Domain speeds time-to-decision by 80%

Domain, an ecosystem of multi-platform property solutions for residential, new development, and commercial properties in Australia, relies heavily on real-time data to make business decisions. Says Pooyan Asgari, Chief Data Officer, “We are operating in an extremely high-velocity market environment.”

Domain has about 300k properties for sale at any given time, and they reach almost 80% of the adult population in Australia every month through news, searching, or ownership services. They advertise roughly 6,000 new properties every day.

The data team at Domain is responsible for answering complex data questions to help departments across the business make better decisions. Separate from productionized dashboards, this analysis is used for specific, high-priority projects; it’s critical to helping other teams at the company move quickly and make the best decisions. The team of 30 quickly found itself fielding so many requests that they couldn’t keep pace with the demand. They needed to find a way to deal with the ever-increasing appetite for data analytics without slowing things down.

Asgari’s approach to alleviating capacity constraints was to decentralize Domain’s data organization model. His goal was to decrease reliance on his data team by enabling “data heroes” on individual teams to be as self-sufficient as possible.

Domain uses Tableau for standardized dashboards and reporting. The tool, however, was not enough for their analysts, who needed more advanced analytics capabilities, like a SQL editor and Python notebooks, to answer specific questions. The data team at Domain needed a tool that would allow data-savvy users within other departments to uncover insights independently: they wanted these users to be able to connect to a database, run queries, analyze and visualize trends, and ultimately make decisions, all without requiring the direct support of the data team.

Asgari explains, “A marketing manager that happens to know the basics of SQL or a product manager who is data savvy, but doesn’t necessarily have technical skills—we call these people data heroes. We now actively promote the use of Mode with individuals across the organization who understand the value of data even if they are not in technical roles. For those who want to get further into the details, Mode is the answer.”

Before Mode, a product manager (PM) who wanted to launch a new product would come directly to the data team for reports on adoption and engagement. The request would go into the data team’s queue, where it might remain for a week or more. Now, that same PM has a “data hero” within their department who can use Mode to query the data and conduct analysis on the product launch in real time.

Empowering people outside of the data team to use data to make decisions has sped up business processes and decisions across a 800-person enterprise. This change in workflow has saved the data team hundreds of hours that now go to more advanced, strategic projects. Additionally, because Mode is connected to datasets stored in Snowflake, the data team can be confident in the accuracy of the data being used by teams across the company.

This kind of agility has become critical in the era of COVID-19. “The COVID lockdown created an unprecedented demand for bespoke analytics within an urgent timeframe. Fortunately, Domain was lucky enough to have a robust set of analytics capabilities enabled by Mode already in place. Our team would have been bombarded by all 800 employees at Domain, but a good chunk of that pressure was removed, because teams could answer their own questions.”

Enabling stakeholders to identify opportunities and make data-driven decisions about where to focus has made Mode a key component of Domain’s modernized business operations.