature institutions, ML offers several promising applications that could benefit the wider microfinance sector:

Sector stakeholders—including funders and MF associations—are crucial for enabling ML experimentation.

Learn how

Using AI for impact assessment

How can AI contribute to impact assessment practices?

AI goes a step beyond machine learning by enabling the semi-automated analysis of both structured and unstructured data. In the context of social impact measurement, AI can support microfinance providers in several practical and forward-looking ways:

While these technologies offer significant potential, their use in European microfinance is still in early stages.

Learn how

06

Video: plan A Why does social impact measurment matter for the CEB ?

• Assumptions: Migrants face both economic and legal barriers to integration. Financial and legal empowerment reinforce each other leading to better outcomes than isolated intervention. Host communities have the enabling environment to support migrant led businesses and legal processes.

Patria Credit's impact goals

The social and economic context often shapes all other elements of a microfinance institution’s approach. Romania, for example, has the highest number of farmers in the EU—nearly 3.5 million—of whom 90% are smallholders cultivating less than 5 hectares. Patria Credit, a non-bank financial institution (NBFI) in Romania, focuses on financing the agricultural sector, particularly small farms. Its mission is to support the development of the country’s agricultural and rural economy, promoting social and economic inclusion in underserved rural areas.

Peri-Urban Migrant Men with BDS

Male migrants in peri-urban zones who received a business loan and BDS Potential insights to explore: Does access to BDS reduce integration barriers in transition zones (e.g., outskirts of cities)?

Indicators aligned with mission and Theory of Change

Indicators should clearly reflect the outputs, outcomes and impacts identified through your Theory of Change. To enhance the relevance and interpretability of outcome indicators, it is essential that output indicators capture two dimensions:

• Client characteristics
• Service characteristics

Urban Migrant Women without BDS

Female migrants in cities who received a business loan without any accompanying BDS How critical is BDS for newly arrived women entrepreneurs in urban areas?

Tip #7

Be specific about activities

Clearly define the activities or interventions that will be implemented to achieve the desired outcomes. This helps in translating the theory into actionable steps. Ensure that there is no duplication of activities (similar activities mentioned twice). For example, instead of writing “support entrepreneurs,” you might specify: “Conduct monthly group training sessions on financial planning” “Provide one-on-one coaching within 3 months of loan disbursement” It is important to ensure that no activity is repeated or vaguely defined.

Only qualitative data can really help explain why certain outcomes and impacts occurred—that is, to uncover the underlying impact pathway.

Target population

• Who constitutes the institution’s client base?
• What are their social and economic characteristics?

Measures used to assess and quantify the achievement of the corresponding level of the logframe, i.e. outputs, intermediate outcomes, outcomes and impact. See the following examples:

Intermediate outcome level

Impact level

Output level

Outcome level

Urban Native Men without BDS

Definition: Male non-migrants in urban areas who received a business loan but no business support services Potential insights to explore: How do self-reliant male clients perform in a more accessible setting without additional support?

Tip #10

Foster a learning culture

Build mechanisms for learning and adaptation into your ToC. Encourage regular reflection, evaluation, and the use of feedback to adjust strategies as needed. This adaptive approach enhances the programme's effectiveness. For example, a good practice is to include quarterly review meetings with staff to discuss client feedback, repayment trends, and drop-off rates in business support sessions. Insights are used to adjust loan terms or revise training content, supporting continuous improvement.

Use simple, direct language

Avoid technical or financial jargon. Write questions at the reading level of the typical client. Example:

• “Did your income increase in the past 6 months?” instead of “Has your financial situation experienced a positive trend?”

Working with an external partner

Working with an external partner can be particularly useful for first-time efforts or when internal capacity is limited. It also helps ensure that the survey results are representative, actionable, and credible, which is especially important when findings are shared with funders, boards, or public stakeholders.

Step 3: Decide what to adapt, drop or formalize

Following the mapping of data sources, an evaluation should be conducted to assess how each source contributes to the impact measurement system:

• Adapt: Modify existing data collection tools to make them more useful for outcome tracking, i.e. update onboarding forms to include further baseline indicators, or tweak client satisfaction surveys to capture self-reported changes over time.
• Drop: If a data collection effort is redundant, unreliable, or not aligned with objectives, consider discontinuing it.
• Formalize: Standardize the collection of useful data that is currently gathered informally (e.g., field officers noting business changes during visits) through the use of templates or simple digital forms.

Understandable to key stakeholders

Your indicators should be easily interpreted by internal and external stakeholders, including clients, staff, board members, and funders. This fosters ownership of the impact agenda and encourages dialogue around performance and client outcomes and impacts.

• Internal or survey data shows what happened — e.g., 20% average income increase.
• Cohort comparisons show for whom — e.g., highest gains among migrant women, but also higher dropout.
• Qualitative interviews (and some qualitative data from surveys) explain why and how — e.g., growth enabled by mentoring and peer support; dropouts linked to housing instability and caregiving burden.

Triangulate with other data

Cross-check interview insights with existing quantitative data or operational KPIs. Do the themes mentioned align with trends in repayment, dropouts, or follow-up loan uptake?

Analyse outcome stories or contribution narratives

Use the qualitative narratives to identify the “stories of change” that can provide evidence of impact of your products and services, as well as other relevant factors.

• Turn your interviews into short case examples or contribution stories.
• Highlight the pathway (service → response → change), not just the result.

• Monitor who is responding (e.g., by gender, age, business size, loan product) and compare to the overall client base.
• If major gaps exist, consider targeted follow-ups with underrepresented groups to balance the sample.
• Weight the data during analysis, if needed, to correct for response bias—though this requires a solid understanding of client demographics.

• Activities: Deliver small loans, provide legal counseling and case management, conduct entrepreneurship workshops.

PerMicro (Italy)

Making impact measurement useful internally

PerMicro collects annual data on financial autonomy, business sustainability, and access to housing and services. This information is used to guide strategic planning and to demonstrate to public stakeholders the institution’s broader contribution to social welfare—strengthening its legitimacy and access to partnerships. Learn more about PerMicro via their website: https://www.permicro.it/credit-and-microcredit-for-inclusion/

Mission

• What is the institution´s overarching purpose?
• What change does the institution ultimately expect?

How can AI contribute to impact assessment practices?

