Layer 4. Sort and reflect – insights into popularity
The fourth layer asks participants to step outside of their own preferences to reflect on what is or is not likely to be popular locally.
How popular development is likely to be when looked at in the round can provide a further useful insight into perceived preferences. But popularity is a slippery concept, particularly if expressed in absolute terms, such as: ‘style A is more popular than style B”. The fourth layer consequently avoids asking participants to rank projects against each other and instead asks them to step beyond their own preferences and sort a range of developments according to whether they believe they would be ‘popular’ or ‘unpopular’ with local residents. In this way the layer provides both a useful check against the more personal results from the other layers and good insight into what is or is not perceived to be popular.
Step 1: Select a Representative Range of Images
Avoiding images used in previous layers, select photos that together encompass a broad range of possible residential environments within the context being examined. Like the 14 suburban images used in the example, these should:
• Vary in density, building types, and architectural styles
• Show groups of buildings or street scenes, rather than single dwellings
• Reflect replicable rather than exceptional one-off projects.
Like those in Layer 3, images will need editing in order that participants focus on the development itself by removing distracting elements such as people in the foreground and ensuring consistent weather conditions across the selection.
Step 2: Ask participants to sort the images
In contrast to the previous layer, Layer 4 requires the delivery of images one at a time in order that participants can sort them into three virtual boxes within the surveying platform:
1. Unpopular
2. Neutral
3. Popular
A simple clear instruction should request: “Sort the developments that you see according to whether you feel they would be ‘popular’ or ‘unpopular’ amongst local residents by dragging and dropping them into the three boxes.”
Step 3: Ask participants to reflect on their judgements
Only after sorting all the images, participants should be invited to reflect on their reasoning by asking: “What factors influenced your choices and therefore your perception of popularity?”. An optional open text box should be provided for the collection of these responses which will help to understand how participants interpret the likely acceptance of different design responses locally.
Step 4: Calculate an overall popularity score
To calculate popularity, a simple scoring system can be applied to the selections: unpopular (1); neutral (2); popular (3), with average scores calculated for each image and compared across participant groups. In the example this can be seen for councillors (bottom left) and planning officers (top right) in urban contexts. As before, colours can help to visualise the results:
• Blue indicates the most popular developments
• Green indicates the second most popular
• Yellow indicates predominantly neutral responses
• Orange indicates the second least popular
• Red indicates the least popular
Step 5: Interpret the quantitative results using qualitative insights
Insights from the reflections can give a richer understanding of the scores. First, analyse the open-text reflections by coding each and grouping the responses into key themes. Then compare this with responses across the full set of images by looking for:
• Majority and minority views
• Strength of perceptions
• Consistency of perceptions across different contexts (e.g. urban vs suburban) and stakeholders (e.g. councillors vs officers)
Using multiple image sets and participant reflections can help to reveal both the depth and the range of perceptions, strengthening the overall analysis about what makes residential developments appear acceptable or unacceptable to observers and communities.