Qualitative data rarely arrives in neat, structured formats. It comes through interviews, field notes, open-ended surveys, WhatsApp conversations, and transcripts across multiple projects and time periods. ​

For many teams, the challenge is not just collecting this data, but making sense of it in a way that can actually inform strategy and decision-making. ​

In this session, we demonstrate how Dots supports end-to-end qualitative and mixed methods workflows to generate meaningful insights. ​

What the demo covers:
1) ​How to structure qualitative data for analysis: Move from raw inputs to organized, analysis-ready datasets
​2) How to combine qualitative and quantitative data in one workflow: Connect and explore mixed methods data together, instead of in silos ​
3) How to move beyond manual coding into deeper analysis: Track patterns, relationships, and changes over time within your data

​What you'll walk away with:
​1) A clear sense of how Dots works and what it can do
2) ​A feel for whether it's the right fit for your use case
3) ​And if it is, a starting point for aligning with the Dots team on how to put your qualitative data to work ​

Who this session is for: ​
1) MEL practitioners and program teams in the social impact sector
2) ​Organizations managing large or ongoing qualitative datasets across projects or geographies
3) ​Teams looking to make qualitative insights more usable for decision-making