Everybody is talking data in online industries, but how can organisations harness these insights and turn them into real sources of competitive advantage?
One way is by blending statistics and machine learning techniques with scale.
At Thoughtworks Live Australia Jonas Jaanimagi, head of media strategy and operations at realestate.com.au, and I talked about how we are using machine learning and analytics to gain greater insights into the intents of the visitors to realestate.com.au, starting with first-time home buyers.
As with all websites, visitors to the REA website generate huge amounts of data. If properly harnessed, this data would help people on their property journey through REA, but only if you can create the right consumer experience.
“What we are doing as a company is supporting that very human journey that people go on,” Jonas said. “To do that, we needed to learn more about the consumer experience in this age of digital transformation.”
Jonas and his team at REA worked with our developers to use machine learning in the execution and process, allowing machines to do the work and people to focus on the creative. The team ran real campaigns with real clients to move from experimental and trial usage to actual programs, quickly. The team was then able to identify the patterns and behaviours of first home buyers with increasing levels of accuracy.
Here’s a few things that helped us get started:
Know your audience. Who are they? What motivates them?
Start small, learn from failures.
Stay skeptical and test your assumptions.
Create value as early as you can.
It's amazing what can be achieved by combining data and statistics experience, knowledge and awareness of the consumer and engineering expertise. We must all prepare for a data-driven future. Get in touch with us if you have questions about a data project or machine learning at your organization.
Watch the entire 45-minute-talk for more details on the results the REA group is experiencing.
Disclaimer: The statements and opinions expressed in this article are those of the author(s) and do not necessarily reflect the positions of Thoughtworks.
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