• Interview transcription and summarization: AI tools (e.g. speech-to-text or transcription services) can convert recorded client interviews into text and generate summaries, saving staff time and increasing consistency—especially when working with large volumes of qualitative data.
• Text and sentiment analysis: AI can analyse open-ended responses, interview transcripts, or client feedback to detect common themes such as satisfaction, trust, empowerment, or wellbeing. Sentiment analysis can help capture emotional tone—especially useful for tracking outcomes that are hard to quantify (e.g., confidence, stress reduction, motivation).
• AI-enhanced qualitative coding: Rather than manually coding interviews line by line, AI tools can now identify and cluster recurring themes. While human oversight remains important, these tools are increasingly replacing traditional qualitative analysis methodologies, allowing for faster, more scalable insights without losing nuance.
• Chatbots and digital feedback loops: AI-powered chatbots or messaging tools can be integrated into client communication channels (e.g., WhatsApp, SMS, email) to collect feedback in a conversational and user-friendly format as well as to conduct virtual surveys and interviews.

Responsibilities: Specification of who is responsible for each activity or component, ensuring accountability and coordination.

Train staff to prioritize client success, encouraging field teams to focus not only on loan disbursement but also on business viability, financial resilience, or long-term inclusion.

Question/Data Type: Closed-Ended (Yes/No, Multiple Choice)

Analysis tools:

• Frequencies: Count how many respondents chose each option.
• Percentages: Show what proportion each response represents (e.g., 52% said “yes”).
• Cross-tabulations: Compare responses across cohorts (e.g., % of migrants vs. non-migrants who hired staff).

Example:

• All clients: 52% of clients report hiring at least one employee post-loan.
• Cohort comparison: 65% of migrant women hired someone, compared to 40% of non-migrant women.
• From client interviews: Many migrant women said the loan allowed them to secure a fixed market stall or buy kitchen equipment, enabling them to hire help. In contrast, non-migrant women mentioned local demand constraints as a reason for not expanding.

MicroBank (Spain)

Making impact measurement useful internally

MicroBank (Spain) aligns its outcome indicators with national policy priorities and uses the results to engage more actively with the public sector. Internal teams also use the data to understand which segments (e.g., women, youth, migrants) benefit most from specific credit lines. Learn more about Microbank via their website: https://www.microbank.com/en/home.html

Step 1: List all data touch points across the client lifecycle

Review all the processes where data is formally or informally collected: onboarding, loan disbursement, renewals, training, monitoring visits, etc.

Practical tips

1. Hold regular impact review sessions. Schedule quarterly meetings to review key outcome indicators, involving management and frontline staff to ensure diverse insights.
2. Make data accessible and understandable. Use simple dashboards or brief summaries to present trends clearly, focusing on both positive outcomes and challenges.
3. Involve frontline staff in interpreting results. Encourage loan officers and trainers to share on-the-ground perspectives that explain the data, helping to uncover root causes behind trends.
4. Use data to adjust services and drive improvement. When challenges emerge (e.g., low business survival rates), adapt products, mentoring, or outreach strategies, and track whether these changes lead to better outcomes.
5. Document and share learning internally. Maintain short learning notes or internal reports summarising each review session. Share key findings with all staff to promote organisational alignment.

(When possible) Conduct interviews in adequate venues and capture contextual factors

Encourage interviewers to conduct interviews in places where interviewees feel at ease and document not only what is said, but also the broader context—gender norms, household dynamics, local economic shocks—that shape whether an outcome occurred.

• Greater economic integration and social stability for migrants, stronger contribution to local economies, reduced marginalization fostering more inclusive communities.

Varying definitions of impact

A microfinance institution serving urban youth entrepreneurs might define its long-term impact as contributing to sustained business creation, improved livelihoods, and integration into the formal economy—enabled by increased access to startup capital, the development of business skills, and expanded employment opportunities. Meanwhile, an MFP working with female migrants might define its long-term impact as fostering greater social and economic inclusion—reflected in improved access to education, healthcare, and social protection, as well as enhanced autonomy and integration into the host community.

Tip #3

Clearly define long-term goals

Begin by clearly defining the long-term goals or outcomes your programme aims to achieve. These goals should represent the positive changes you want to see in the broader context. For example, you might consider setting a long-term goal as: “Increased economic resilience and social inclusion of low-income self-employed individuals.” This is aligned with both EU social policy priorities and the institution’s mission.

Use open-ended questions to explore causality, avoid "prompting"

Design interview guides with broad, non-leading questions like:

• “Can you tell me how your business has changed and performed over the last two years?”
• “What factors helped you grow your business or hire new employees?”
• “Why has your income increased over the last two years?”
• “Were there any challenges you faced?”

These open formats allow clients to express what really mattered, including unintended effects.

How was the toolkit developed?

The toolkit is the result of a collaborative and evidence-based process led by the Council of Europe Development Bank (CEB) to respond to the practical needs of MFPs in Europe in the field of social impact measurement. It draws on three information sources:

• an in-depth literature review of best practices and international standards, to establish a solid conceptual and methodological foundation
• a series of semi-structured interviews with key stakeholders, that offered insights into real-world experiences and dilemmas
• a survey that provided a snapshot of current practices, challenges, and needs

It is a practical toolkit that:

• Reflects operational realities of small and medium MFPs
• Offers adaptable tools (not prescriptive)
• Builds systems that are meaningful, manageable, mission-aligned

Identify service gaps by analyzing which client segments (e.g., youth, migrants, rural entrepreneurs) are underserved or excluded.

Tip #2

Engage stakeholders actively

Involve key stakeholders in the development process actively. This includes your clients, staff, community leaders, and experts. Their insights and perspectives are critical for building a comprehensive and inclusive ToC. For example, a MFI in Portugal hosts workshops with loan officers, clients (including migrants and low-income workers), and local government representatives. They co-design the ToC to ensure the planned financial literacy component aligns with clients’ real needs and barriers—such as digital literacy or language gaps.

• Inputs: Financial Services, legal expertise, training resources, partnerships with local authorities.

• Outputs: Migrants access capital for micro businesses, receive legal support and gain essential business skills.

Tip #6

Be realistic and consider what is feasible

Ensure that your ToC is realistic and shows what is actually feasible within the given context. Set achievable expectations, considering available resources, timelines, and the complexity of the social change you are aiming for. Consider the following example: A MFI in Lithuania initially aims to serve all unemployed youth in the country. After reviewing budget and staffing, they narrow the scope to target three regions where youth unemployment is highest, aligning ambition with resources.

Client satisfaction provides insight into whether clients feel their needs are being met and whether products and services are contributing to meaningful improvements in their lives.

Tip #3

Clearly define long-term goals

Begin by clearly defining the long-term goals or outcomes your programme aims to achieve. These goals should represent the positive changes you want to see in the broader context. For example, you might consider setting a long-term goal as: “Increased economic resilience and social inclusion of low-income self-employed individuals.” This is aligned with both EU social policy priorities and the institution’s mission.

