Method

Thematic Analysis

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Thematic Analysis is a method for systematically analysing qualitative data. Its purpose is to identify recurring themes, patterns, and meanings within interviews, statements, notes, or participation results. Unlike Topic Mapping (Affinity Mapping), the data are not only organised but also carefully analysed and interpreted.

Goal

The aim of Thematic Analysis is to identify recurring themes and patterns within qualitative data. The method helps reveal which concerns, needs, challenges, or expectations occur most frequently and what they mean for the subsequent planning or decision-making process.

When useful?

large amounts of qualitative data need to be analysed.
recurring patterns and themes should be identified.
participants' interests, needs, or challenges need to be better understood.
the results will inform decisions or future participation activities.
the aim is not only to organise the data but also to interpret what matters most to participants.

When not useful?

only a small number of statements are available.
only numerical or statistical data need to be analysed.
predefined categories already exist and no open-ended analysis is required.
results are needed quickly and there is insufficient time for an in-depth analysis.

Process

Collect all relevant materials, for example:

interview transcripts
interview notes
workshop documentation
moderation cards
responses to open-ended survey questions
observation notes

The more complete the data set, the more meaningful the analysis will be.

Before starting, consider:

What do we want to find out?
Which insights are we looking for?
Which future decisions should the analysis support?

Examples include:

"Which challenges are mentioned most frequently?"
"What needs do participants express?"
"Which topics are most relevant for further planning?"

Read through all available material carefully before beginning the analysis.

Avoid creating categories immediately. Instead, develop an overall understanding of the data.

Helpful questions include:

Which themes emerge?
What is surprising?
Which statements occur repeatedly?
What concerns participants most?
Which challenges or wishes are mentioned?
Which statements stand out?

Highlight important statements or passages in the text.

Assign short descriptive labels (codes) that summarise their meaning.

Examples:

Statement: "There are not enough safe cycling routes."

Code: Cycling infrastructure

Statement: "I would like more places where people can meet."

Code: Meeting places

A single statement may receive more than one code.

Look for codes that relate to one another.

For example:

Mobility

cycling infrastructure
public transport
road safety

Public Space

quality of public spaces
greenery
seating

These groups form the first broader topic areas.

Review the coded data and identify broader themes.

Helpful questions include:

Which themes occur most frequently?
Which themes are connected?
Which themes are particularly relevant to the research question?

The themes should not simply describe what participants said, but also explain what the statements mean in a broader context.

Check the emerging themes carefully.

Consider:

Do the statements really belong to this theme?
Are there overlaps between themes?
Are important themes missing?
Are the theme names clear and understandable?

If necessary, merge, split, or rename themes.

Finally, describe and interpret each theme.

Example:

Many participants expressed a desire for higher-quality public spaces. Seating areas, green spaces, and places for social interaction were mentioned particularly often.

This stage creates the real value of the analysis. Individual statements are transformed into meaningful findings.

The final result is not simply a collection of individual statements, but a structured analysis of the most important themes and patterns.

Possible outcomes include:

key themes
recurring needs
challenges
wishes and expectations
patterns and relationships
recommendations for action
a basis for political or administrative decision-making

The results help reduce large amounts of qualitative data to their most important insights in a clear and understandable way.

Unlike Topic Mapping, the focus is not on organising statements but on interpreting their meaning.

The findings can subsequently be presented in reports, presentations, topic summaries, or recommendations for action and often serve as a foundation for further work by public administration, policymakers, or project teams.

Source: Kerr, J., Cheers, J., Gallegos, D., Blackler, A. & Kelly, N. (2023): The Art of Co-Design: A Guide Through Creative Collaboration. BIS Publishers.

Notes

Tips

Use participants' original wording whenever possible.
Clearly document how themes were developed.
Work as a team on larger projects.
Reflect critically on your own assumptions and interpretations.
Look not only for frequently mentioned issues but also for unexpected perspectives.
Review the themes several times.
Document intermediate steps and important analytical decisions.

Not suitable for

only quantitative data are available.
only a quick organisation of results is required.
the amount of data is very small.
no interpretation of the statements is desired.

Afterwards

Afterwards, methods that organise, deepen, or translate the gathered content into concrete steps are useful. Depending on the goal, the following formats can follow, for example:

Collaborative Analysis

Collaborative Analysis is a method in which results are not interpreted solely by experts or project leaders but together with the people who participated in the data collection or engagement process. The aim is to incorporate different perspectives into the interpretation and ensure that findings are understood not only about participants but with them.

SimpleStructured

Sensemaking

Sensemaking is a collaborative method for analysing and interpreting information, observations, and participation results. Unlike scientific analysis, it does not focus on systematically coding data or conducting statistical evaluations. Instead, it aims to identify patterns, relationships, themes, and insights in order to develop a shared understanding of a situation.