Your stories, visualised
Evaluators, researchers, NGOs, and universities use Causal Map to find out what works, why, and for whom, straight from what people tell them in interviews, reports, and surveys.
Test whether programmes work
You have a theory of how your programme is supposed to create change. Causal Map lets you check that theory against what stakeholders actually say, and see where the evidence is strong or missing. What is causal mapping?
Find out what drives what
Read through your interviews and mark the causal connections people describe (“training improved my confidence”). Then filter, compare groups, and see which factors come up most as drivers or outcomes.
Present the evidence
Generate interactive maps and visual reports that show exactly how you arrived at each finding. Every claim links back to the source text. See case studies.
Code your own data
“Coding” here means reading through your sources and marking the causal claims people make: who says what leads to what. The app builds maps as you go. This works well for up to around 30 interviews. For larger datasets, add optional AI coding: AI extracts connections at scale while you review and interpret. Try it free or see pricing. Follow our Guide for tutorials and worked examples.
We do it for you
Include us in your analytical team. We code your data and deliver a visual report showing which factors drive which outcomes, where groups agree and disagree, and whether the evidence supports your theory of change. Learn more or get a quote.
Trusted by organisations including UNICEF, World Food Programme, Save the Children, IFRC, Tearfund, Fairtrade, Diageo, and universities worldwide.
What our users say
I chose Causal Map because of its appealing visualisation of the maps and the variety of tools that make a comprehensive analysis possible. I also highly appreciated the personal and user-oriented support from Steve and his team.
Christoph (Researcher)
I found the Causal Map app particularly helpful in combining a diverse range of data sources into one place, and the simple interface allowed for effective induction analysis. Following helpful training by the Causal Map team, I was able to interrogate the data to create helpful visualisations.
Michelle (Researcher)