Step 4: Plan for new data collection—Only where needed

• Full-scale surveys should not be launched immediately; priority should be given to addressing the most strategic data gaps.
• Develop a simple initial data plan:
• Who collects which data, when, and how often?
• Is an external survey research firm or research center needed for data collection?
• Where is the data stored?
• Who is responsible for analysis?
• Is an external survey research firm or research center needed for data analysis?

Create a one-page data collection calendar and responsibility matrix to clarify internal roles.

• Outcomes: Enhanced income stability and self-reliance for migrant households, reduced vulnerability to exploitation and legal insecurity.

Tip #10

Foster a learning culture

Build mechanisms for learning and adaptation into your ToC. Encourage regular reflection, evaluation, and the use of feedback to adjust strategies as needed. This adaptive approach enhances the programme's effectiveness. For example, a good practice is to include quarterly review meetings with staff to discuss client feedback, repayment trends, and drop-off rates in business support sessions. Insights are used to adjust loan terms or revise training content, supporting continuous improvement.

Expected social impacts of microfinance in Europe

The expected social impacts of microfinance in Europe are tied to:

• labor market integration,
• formalization of economic activity,
• empowerment through business ownership.

These priorities are aligned with broader EU policy goals, particularly those outlined in the European Pillar of Social Rights and its Action Plan, which commits to achieving higher employment, reducing poverty, and expanding access to education, training, and essential services.

Tip #1

Use available data

A good ToC should be evidence based, referring to what we already know about the problem and its potential solutions. So, when designing your ToC it is essential you look at what information and evidence exist to support that your programme activities will address the identified problem. For example, an MFI in Romania reviews national reports on financial inclusion and finds that women entrepreneurs in rural areas face credit access barriers. It also consults EU studies (e.g., from the European Microfinance Network) confirming that tailored loan products improve access. The MFI uses this evidence to justify its new rural women entrepreneurship programme.

Client perception indicators

Client perception indicators regarding the quality of services and products can also be considered and contrasted with output, outcome and impact indicators to gain a more nuanced understanding of impact.

European Code of Good Conduct for Microcredit Provision

Impact

• Increased financial resilience of low-income or vulnerable households
• Improved social inclusion of migrants and disadvantaged groups
• Sustained microenterprise survival rates after 2+ years
• Contribution to local economic revitalization or reduced reliance on social benefits

Boards

When using impact data to inform boards and internal leadership, it is important to consider the following elements:

• Use a fair balanced mix of quantitative data (KPIs, trends) and qualitative insights (challenges, lessons learned).
• Apply regular impact updates integrated into board reports or strategic reviews.
• Use dashboards highlighting progress towards ToC or Logframe targets.
• Present scenario analyses showing how impact results influence organisational strategy.
• Show honest reflection on gaps or unintended outcomes to guide improvements.

Boards and internal leadership require concise and visual summaries to guide strategy and resource allocation, to make informed strategic decisions, assess organisational performance, and identify risks or gaps. A combination of quantitative data and qualitative insights provides a complete picture; numbers indicate progress, while qualitative context highlights challenges and learning opportunities. Honest and balanced reporting allows boards to guide course corrections, set priorities, and ensure that the organisation stays aligned with its mission and Theory of Change.

Compulsory survey participation

Another strategy—though not always feasible or suitable for every institution—is to make survey participation compulsory at key client touchpoints, such as when a client renews a loan, receives business support services, or completes a training program. By integrating the survey as a standard part of the service review or exit process, institutions can significantly improve response rates and ensure that feedback is collected at consistent moments in the client journey.

Problem statement

• Which barriers or gaps does the institution aim to address are to be addressed (i.e., barriers and gaps faced by clients)?

Tip #4

Map out causal pathways

Clearly articulate the causal pathways from inputs/activities to outcomes and, ultimately, to impact. This mapping helps to visualize the logical connections and understand how each component contributes to the intended impact. Check this example as a reference:

Example

Long-term impact

• What is the desired end result the institution aims to achieve?

ADIE - France

ADIE uses its biennial outcome survey to assess business survival, transitions out of welfare, income evolution, job creation, self-fulfilment and quality of life improvements. These insights feed into product refinement and communication strategies. ADIE staff are also trained to understand the broader changes clients experience, reinforcing a mission-driven culture at all levels of the organization. Learn more: https://www.adie.org/

Listen for mechanisms, not just events

Train field staff to delve into why things happened, not just what happened. For instance:

• "Did confidence increase?"
• "Did the loan help smooth income seasonality?"
• "Was access to the new business network more valuable than the access to capital?"

Risk mitigation strategies: Strategies and actions planned to address identified risks and challenges.

ADIE (France)

ADIE (France) conducts a comprehensive impact study every two/three years, surveying a large sample of microcredit recipients. It tracks business sustainability, reduction in welfare dependency, job creation, and improvements in quality of life and banking inclusion. ADIE also reports on the environmental impact of their clients and uses both primary (surveys) and secondary (national statistics) data sources. Learn more about ADIE via their website: https://www.adie.org/

Balance closed and open-ended questions

Use closed questions (yes/no, multiple choice, scales) for comparability. Add one or two open-ended questions only when necessary for depth.Examples:

• Closed: “Has the number of your employees changed since receiving the loan?”
• Open: “What was the main factor that influenced this change?”

• Define the population clearly (e.g., all active clients, women entrepreneurs, clients with loans over €5,000).
• Use a random or stratified sampling approach to ensure diversity across relevant cohorts (e.g., gender, migrant status, business sector).
• Keep the sample manageable but statistically meaningful—e.g., 60–100 respondents may be sufficient for simple trends across a few cohorts.
• If resources are tight, consider rotating samples (e.g., survey a different group each year), targeted samples for specific programs, or conducting surveys every two or three years

Public registries

Public registries—such as credit bureaus, tax authorities, or local chambers of commerce—can offer valuable external data to complement your internal records and client-reported information. These sources may provide insights into clients’ credit histories, business registrations, employment status, or tax filings. When accessible, such data can help verify outcomes like business formalization, creditworthiness improvements, or increased financial stability over time. While access and data quality vary by country, leveraging these sources can reduce survey fatigue, increase reliability, and support longitudinal analysis—especially if linkages can be automated through digital channels.

Tip #8

Create a visual representation

A graphical representation, such as a flowchart or diagram, is often used to illustrate the relationships and connections between the different elements of the ToC. This visual representation helps stakeholders understand the logic behind the programme. Tap the icon to see examples:

Examples

Sustainable Development Goals (SDGs)

Tip #6

Be realistic and consider what is feasible

Ensure that your ToC is realistic and shows what is actually feasible within the given context. Set achievable expectations, considering available resources, timelines, and the complexity of the social change you are aiming for. Consider the following example: A MFI in Lithuania initially aims to serve all unemployed youth in the country. After reviewing budget and staffing, they narrow the scope to target three regions where youth unemployment is highest, aligning ambition with resources.

