A street scene featuring historic buildings, shops, and outdoor seating. Clear blue skies and a church spire in the background enhance the inviting atmosphere of the area.
Sincil Street, Lincoln © Historic England Archive View image record DP393440
Sincil Street, Lincoln © Historic England Archive View image record DP393440

Data Collection Methods Toolkit

When it is done well, evaluation can help us understand how our work makes a difference. Through evaluation, we listen, learn, and work together to create better places and services. 

This resource has been designed to help you collect and make sense of evidence of the social impact of your heritage project.

Here, we share some ways to collect and make sense of the data and stories you gather. We have provided links to resources that offer the practical support needed when using these tools for evaluation.

Data collection methods

Select from the methods below to collect and make sense of data. They can be used as part of an evaluation of your heritage work.

To learn more about creative and participatory evaluation methods, there are more comprehensive guides available from:

Survey question bank

When you are creating a survey you must make sure you are using quality questions rooted in evidence. To help with this we have provided a question bank which you can download.

The questions are grouped in sheets that correspond with the 6 areas of social impact for heritage. Choosing questions will be easier if you have already decided which indicators are most relevant to your project's aims. 

Simply select the questions that will work best for your chosen indicators and survey audience. 

Creative evaluation prompts

You can also use the survey bank when you need to write open-ended questions. You will need these for the more creative and participatory evaluation methods like the wall of words, photo stories and experience mapping methods.

For help writing open-ended questions, first download the social impact survey question bank. Take questions with yes/no answers or rating scales and rephrase them as prompts that invite participants to share their personal experiences, feelings, or reflections. For example:

Indicator

Survey question

Prompt

Loneliness

Have you met new people or made friends at events or exhibitions organised by us?

Is there someone you’ve connected with through this place or event? Tell us about them.

Belonging

I feel more part of the community after visiting (this organisation or event).

What makes you feel like you are part of something? Did anything here today remind you of that?

Community identity

(This organisation) plays a role in shaping the community’s sense of identity.

How would you describe your community to a visitor?

Social networks

Volunteering increased the number of people I know…

Have your social circles changed since you started volunteering? If so, can you tell us how?

Cohesion

Do you think this place has brought people together?

Can you share a moment when you saw people from different walks of life connecting here?

The importance of rigour

Rigour means collecting and making sense of data carefully, thoughtfully and appropriately. It means:

  • Finding and following good practice advice
  • Using good and trustworthy information sources
  • Explaining how you arrived at your results 
  • Making it possible for others to check or repeat the work
  • Being fair and not letting personal opinions affect the results
  • Not asking leading questions
  • Not only focussing on the positives
  • Being honest about what did not work well

Rigour matters because it ensures you are truly measuring what you intend to measure. For example, if 95% of people rate your facilities as excellent, but your evaluation lacks rigour, you might overlook underlying issues that still need improvement.

A rigorous approach benefits you by providing reliable and meaningful data that reflects reality, not just superficial impressions. When data collection is designed and carried out with rigour, the results can be trusted and used confidently to inform decisions and drive improvements.

Evidence and claims

Whichever tool you use, creative or otherwise, respect the limits of the evidence you generate. Be careful not to overstate your impact or make claims that your data does not support. Honest data collection and reporting builds credibility and fosters genuine learning. Overselling your impact can damage trust and jeopardise future funding.

Example: interpreting evidence 

Scenario

A local heritage organisation restores a historic building and opens it for community events, workshops, and cultural programming. The organisation conducts a survey 6 months after reopening.

What the evidence shows

Surveys indicate that 70% of attendees report feeling more connected to local history, and several community groups now use the space regularly. However, the data is mostly qualitative, and the organisation has yet to measure the long-term social impacts (such as, increased civic engagement or economic benefits). The organisation did not collect any data before the restoration started, so there is nothing to compare the data to.

Overstating the impact

To claim that "The project transformed the community, significantly increasing civic pride and reducing social isolation across the region" would be an overstatement.

This claim assumes broad, long-term effects not supported by short-term or anecdotal evidence. It also attributes regional changes to a single project without sufficient data.

Making a credible claim

"Early feedback suggests the restored heritage site has helped many residents feel more connected to their local history. Community use of the space is growing, and ongoing evaluation will help us better understand its wider social impact over time."

This version accurately reflects the evidence, avoids overclaiming, and signals a commitment to continued learning and honest assessment.

Evaluation resources