Explainer - qualitative and quantitative data collection, and mixed methods approach

Owned by Nicole Mc Neilly
Last updated: Aug 17, 2023
3 min read

Intended Learning outcomes

This page is designed to help you:

  • Better understand the differences between qualitative and quantitative data collection

  • Advocate for a mixed methods approach

  • Strengthen your knowledge of when to apply certain methods

What are data collection methods?

Methods are ways of collecting and analysing data. Data can be collected in a number of ways - the most common methods are through surveys, interviews, focus groups and observations. You might also consider how you measure more quantitative change: interaction with your online collections or website, engagement with social media, location-tracking, use of your API, etc. Each of these data sources can give you interesting information to triangulate with more qualitative information.

Whatever type of impact you are most interested in measuring, how you collect your data will generally fall into one of two categories: qualitative or quantitative methods. It’s important to know the pros and cons and to think about how you can balance a mixed methods approach.

Qualitative vs quantitative data collection - an overview

Quantitative

What: Things that can be quantified - numbers are always involved. Like satisfaction ratings, numbers of people engaging with an exhibit, etc.

When:

  • To answer questions about how many, how much

  • To make comparisons between different (groups of) people

  • To get a general overview of a situation

Advantages:

  • Generalisable to larger population

  • (Relatively) easy to analyse

  • Reliable and consistent data

Disadvantages:

  • Difficult to interpret without context

  • Not everything can be quantified

  • Building representative samples is difficult

 

A mixed methods approach

A wholly qualitative approach is unlikely to result in a report full of statistics. At the same time, if you collect data using rating scales or yes and no questions, you’re unlikely to have the rich information that adds nuance to your analyses and creates the narrative you need to help share your impact story. We suggest thinking about how you ensure a balance between qualitative and quantitative methods. 

Ask yourself: what sort of evidence/information would I or my stakeholders find convincing in support of the impact claims? When one of our authors asked this to interviewees in research she was conducting, a large majority said that it’s more convincing to have statistical evidence as well as real more qualitative case studies. That is to say, a mixed methods approach where you balance numbers and insight.

Quiz - test what you understand

  1. You want generalisable data that can be compared exactly to data collected by other people. Will you want to use a qualitative or quantitative method?

  2. You want to ask only a few questions to a large group of people in a fast, simple way. Will the method you choose be qualitative or quantitative?

  3. You want to understand how someone behaves or reacts in a certain situation in the library. Will the method you choose be qualitative or quantitative?

  4. You know that your funder wants to see hard facts and percentages that can be easily quoted and shared. Will the method you choose be qualitative or quantitative?

  5. You want to report on both what happened and why. Will the method you choose be qualitative or quantitative?

 

  1. Quantitative data is easy to compare to data collected by others. Standardised indicators or questions help with this.

  2. Quantitative. You might use a pop-up survey.

  3. Qualitative. You might conduct an observation to understand the differences in behaviour.

  4. Quantitative data - the numbers - will be effective in this situation. But don’t forget that individual perspectives - which you can include as quotes - can be effective and are often more meaningful, too. You might take a mixed methods approach to help you deliver this balance.

  5. Mixed methods approaches will help in this case, and in most cases!

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