Question type: Cardinal / Numeric

Analysis tools:

• Mean and median: Show average and central values.
• Minimum and maximum values: Define the range of responses.
• Standard deviation: Measure how spread out responses are (optional).

Examples:

• All clients: Average revenue increased from €1,000 to €1,350/month.
• Cohort comparison: Migrant women experienced a 35% increase; non-migrant men, 18%.
• From interviews: Migrant women who saw revenue growth typically combined loan use with informal peer learning or community support. Some non-migrant men reported limited growth due to saturated local markets or higher fixed costs.

Outputs

• Number or proportions of loans disbursed to underserved groups (e.g. migrants, youth, women)
• Number of financial literacy workshops delivered
• Number of self-employed individuals supported
• Number of business advisory sessions provided

Avoid confusing or abstract phrasing

Avoid double negatives (e.g., “Don’t you disagree…”) or vague concepts. Ask one thing at a time. Example:

• Bad: “Would you say you are not unhappy with your financial wellbeing?”
• Good: “How satisfied are you with your financial wellbeing?”

Step 2: Assess data quality and gaps

• Which indicators are already well-covered by your current data?
• Where is the data missing, outdated, inconsistent, or too aggregated?
• What kind of data (qualitative/quantitative) is underrepresented?

Outputs

The direct and tangible products or services resulting from project activities. What evidence is there that the activities were performed as planned? It is the measurable effect of your work. What have we delivered? Examples:

• Number of loans disbursed to underserved groups (e.g. migrants, youth, women).
• Number of savings accounts opened.
• Number of financial literacy workshops delivered.
• Number of self-employed individuals supported.
• Number of business advisory sessions provided

Timeframe: A timeline that outlines the start and end dates of the period to be assessed, as well as key milestones and activities.

Funders and investors

The following suggestions can be used for presentation style for annual or public reports:

• Concise, data-driven reports highlighting key outcomes and success stories.
• Benchmarking against international frameworks (e.g., SDGs, IRIS+ indicators).
• Visuals, such as infographics, dashboards, and trend graphs showing progress over time.
• Real-life examples linking data to positive change (e.g., jobs created, businesses sustained).
• Emphasis on transparency, scalability, and risk management.

Funders and investors (e.g. CEB, EIF, EC) are result-oriented and are interested in understanding whether outcomes align with their priorities, i.e. gender inclusion, job creation, social cohesion. They also want to see that their resources are generating measurable social and economic returns. Their focus is often on comparability, risk management, and alignment with recognised standards (e.g., SDGs, IRIS+, SPTF). Presenting clear, concise, and standardised data builds credibility, reassures them of effective resource use, and increases the likelihood of continued funding. Visuals like infographics and trend charts help them quickly assess progress and impact at scale.

Be specific with timeframes

Always anchor questions to a clear period. This improves recall and consistency. Example:

• “In the past 30 days, how much income did your business generate?”

Second practical consideration: Complementary indicators

It is also good practice to combine quantitative and qualitative indicators that are discussed in more detail in an upcoming slide in this module. Quantitative indicators, such as the number of loans disbursed or the percentage of businesses still operating after one or two years, provide clear, measurable data. However, they rarely capture the full story. Complementing them with qualitative indicators, such as client satisfaction levels or beneficiaries reporting increased confidence in managing their businesses, gives deeper insights into the transformative impact of products and services.

Expected outputs

• What are the immediate results of the activities and services that the institution would like to achieve?
• Has the target population been reached?

Navigation Guide

Welcome! Here's how to explore the toolkit:

• Use the blue arrows on the top right corner to move between slides
• The Home button will bring you back to a slide containng an index of the modules:

• Each + opens a pop-up or reveals extra content such as examples, tips, or explanations— click to dive deeper.

Icons:

• Each section includes explanations of key concepts, case examples from MFPs in Europe, as well as downloadable templates and tools.

Now you're ready — start exploring!

SIS Credit (Bulgaria)

SIS Credit (Bulgaria) focuses on employment generation, entrepreneurial training, and financial capability. Through regular outcome monitoring, it demonstrates contributions to local economic development, particularly in underserved regions. Learn more about SIS Credit via their website: https://www.siscredit.com/en/home/

Tip #8

Create a visual representation

A graphical representation, such as a flowchart or diagram, is often used to illustrate the relationships and connections between the different elements of the ToC. This visual representation helps stakeholders understand the logic behind the programme. Tap the icon to see examples:

Examples

PerMicro (Italy)

PerMicro (Italy) collects outcome data on access to credit, business growth, women’s empowerment, and housing improvements. It evaluates impact both at the enterprise level (e.g., job creation, sustainability) and household level (e.g., medical care, transportation, family income), with attention to clients from marginalized groups. Learn more about PerMicro via their website: https://www.permicro.it/credit-and-microcredit-for-inclusion/

Address assumptions and risks

Explicitly identify and address assumptions and risks associated with the delivery of your products and services. Consider external factors that could impact the success and document the assumptions that need to hold true for the project to achieve its objectives. Develop strategies to mitigate identified risks. In this case, a mitigation strategy would be to translate documents into Arabic and French and provide in-person onboarding support in community centers. These are integrated directly into the logframe design to make risk mitigation part of delivery.

An MFI in Italy expands services to migrant entrepreneurs. In its logframe, the team identifies these assumptions and risks:

• Assumption: Migrant clients have access to digital devices for online applications
• Risk: Language barriers limit understanding of loan conditions

Start with a clear impact hypothesis

Before conducting the interviews, the ToC should be reviewed to identify the expected pathways through which services contribute to outcomes (e.g., income increase, job creation) and to structure interviews around plausible causal links. It is important to consider that external factors, such as business cycle, client-specific market opportunities, or policy environment, can substantially influence observed incomes or impacts.

Tip #9

Write a narrative of the ToC

Alongside the visual representation, a narrative explanation provides a detailed description of the causal relationships, logic, and rationale behind each element of the ToC. Use it as a communication tool to share the vision and logic of your programme.

Assumptions

The external factors and conditions that are expected to hold true for the programme to achieve its intended outcomes. These can include contextual factors, political stability, community support, etc. Assumptions reflect our deeply held values, norms and ideological perspectives, it is how we can forecast what changes might occur as an outcome of the programme.

