Analyse your data

What’s the best way to make sense of the data you’ve collected?

Data analysis is the process of making sense of the data you have collected. It involves examining your data to find patterns and themes, and drawing conclusions about what it is telling you.

Here we explain how to use the questions outlined when planning your impact practice, alongside the five types of data framework, to analyse your data.

How to analyse your data

Data analysis should start with what you need to know. By agreeing your goals and deciding what data to collect, you will have already identified the research questions you want to answer. These should frame your analysis.

Use the five types of data framework to review your data systematically. The focus of your analysis will depend on your particular needs. For example, if your programme model is similar to others, and evidence on the effectiveness of your particular approach already exists, you may choose to focus on your reach and the quality of your service (user, engagement and feedback data).


User data

Information on the characteristics of the people you are reaching

Key questions

  • Who are we reaching and what are their characteristics?
  • Who are we not reaching and what are their characteristics?
  • Are we reaching our intended target audiences?
  • How do people reach us? How do they hear about us?

Feedback data

Information about what people think about the service.

Key questions

  • Who do we get feedback from?
  • Who do we not get feedback from?
  • Do people enjoy the service(s)? Do they find it useful?
  • Which aspects do they rate the highest and lowest? What is working well/less well?
  • Do different groups of users respond differently?
  • Is the service being delivered as we intended?

Engagement data

Information about how people are using your service, and the extent to which they use it.

Key questions

  • How often are people using our service(s)? For how long?
  • Do some groups of users engage better than others?

Outcomes data

Information about the short-term changes, benefits, or assets people have gained from the service.

Key questions

  • What is different now? What are the changes in behaviour, attitudes, and skills among our users?
  • Are we seeing the outcomes we expected to see?
  • How has our service(s) helped? Can changes be attributed to our work? What other factors contribute?
  • Have certain aspects have helped certain users, and under what circumstances
  • Are the results consistent? Do we achieve better outcomes for some groups of users?
  • Where do we get our best results? Which are our most effective activities? Under what circumstances?
  • Are we helping those in greatest need?

Impact data

Information on the long-term difference that has resulted from the service.

Key questions

  • What is the long-term difference our service(s) has made? For whom?
  • What other factors have contributed to this change?

Save the five types of data for later

Keep our framework and key questions to hand to make sure you’re focusing on the right data.

Adapted from content from Inspiring Impact partner NPC 

Not sure what data to use?

The Data Diagnostic asks 10 multiple choice questions about what your programme or service is, how it works, and who it targets. It then provides a tailored report recommending what kind of data you should consider collecting and how.

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Quantitative data

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Qualitative data

How can you analyse qualitative data to understand the reasons for change?

Compare your data

How can you compare your data to understand it in a wider context?

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