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Help for Heroes commissioned M.E.L Research to develop a detailed supporter segmentation of the UK charity-giving public, focusing specifically on individuals who support – or could be encouraged to support – military and veterans’ charities. The charity sought an evidence-based understanding of the motivations, behaviours and communication preferences of potential supporters, with a view to strengthening engagement, improving message resonance, and ensuring its offer aligns with what matters most to supporters and prospective supporters.

A significant driver for this work was the fragmented and highly competitive charity marketplace, in which Help for Heroes needed to understand how to position itself more effectively. The charity also recognised gaps in public awareness and understanding of veterans’ issues, and wished to explore how communications could better address perceived barriers. Reaching “in-market” supporters – individuals willing to consider donating to a military or veterans’ charity – was central to the study, but the work also considered “out-of-market” groups (those unlikely to support) to understand overall population proportions and contextualise findings.

The project required sensitivity due to the nature of topics covered: personal motivations, views on veterans, charitable giving, and barriers relating to trust or perceived lack of relevance. Reaching both supporters and rejectors of veterans’ charities posed its own challenge, particularly where attitudes were strongly held.

The segmentation was developed through a multi-stage mixed-methodology, combining qualitative exploration, large-scale quantitative research and advanced statistical modelling. Each stage built on the previous, ensuring that the final segmentation reflected evidence rather than assumptions.

1. Existing Data Review & Stakeholder Engagement
M.E.L Research reviewed existing internal data, previous qualitative insight, wider market evidence and stakeholder knowledge held within Help for Heroes.

A facilitated stakeholder workshop allowed internal teams to share existing perceptions of supporters, articulate challenges and begin shaping the scope of the segmentation.

2. Online Qualitative Community (n=25)
A one-week online community explored broad life motivations through to specific views on charities and veterans’ support.

Participants discussed worldviews, drivers, current behaviours and attitudes towards Help for Heroes.
Insights from this stage informed questionnaire design to ensure the quantitative phase was grounded in real supporter language and real-world motivations rather than internal assumptions.

3. Quantitative Market Survey
Nationally representative survey of 1,000 “in-market” respondents, defined as those who currently support or would consider supporting a charity and who were open to supporting a military/veterans’ charity.

An additional sample of c.1,500 “rejectors” of veterans’ charities was asked a shorter series of attitudinal questions.
Weighting ensured the whole-market sample was representative by age, gender and region.

Approximately 400 variables were captured covering motivations, attitudes, behaviours, charity perceptions and Help for Heroes awareness.

4. Statistical Analysis & Segmentation Modelling
M.E.L Research conducted a multi-stage statistical process to derive robust and meaningful segments:

5. Persona Development Workshops
Stakeholders reviewed the emerging segments, explored practical applications, and co-developed working personas.

Exercises supported teams to start applying the segmentation to real decision-making, messaging and tailored approaches.

6. Pen Portraits & Final Reporting
Detailed pen portraits were developed for each segment, using quantitative data, attitudinal patterns and further qualitative depth-interviews.

The final deliverables included a written report, detailed segment descriptions and modelling outputs.

Outputs

Analytical Outputs
M.E.L Research undertook:

The segments produced included:

Formats Delivered

The segmentation enabled Help for Heroes to:

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