• Migrant women emphasized the role of the loan in overcoming initial capital barriers and the training in building confidence and navigating regulations. Many cited childcare and housing as barriers to growth.
• Non-migrant women often focused on personal development and the ability to test new business ideas with reduced financial risk.
• Migrant men highlighted the importance of accessing formal credit, as many had previously relied on informal borrowing. Some faced difficulties with legal status or bureaucracy.
• Non-migrant men were more likely to attribute success to their own previous experience but appreciated the flexibility of the financial product.

Outcomes

Mid-term changes in behaviours, conditions or observed benefits resulting from the programme products and services. These are higher level results than those from intermediate outcomes. Who, what changed and how? Examples:

• Enhanced business resilience to economic shocks or market fluctuations.
• Increased proportion of clients reporting stable and regular income from their business activities.
• % of clients reporting increased income or business turnover.
• % of clients transitioning from unemployment to self-employment.
• Improved ability to manage personal or business finances.
• Increased digital or financial capability

Tip #5

Identify assumptions and risks

Explicitly state the assumptions underlying your ToC. Identify the conditions that must be true for the theory to work. Additionally, assess and document potential risks that could impact the achievement of outcomes. For example, a French MFI identifies the assumption that clients will participate in business mentoring if offered. A risk is that cultural stigma or scheduling issues might prevent participation. They note this in the ToC and plan a pilot mentoring program to test interest first.

Strengthen relationships with stakeholders, including clients, public authorities and funders by improving financial and non-financial offer, and demonstrating real-world outcomes aligned with policy goals (e.g., employment, social cohesion, local development).

Offer opt-out options

Some clients may be unwilling or unable to answer certain questions. Avoid forcing a response. Examples:

• Include response options such as: “Don’t know” or “Prefer not to answer.”

CERISE+SPTF’s Universal Standards for Social Performance Management

Steps to improve your products and services

1. Track relevant outcome indicators, not just outputs. Go beyond counting loans disbursed, measure real outcomes such as financial health, business survival, or repayment challenges by client segments.
2. Analyse outcome data to identify product gaps. Look for patterns that reveal which groups face difficulties.
3. Engage clients for deeper insights. Combine outcome data with client feedback to understand structural barriers (e.g., childcare responsibilities, seasonal income cycles) that products may not address.
4. Adjust product features based on evidence. Use outcome insights to redesign loan terms, eligibility criteria, or repayment schedules. For example flexible repayment options for women, tailored products for rural clients, etc.
5. Institutionalise product review workshops. Schedule regular product review sessions using outcome data, client feedback, and repayment trends to continuously adapt and improve products, ensuring they meet evolving client needs.

Step 1: Classify data by type of indicator and purpose

Review each entry in the data inventory table and consider whether each data point (e.g., age, income, business type) is best understood as an output, an outcome, or a proxy for impact. For each data source, tag:

• The type of indicator it supports (output, outcome, or impact)
• The purpose it can serve: internal learning, donor reporting, or both
• The European or international standards and frameworks it captures (e.g., which SDG?).

It is important to keep in mind that some data points can serve multiple functions. For instance, income at onboarding may be used to estimate the poverty level of clients reached (output), while changes in income over time may serve as a measure of outcome or impact.

Tip #1

Use available data

A good ToC should be evidence based, referring to what we already know about the problem and its potential solutions. So, when designing your ToC it is essential you look at what information and evidence exist to support that your programme activities will address the identified problem. For example, an MFI in Romania reviews national reports on financial inclusion and finds that women entrepreneurs in rural areas face credit access barriers. It also consults EU studies (e.g., from the European Microfinance Network) confirming that tailored loan products improve access. The MFI uses this evidence to justify its new rural women entrepreneurship programme.

Tip #5

Identify assumptions and risks

Explicitly state the assumptions underlying your ToC. Identify the conditions that must be true for the theory to work. Additionally, assess and document potential risks that could impact the achievement of outcomes. For example, a French MFI identifies the assumption that clients will participate in business mentoring if offered. A risk is that cultural stigma or scheduling issues might prevent participation. They note this in the ToC and plan a pilot mentoring program to test interest first.

Support strategic decisions by grounding institutional priorities in evidence about what works for different client groups and how.

Intermediate outcomes

Short-term changes achieved because of the programme interventions. These are already observed changes resulting from the activities and outputs contributed by the programme. Who, what is changing and how? Examples:

• Increased access to financial services and products by vulnerable groups.
• Improved awareness of financial and entrepreneurial opportunities.

Use SMART indicators

Develop specific, measurable, achievable, relevant, and time-bound (SMART) indicators for each level of the logframe. Indicators should provide clear and quantifiable measures of progress toward achieving the project's objectives. Well-defined indicators facilitate effective monitoring and evaluation. This indicator is: Specific (focuses on youth in two cities); measurable (targets 150 loans and 85% repayment); achievable (based on past demand analysis); relevant (aligns with national youth employment goals), time-bound (deadline of Q4 2025).

For example, a microfinance institution in Bulgaria wants to promote youth entrepreneurship. Instead of a vague indicator like “More young people supported,” they define a SMART indicator: “By Q4 2025, disburse at least 150 microloans to entrepreneurs aged 15–29 in Sofia and Plovdiv, with a minimum 85% repayment rate after 6 months.”

Operating Principles for Impact Management (OPIM)

Tip #9

Write a narrative of the ToC

Alongside the visual representation, a narrative explanation provides a detailed description of the causal relationships, logic, and rationale behind each element of the ToC. Use it as a communication tool to share the vision and logic of your programme.

Outcomes

• % of clients reporting increased income or business turnover
• % of clients transitioning from unemployment to self-employment
• Improved ability to manage personal or business finances Increased digital or financial capability

Tip #3

Clearly define long-term goals

Begin by clearly defining the long-term goals or outcomes your programme aims to achieve. These goals should represent the positive changes you want to see in the broader context. For example, you might consider setting a long-term goal as: “Increased economic resilience and social inclusion of low-income self-employed individuals.” This is aligned with both EU social policy priorities and the institution’s mission.

Impact

The ultimate, long-term goal or impact the programme aims to contribute to. The impact is the result of many and different factors or interventions influencing changes in policies, structures, systems and society. What is the ultimate change you aim to achieve? Examples:

• Greater financial inclusion, particularly among underserved groups (e.g., migrants, women, youth)
• Job creation within supported microenterprises, contributing to local employment growth
• Increased financial resilience of low-income or vulnerable households. Improved social inclusion of migrants and disadvantaged groups

Third practical consideration: Align w/ international frameworks

Finally, to strengthen the credibility and comparability of impact measurement, it’s important to align indicators with international frameworks (refer to the next slide for a deeper discussion). These include the European Code of Good Conduct for Microcredit Provision, Sustainable Development Goals (SDGs), the IRIS+ system developed by the Global Impact Investing Network, and the Social Performance Task Force (SPTF) standards. For example, if microfinance products and services contribute to improving women’s economic participation, indicators can be linked to SDG 5 (Gender Equality) or SDG 8 (Decent Work and Economic Growth). Using recognised frameworks ensures results are understandable and valued by funders, partners, and the broader microfinance community.

