“How does your income compare to everyone else’s” is an interactive tool which offers users a surprising look at their own position on the income spectrum.
Users are asked to guess where they sit and then enter their weekly income. The tool reveals whether or not they were correct — most were not, in line with recent research.
After establishing the reader’s position, the interactive takes them on a visual journey which compares them to the very richest Australians — the 3.84 per cent who earn above $A156,000 a year, or $A3,000 a week, before tax.
Over a million people viewed the piece across ABC platforms, and it was widely shared on social media. In an environment where many Australians likely felt hard-done-by without wage increases for many years, the tool provided them with a perspective that they were unlikely to see otherwise.
Recent research shows that people are terrible at estimating where they sit in terms of money relative to others. Poorer people tend to overestimate their relative worth, whilst richer people tend to underestimate. This is related to our psychological tendency to see our own position as average, and our inability to see the bigger picture.
This was backed up by the data we collected when people used our tool. Only 11 per cent of respondents correctly guessed within the range of their income bracket. The vast majority of people underestimated their position — in short, they were relatively richer than they thought they were. We were able to produce another piece of original work using this data, which told an interesting story about our audience.
The most telling thing about the success of the project is that the data which underpins it (the 2016 census) had been available for over a year for anyone to look at. All we did was take the data and put it in an easily digestible format which told the reader a surprising personal story which was well-visualised and easy to understand.
In the months after our story, many other news outlets published similar explainers, both in Australia (eg. Sydney Morning Herald) and overseas (eg. New York Times).
- Data analysis: We used the Australian Bureau of Statistics’ Census Table Builder to extract all of the data from the 2016 census, including cross referencing income data with demographic data. From here, we used simple Excel spreadsheets to tease out the most interesting findings.
- Personalisation: We asked users for only three simple inputs — their weekly take-home pay (after tax, to keep it simple), their postcode or suburb, and a guess of their position. From these simple inputs, we were able to tell a completely personalised story which had national significance.
- Scrollyteller design: We utilised the user’s scrolling to step them through the geographical data, allowing words and visualisations to be presented in a perfectly complementary design.
- Data visualisation: Simple but tried and true techniques — choropleth maps and dumbbell charts — with a personal touch.
What was the hardest part of this project?
The team had endless discussions about the design of the tool, how it would function, and how it would present its results. Deciding how to tell the geographical story was especially fraught — Australia is an enormous country with a geographically spread population. The question was, how could we make the national picture relevant to them?
The centrepiece of our visualisation was a choropleth map of Australia, colour coded with the proportion of high income earners in each Local Government Area of Australia. The problem we had here was a common one with choropleths of Australia — the big picture often obscures data in smaller areas.
To get around this, we built a ‘scrollyteller’ interactive which steps readers through the relevant information to them, moving them and zooming around the choropleth and highlighting details. The user enters their postcode or LGA, and is presented with the statistics and rankings for their area and their state, as well as the top and bottom LGAs for the measure. As the reader proceeds, data relevant to the statistics they are reading is highlighted; irrelevant areas melt away. It allowed us to show both the national and personal picture all at once, and counter the psychological predisposition towards the smaller picture in favour of the bigger one.
What can others learn from this project?
- The power of personalisation: Legacy news organisations often focus on the bigger picture because technology in the past did not offer opportunities to personalise. People love to be told a surprising story about their own situation, and how they compare to others — technology and new ways of telling stories can facilitate this. You just need to think outside the box.
- Just because data can be accessed, doesn’t mean it’s accessible: The underlying data was available for more than a year online for anyone to access. If people wanted to, they could search through it to find out where they sat. But who has the time for that, or even the knowledge that it’s possible? We simply took the legwork out of the task and presented it well. The learning here is that data doesn’t always need to be exclusive or embargoed, it just needs to be interesting.
- As users access your data, they’re also creating data: If you’re asking users to enter data, be prepared to capture it as it can create good exclusive follows. Using the data collected from our readers, we were able to generate another story, read by another 280,000 people about how people are terrible at estimating their relative income wealth. This in turn drove even more people back to the original story.