Using big digital data as the basis of new products is an enticing prospect. But people – your potential users and customers – have complicated relationships to both technology and to changing their everyday habits. You need to understand the diverse motivations different people might have in relation to your products.
This case study explores the effects of various assumptions made by a platform- based startup about its potential users.
“Our aim for the platform is this,” the CEO of the Community Home Improvement Platform (CHIP) explains. “The UK’s housing stock is in a bad state. We want to help building owners like householders, businesses and landlords get a better deal on the materials they need to make improvements. We can use big data to identify needs, and social tools to allow individuals to aggregate into groups. Like this, consumers will get a better deal from installers, installers will save on marketing costs, and we’ll bring about positive change across the housing stock.”
A good start
When development kicked off, things were looking good. CHIP’s CEO and her team developed links with key people in the city they were working in. “We’re like a little Switzerland,” she said, “with friends and partners across the public, private and third sectors.” The team had thought about all the platform’s users, not just the wealthy ones. The platform identified discounts and government grants to help out those with less ready cash. But not everything was perfect.
This approach could exclude people by not engaging with what matters to everyone.
Motivation isn’t just about money
The platform thought about income diversity, but it wasn’t able to work with other kinds of social difference. Other social characteristics like age are known to affect motivation to have major building works done, with younger people put off by high costs and older people preferring to avoid disruption. However, the platform didn’t look at these. Instead, it understood motivation as just economic. In other words, people would only be interested if the works improved the value of their building, or if the work saved them money. This approach could exclude people by not engaging with what matters to everyone.
The platform was difficult to use, which discouraged the less tech savvy. Early in its design, the platform was targeted at individuals or community groups. However, during its development it became more and more complex. Eventually, the team decided that users should go through a technician provided by the platform rather than using it independently. This made it much harder to access.
We put in a lot of effort to help develop this platform because we’re worried about people living in substandard accommodation. It feels like we’ve wasted our time.
Community groups disappointed
Then, the platform’s designers changed direction. They decided to focus on selling only to large businesses like landlords, reducing their focus on communities considerably. “We were really disappointed,” said the leader of a community group. “We put in a lot of effort to help develop this platform because we’re worried about people living in substandard accommodation. It feels like we’ve wasted our time.”
So, this was a project with great potential at the outset. But over time inadvertent exclusion emerged in various ways. This reduced the potential client base the platform could have accessed and damaged relations with city partners who might also have attracted customers. It also reduced the social good which the business had first intended to generate.