Tip #7

Be specific about activities

Clearly define the activities or interventions that will be implemented to achieve the desired outcomes. This helps in translating the theory into actionable steps. Ensure that there is no duplication of activities (similar activities mentioned twice). For example, instead of writing “support entrepreneurs,” you might specify: “Conduct monthly group training sessions on financial planning” “Provide one-on-one coaching within 3 months of loan disbursement” It is important to ensure that no activity is repeated or vaguely defined.

Qredits (Netherlands)

Qredits (Netherlands) monitors business survival after 3 and 5 years, job creation, and transition to mainstream financial services. It also tracks client diversity (e.g., age, gender, migration background) and connects outcomes to SDGs 1, 4, 5, 8, and 11. Data are gathered through follow-up questionnaires and complemented by official statistics. Learn more about Qredits via their website: https://www.qredits.com/

Peri-Urban Native Men with BDS

Male non-migrants in peri-urban areas who received a business loan and business trainingCan BDS amplify the outcomes of more established local clients in semi-urban zones?

It is important that you keep the following in mind:

• Your objectives should always be SMART (specific, measurable, achievable, realistic and time-bound).
• Write assumptions and risks that can be identified.
• Design your indicators to measure progress towards objectives.
• Set the targets for each indicator.

Tip #2

Engage stakeholders actively

Involve key stakeholders in the development process actively. This includes your clients, staff, community leaders, and experts. Their insights and perspectives are critical for building a comprehensive and inclusive ToC. For example, a MFI in Portugal hosts workshops with loan officers, clients (including migrants and low-income workers), and local government representatives. They co-design the ToC to ensure the planned financial literacy component aligns with clients’ real needs and barriers—such as digital literacy or language gaps.

National and regional statistics for benchmarking

Publicly available statistics from national or regional sources—such as statistical offices, labor ministries, or development agencies—can offer crucial context for interpreting outcome and impact data. These may include unemployment rates, business survival trends, poverty indicators, inflation, or average income by sector and region. Such data help benchmark client progress against broader economic trends, identify whether observed changes are due to the intervention or part of wider shifts, and strengthen the credibility of the analysis. While these sources do not replace client-level data, they are particularly valuable for cohort comparisons, contextualizing results, or justifying targeting strategies in funding applications.

Avoid questions that encourage socially desirable answers

Frame questions neutrally, without implying there is a “right” answer. Examples:

• Bad: “Have you made your business more successful with our help?”
• Good: “Has your business performance changed in the past 6 months?”

Recurring client-reported data

Many microfinance providers regularly receive data from clients as part of their ongoing relationship—particularly from SMEs that are required to submit simplified profit and loss (P&L) statements, cash flow records, or basic business updates. This operational data can provide valuable insights into business growth, financial resilience, and employment generation over time. When standardized and digitized, such recurring data becomes a powerful tool for tracking client progress and assessing impact without the need for costly standalone surveys. Ensuring consistency in the format and frequency of this reporting is key to making it actionable for both internal decision-making and external reporting.

Assumptions

• What are the external factors and conditions that are expected to hold true for the institution's activities, services and products to achieve their intended results?

Use guided probing to identify contribution, avoid “bias”

Ask follow-up questions that gently explore attribution, e.g., After delving into the factors that helped grow the business or create jobs, ask the following:

• “Would you say this would have happened anyway, without the loan/training/mentoring?”
• “How has the loan/training/mentoring contributed?”

This helps gauge the role of your intervention while acknowledging external influences.

Step 6: Prioritize high-value, low-cost data

Focus first on data sources that are already digitized, consistently updated, and relevant to key outcomes or funder requirements.

Link activities to outputs and outcomes

Establish a logical and coherent linkage between the organisation’s activities, outputs, and outcomes. Clearly illustrate how each activity contributes to the production of outputs and, subsequently, how these outputs lead to the achievement of specific outcomes. This logical sequence reflects the project's theory of change. This structure shows a clear causal chain from training activity to a measurable behavioral outcome that supports loan sustainability.

An MFP in Spain offers financial literacy workshops as a precondition for loan approval. In its logframe:

• Activity: Deliver monthly financial literacy workshops
• Output: 200 clients complete training by end of year
• Outcome: 70% of trained clients demonstrate improved financial management (measured via reduced missed payments and budgeting scores)

Assumptions: Explicit identification of external factors or conditions that need to be in place for the project to succeed. Assumptions are crucial for risk management.

MicroBank (Spain)

MicroBank (Spain) uses telephone surveys and interviews to assess job creation, financial inclusion, support for the social economy, and gender equality. It systematically links outcomes to selected SDGs and uses national statistics to complement client-level data. Learn more about Microbank via their website: https://www.microbank.com/en/home.html

Easy to communicate to the general public

Indicators should be framed in a way that supports transparency and public accountability, without requiring technical interpretation. Consider how they will appear in reports, dashboards, or fundraising materials.

Tip #4

Map out causal pathways

Clearly articulate the causal pathways from inputs/activities to outcomes and, ultimately, to impact. This mapping helps to visualize the logical connections and understand how each component contributes to the intended impact. Check this example as a reference:

Example

Step 5: Evaluate external data options

List external sources (e.g., regional/national statistics, credit bureau access, chamber of commerce records) and assess:

• Is this data available and up to date?
• Can we trust its quality and consistency?
• Especially for regional/national statistics: How granular is the data? Can it be matched with our markets/regions where we operate?
• Is it accessible at no or limited cost?
• Does it align with the outcomes we want to track?

Use impact data for targeting and outreach

1. Disaggregate outcome data by key demographics. Collect and analyse data by gender, age, location, migrant status, and other relevant factors to reveal who is being reached, and who is not.
2. Identify gaps and underserved groups. Look for patterns showing low participation or poor outcomes among specific groups, for example ADIE in France noticed underrepresentation of migrant women.
3. Adapt outreach strategies based on insights. Use the data to design targeted outreach, such as translated materials, partnerships with community groups, or campaigns tailored to specific populations.
4. Continuously monitor targeting effectiveness. Track whether outreach adaptations lead to improved access and outcomes for previously underserved groups, like Qredits in the Netherlands adjusted their approach this way for youth and rural clients.
5. Collaborate with community stakeholders. Partner with local organisations that work closely with hard-to-reach groups to improve trust, cultural relevance, and overall outreach effectiveness.

