Data Products

From Insight to Impact. Get more out of your data using KIT’s broad repertoire of data products.

We help our clients and partners to make the most of their data, supporting them to use evidence to learn, improve and make better-informed decisions. Using a combination of open, monitoring and evaluation (M&E), and primary survey data, we provide actionable advice to increase project impact and value.

Through M&E, every international development project generates a vast amount of data on beneficiaries, stakeholders, value chains and the local social dimensions, like access to loans or decision power. However, few projects manage to take full advantage of this potential, suggesting that a wealth of information is under-utilised.

Maximum insight into your data

At KIT, we are dedicated to providing our clients and partners with maximum insight into their data. Doing social research requires a high time investment from respondents, as well as a willingness to provide personal data to support the project. We owe it to them to maximise the impact of their investment on your learning.

Intuitive and actionable dashboard

Our data scientists present your data in a comprehensive, yet intuitive and actionable dashboard. We first help you refine and/or define your indicators, which we use to subsequently develop interactive data dashboards, guiding you through the output, outcome and impact indicators of your project.

By allowing users to manually apply filters, disaggregate data and draw comparisons between subgroups, our dashboards allow them to fully master their data. By creating multiple layers of access, different subsets of data and functionalities can be made available for different stakeholders.

Transparency and accountability,

Sharing the data with funders and other stakeholders boosts our clients’ transparency and accountability, which in turn builds trust across their networks.


Our longstanding track record in providing data insights provides us with a vast set of off-the-shelf tools and analytical methodologies that can be customised for each client and partner. At KIT, we provide a one-stop-shop , delivering services at any stage of the M&E cycle. Therefore, we have ready-made processes to extract, transform, load and process the data between various stages of analysis. We can thus guarantee value for money through efficient development of state-of-the-art products against strict deadlines.

Sample of our data services

Profiling of beneficiaries using unsupervised machine learning

Every beneficiary requires a different set of interventions to improve. Using unsupervised machine learning models , we create beneficiary clusters that form the basis of various profiles of individuals and households. Per cluster, we test which intervention yields the greatest impact, so our clients can specify their approach. For Cargill and Nestle , we have generated farmer profiles using clustering algorithms to allow them to differentiate their interventions to support living income accordingly.

Predicting success using decision trees

Decision trees are among the best algorithms to generate easy-to-interpret nonlinear effects. Determinants of success are ordered based on their relative importance, and coefficients are assigned to quantify their impact on the outcome variable. We have employed decision trees for an impact evaluation for FMO , where we tested which characteristics determine farmers’ success in loan acquisition.

Data visuals

Each project requires its own set of visuals to satisfy the purpose of the client. We have developed a wide set of intuitive and easy to interpret plots to visualise KPI’s, (sub-) indicators, geodata and much more. We adapt each visualisation to match the client’s needs.

Secondary data deep-dive

By triangulating data with KIT’s databases and open data, we provide context and give meaning to the programme’s data. Not only can we compare yield data to our historical database, we also use open data sources to see how it compares to other yield estimations in the region, and we can use remote sensing data on soil quality and weather patterns to clarify outcomes.

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