Data Probes

Josh Greenstein

Coming up with a relevant data probe for housing affordability was quite a difficult task. It was especially difficult when I knew my two participants, Chloe and Ting, were both in their early 20s and wouldn’t have had to think much about the issue thus far in their life. Given this early hurdle, I turned the situation around and had my participants get actively involved in the issue, and I was able to craft a probe that allowed me to attain relevant information from them. I gave them a ‘do-it-yourself’ bar graph, with ‘age’ on the x axis and ‘ideal house value’ on the y axis. I then instructed them to draw the graph, indicating their ideal house value at different ages throughout their life. The graph can be seen below.

Screen Shot 2016-08-29 at 5.30.32 pm

Then, the participant was to describe this idealised property, answering three questions.

Where is it?

How many bedrooms, bathrooms?


While getting an understanding of where my participants see themselves in a few years is rather pleasant, it was important to see if these idealised properties were actually possible given today’s housing affordability landscape. They were then to go on a Sydney property website, like or, and try find a house exactly like the one they had described using their site’s search filter function. If they did indeed find these homes in their searches, they were to answer the question ‘Is this the sort of property you had in mind? Would you live here?’ to see if their found houses live up to the expectation of what they initially thought.

Here are my participants resultant graphs.


Screen Shot 2016-08-29 at 5.49.31 pm.png


Screen Shot 2016-08-29 at 5.50.13 pm

It’s quite interesting to see the similarities between the two graphs. Both participants would like an inner city apartment for their late 20s, but have grossly underestimated the cost of such a place. Both ‘family, settled down’ properties hover around the $1m, $1.25m mark and remaining there until their 50s before retiring in a downsized property. Here are some quotes from my participants about the properties they selected.


‘That first house is so bleak’

‘I love the second house that would be a fun time’


‘It’s in the right price range but so tiny why so small and expensive I guess I would begrudgingly live there’

‘I’m very happy with my castle hill house’

What I think is most important with this sort of data probe is that my sample size was incredibly small. Taking two female graphic designers in their early 20s, it’s not shocking to see the results be so similar. If I were to do this sort of probe again, I would expand it to a larger selection of faculties and education. Keeping the age of my participants around 20-25 would allow for a wider range of ‘aspirational homes’

I think the value in a data probe like this can’t be overstated. Firstly, it educates and informs people that may be unaware of the issue of housing affordability in Australia. By having them estimate what their ‘ideal home’ might cost, it can shed some light on this important issue for them. It may be harsh, but having them realise the brutal reality of housing affordability in Australia might help them in the long run.

5 Key Points

  1. As far as my target audience is concerned, they’re not particularly aware of the issue of housing affordability.
  2. People are realistic about the ‘quality’ of their home in their early 20s,
  3. Despite this,  they’re unrealistic about the price these homes will cost.
  4. ‘Inner city apartments’ appear to be all the rage amongst 20-something designers.
  5. Downsizing for retirement seems like a popular choice, but would require owning a property at some point.