Client onboarding data

The client onboarding process is a valuable moment for collecting data that can serve multiple purposes. Information typically gathered during loan applications or account setup—such as gender, age, residence, and type of business—can be used to generate key output indicators. Additionally, onboarding is an opportunity to establish baseline data for future outcome and impact tracking, including metrics like household income, business revenue or profit, and number of employees.Since much of this data is already collected for due diligence and risk assessment, integrating impact-relevant questions into your onboarding forms can be a cost-effective way to strengthen the measurement system of the institution without overburdening staff or clients.

The logframe is a tool that can be used to:

• Plan and track the progress of your activities with your clients.
• Visualize the project’s goals, objectives, activities, and deliverables.
• Identify risks and issues.
• Monitor and evaluate your progress.

A large proportion of the impacts that institutions aim to track is usually not quantifiable. For example, changes in household dynamics, community participation, social integration, quality of life or empowerment

Client transaction and interaction data

Client transaction and interaction data—such as loan disbursements, repayments, savings activity, loan renewals, participation in training sessions, or use of digital channels—offer a continuous and cost-effective source of behavioral insights. These data are typically recorded through your MIS or other internal systems and can serve as valuable proxies for outcomes like financial stability, business growth, or client engagement. For instance, repeat loan renewals may signal business continuity or customer satisfaction, while consistent savings patterns or attendance at training sessions may reflect increased financial literacy or motivation to improve economic prospects.

SIS Credit - Bulgaria

SIS Credit uses outcome data to monitor whether clients are gaining employment or improving their business management skills. These findings inform product adjustments and are shared internally to raise awareness among loan officers about the longer-term effects of their work. Learn more: https://www.siscredit.com/en/home/

Tip #2

Engage stakeholders actively

Involve key stakeholders in the development process actively. This includes your clients, staff, community leaders, and experts. Their insights and perspectives are critical for building a comprehensive and inclusive ToC. For example, a MFI in Portugal hosts workshops with loan officers, clients (including migrants and low-income workers), and local government representatives. They co-design the ToC to ensure the planned financial literacy component aligns with clients’ real needs and barriers—such as digital literacy or language gaps.

Public and clients

The following must be taken into account when presenting to the public and clients, to ensure impact data is clear and meaningful:

• Use simple, accessible language avoiding technical jargon.
• Make use of human stories and testimonials to show impact on real lives.
• Present infographics, short videos, or social media posts illustrating key achievements.
• Organise community events or newsletters summarising outcomes in an engaging way.
• Try to encourage client feedback to validate and enrich the data presented.

Public and clients benefit from storytelling and key messages that reinforce your mission and transparency. For the public and clients, trust, relevance, and transparency are key. Complex technical reports risk alienating these groups. Instead, using simple language, human stories, and engaging formats (e.g., testimonials, visuals) makes impact tangible and relatable. Clients want to see how services affect their lives, while communities and stakeholders want reassurance that your organisation delivers positive, ethical, and meaningful results. Inclusive communication fosters trust, encourages participation, and builds your organisation's reputation.

Step 2: Create a data inventory table

For each touchpoint, fill in:

• Type of data collected (e.g., age, income, business sector)
• Format (paper, digital, Excel, MIS)
• Frequency (one-time, monthly, annual)
• Responsible person/department
• Storage location
• Level of completeness and quality
• Access restrictions (GDPR/compliance)

Harmonized Indicators for Private Sector Operations (HIPSO)

Question type: Ordinal Scales

Analysis tools:

• Median and mode: Show central tendency without being skewed by extremes.
• Score distribution: Visualize how responses spread (e.g., 25% “not at all satisfied”, 40% “somewhat”).

Example:

• All clients: Overall satisfaction (using median or mode) with income stability rose from “somewhat” to “fairly satisfied.”
• Cohort comparison: Young women showed the biggest improvement; older men remained unchanged.
• From interviews: Young women often attributed their improved satisfaction to feeling more in control of household finances and gaining budgeting skills from the training. Older men reported feeling more pessimistic about the market context or upcoming retirement.

Rural Native Women without BDS

Female non-migrants in rural areas who received a loan but no BDS What are the performance gaps for rural women lacking advisory support?

Activities

The specific actions or interventions undertaken by the programme. These are the means by which inputs are transformed into tangible outputs and contribute to achieving the intermediate outcomes. What do we do? Examples:

• Delivery of financial products and services.
• Delivery of business support and training.
• Support for community development.

Open-Ended Questions

Analysis tools:

• Thematic coding: Group responses into categories (e.g., “lack of childcare”, “mentoring support”).
• Frequency of themes: Count how often each theme appears.
• Quotations: Use for reporting and illustrating key points.

Example:

• All clients: Many clients attributed business growth to the initial financial injection.
• Cohort example: Migrant women more often credited personal mentoring and networks; young men cited digital marketing skills.
• Sample insights: “The training helped me track my spending, but it was really the mentoring that pushed me to register officially.” or “I didn’t expand because I couldn’t afford childcare—so I paused my activities even after the loan.”

Means of verification: Clear identification of methods and sources of information that will be used to verify the achievement of objectives and outcomes. conduct entrepreneurship workshops.

Routine client feedback and satisfaction surveys

Many MFPs conduct periodic satisfaction surveys, client exit interviews, or feedback mechanisms as part of their service quality management. While often designed to monitor client experience, these tools can also provide valuable outcome-related insights—such as perceived improvements in business performance, financial stress, or quality of life. If conducted regularly (e.g., annually or after loan cycles), they can help track client perceptions over time and flag potential issues like over-indebtedness or service gaps. In addition, collecting short qualitative feedback during regular touchpoints—such as branch visits, call centre interactions, or follow-up meetings—can complement quantitative metrics and provide a more nuanced understanding of impact.

Tip #2

Engage stakeholders actively

Involve key stakeholders in the development process actively. This includes your clients, staff, community leaders, and experts. Their insights and perspectives are critical for building a comprehensive and inclusive ToC. For example, a MFI in Portugal hosts workshops with loan officers, clients (including migrants and low-income workers), and local government representatives. They co-design the ToC to ensure the planned financial literacy component aligns with clients’ real needs and barriers—such as digital literacy or language gaps.

Activities, services and products

• What does the institution deliver to address the problem?

Rural Migrant Women with BDS

Definition: Female migrants in rural areas who received a business loan and participated in BDS sessions Potential insights to explore

• Does BDS improve outcomes for women in low-density, high-barrier areas?

Select a sample that reflects variance

Don’t only interview ‘success stories.’ Include clients with neutral or negative experiences to understand the full spectrum of outcomes. These can be clients with negative outcomes (e.g., job reduction or business revenue reduction) as well as clients that are unhappy with the MFP services or products. This is essential to avoid bias in impact stories.

Feasible to collect and analyse

The cost and complexity of data collection must match your institution’s capacity and resources. Start with indicators that can be tracked using existing systems or through light-touch adaptations. Where possible, leverage administrative data and integrate indicator tracking into operational workflows to avoid duplicating efforts.

Step 3: Review past reports and forms

Look at application forms, past donor reports, due diligence files, and exit surveys to uncover indicators you may already be tracking without realizing it.

Engage stakeholders

Involve key stakeholders throughout the development of the logframe. Gather input from individuals who have a vested interest in the success of your products and services, including your clients, loan officers, and managers. Stakeholder engagement helps ensure that the logframe reflects a collective understanding and commitment. Based on this input, the logframe includes: Indicators tracking client satisfaction; outputs related to improved follow-up protocols; outcomes on increased client retention and repayment. Engaging stakeholders ensures the logframe isn't designed in isolation and aligns with field realities.

In Hungary, an MFI consults with:

• Clients (via surveys) about what services they need
• Loan officers on barriers to recovery or client communication
• Branch managers on operational challenges

• Intermediate outcomes: Increased self-employment and business activity among migrants, improved knowledge of legal rights and processes, higher rates of legal status regularization (e.g. work permits, residency, documentation).

IRIS+ (GIIN)

Refine products and services based on learnings from client narratives or findings from intended or unintended outcomes—such as adapting loan sizes, training content, or repayment schedules when clients struggle to achieve financial stability.

Tip #3

Clearly define long-term goals

Begin by clearly defining the long-term goals or outcomes your programme aims to achieve. These goals should represent the positive changes you want to see in the broader context. For example, you might consider setting a long-term goal as: “Increased economic resilience and social inclusion of low-income self-employed individuals.” This is aligned with both EU social policy priorities and the institution’s mission.

How can machine learning contribute to impact assessment practices?

• Pattern recognition in outcomes: ML algorithms can detect which client characteristics, services, or contextual factors are most strongly associated with positive social outcomes—insights that are often difficult to uncover through manual analysis.
• Predictive analytics: ML can help forecast which clients are more likely to benefit from specific products or support services (e.g., training, mentoring), enabling more efficient targeting and resource allocation.
• Segmentation and cohort analysis: Advanced clustering techniques can group clients by similar behavioural patterns or life circumstances, facilitating more meaningful outcome comparisons and improving cohort tracking over time.
• Hypothetical counterfactuals: Perhaps most critically, ML can simulate “what-if” scenarios by predicting how similar clients without access to a specific intervention would have fared. This allows for quasi-experimental comparisons without a traditional control group, offering an ethical and feasible way to estimate impact for institutions that cannot implement randomized trials.

Tip #3

Clearly define long-term goals

Begin by clearly defining the long-term goals or outcomes your programme aims to achieve. These goals should represent the positive changes you want to see in the broader context. For example, you might consider setting a long-term goal as: “Increased economic resilience and social inclusion of low-income self-employed individuals.” This is aligned with both EU social policy priorities and the institution’s mission.

Qredits - Netherlands

Qredits analyzes business survival and job creation rates to evaluate the effectiveness of its coaching and loan services. Outcome data are integrated into internal dashboards and used in team meetings to identify gaps or adapt training offers, particularly for underperforming segments. Learn more: https://www.qredits.com/

Don’t just extract but also reflect

Treat qualitative interviews as opportunities for learning, not just reporting. Share findings internally to adapt services, and externally to build legitimacy with funders.

First practical consideration: Disaggregate indicators

When defining indicators, it is essential to ensure that they are not only meaningful at the overall programme level but also for specific groups within the target population. Disaggregating indicators by gender, age, migrant status, or other relevant characteristics makes it possible to assess whether services are reaching those who face the greatest barriers to inclusion (in an upcoming section, it’s discussed how to create meaningful client cohorts). For instance, tracking how many women entrepreneurs accessed microloans, or how many migrants successfully formalised their businesses, helps understand whether services are reaching the people who face the greatest barriers to financial inclusion.

CERISE+SPTF Outcomes and SDGs Resource Center (linked to the Universal Standards, Dimension 6)

Step 4: Consult key staff

Speak with credit officers, IT, monitoring and evaluation (M&E) staff, and branch managers to identify data sources that aren’t formally documented.

Tip #1

Use available data

A good ToC should be evidence based, referring to what we already know about the problem and its potential solutions. So, when designing your ToC it is essential you look at what information and evidence exist to support that your programme activities will address the identified problem. For example, an MFI in Romania reviews national reports on financial inclusion and finds that women entrepreneurs in rural areas face credit access barriers. It also consults EU studies (e.g., from the European Microfinance Network) confirming that tailored loan products improve access. The MFI uses this evidence to justify its new rural women entrepreneurship programme.

Inputs

The resources, raw materials that provide the basis for a project and that the implementing organisation will leverage to achieve the expected results. What do we have? Examples:

• Networks
• Technical expertise
• Technology
• Personnel

Tip #1

Use available data

A good ToC should be evidence based, referring to what we already know about the problem and its potential solutions. So, when designing your ToC it is essential you look at what information and evidence exist to support that your programme activities will address the identified problem. For example, an MFI in Romania reviews national reports on financial inclusion and finds that women entrepreneurs in rural areas face credit access barriers. It also consults EU studies (e.g., from the European Microfinance Network) confirming that tailored loan products improve access. The MFI uses this evidence to justify its new rural women entrepreneurship programme.

Use impact data to improve your non-financial services

1. Track outcomes for clients receiving non-financial services. Measure business survival rates, income growth, or employability separately for clients who access training, mentoring, or advisory support.
2. Compare outcomes with clients not receiving support. Assess whether those participating in non-financial services achieve better results, as seen with Polish MFIs that found higher business survival rates among trained clients.
3. Use evidence to adjust and improve support services. When outcome data shows certain training or mentoring activities lead to better results, scale them up or refine their content and delivery.
4. Engage clients to understand their experience. Combine outcome data with feedback from clients on the usefulness, accessibility, and impact of non-financial services to ensure they meet real needs.
5. Demonstrate value to funders and internal decision-makers. Use clear outcome evidence to justify resource allocation for training, coaching, or mentoring, as BCR Social Finance did by strengthening their support programmes based on improved business stability results.

Use small samples, but systematically

Even 6-8 interviews per cohort or client segment, if chosen thoughtfully, can yield rich insights. What matters is how rigorously they are analyzed and reported.