Aalto Drives a Direct Real Estate Marketplace with Data
How a real estate startup scales data insights, increases data accessibility for staff and customers, and increases product speed.
Aalto is a real estate marketplace that lets people buy and sell homes online. They combine modern technology with a centralized team of licensed agents. This online model provides a consistent, high quality experience while costing less to operate, so buyers and sellers save money with low fees and rebates.
Aalto uses Mozart Data for internal data-driven decision making and to generate insights to share with customers. By using Mozart they were able to quickly gain data observability, fix errors in their data stack themselves, and empower their product teams to answer their own questions with self-service dashboards – all without needing a dedicated data engineer.
Upgrading ETL to gain data observability
Before they started using Mozart, Aalto was struggling to connect multiple data sources using Stitch and BigQuery.
Due to the nature of their real estate business, Aalto needed to join multiple external data sets and run computationally complex queries. Their data stack included a PostgreSQL database, the Segment customer data platform (CDP), Facebook data, Google data, and a CRM. As a result of the complexity, it could take queries 15 to 30 seconds to run – longer than a typical ad hoc query.
When Nathan Mayer, BizOps at Aalto joined the team, he immediately saw a data strategy that wasn’t working.
“With Stitch, it actually took a lot of work to be able to start to spin up data sets. And once something was down, I couldn’t go solve it upstream,” Mayer said.
Once Aalto started looking for data integration solutions, their search was short. Aalto picked Mozart because it provided a powerful and elegant way of managing incoming data sources, added observability features, and had virtually no learning curve for users with SQL skills. Mayer was able to connect data sources himself and provide self-service data resources to all of his co-workers without needing to hire a data engineer to manage data pipelines.
Finally, Mozart stood out because it was user-friendly and Aalto found it far less expensive than keeping their current system. Mayer notes, “If you were going to pay for any of the services that Mozart offers as a managed service, you’d already be out more money than the cost of Mozart.
Accelerating internal analytics and surfacing market data to users
Because Mozart provides a pre-built data stack, Aalto was able to immediately centralize all their data in a data warehouse without needing to worry about designing pipeline architecture or hiring someone to manage it.
By changing technology, Aalto rapidly decreased the time-to-insight while also reducing manual data engineering tasks. Mozart enabled Aalto’s BizOps team to avoid spending their time manually setting up sessions, pipeline lineage, and data observability tasks. Instead, they could directly focus on improving the value of their data by curating it and getting it into the hands of teams faster.
Mozart allows a single admin to go in and make quick changes to the data pipeline without needing to work through dependencies and wait for other teams to respond. Mayer says, “With Mozart, you have a single individual contributor who’s able to find a data source, connect it, and create a production-ready dashboard in like an hour. One of the engineers said to me, ‘Hey Nathan, don’t tell the rest of the engineers how easy it is to get data into the database and usable quickly. They think I’m a genius using this.’”
By providing a means for technical and less-technical users alike to easily craft self-service dashboards and reports, Mozart can scale the benefits of centralizing and curating data in a data warehouse. Mozart didn’t just provide a single internal resource, it enabled a single user to scale data insights out to all teams.
Due to its ease of use, Mozart has become a central pillar of Aalto’s data strategy. Aalto uses Mozart to bring data from a variety of real estate sources together for internal use and their customers. They combine their platform event data with property-level data to identify trends in the marketplace and share comparable home data with customers in their product.By connecting data sources, Mozart enabled internal teams to answer complex questions such as how marketing spend affects downstream success in the application. Aalto has future plans to use data from Mozart to guide their software development life cycle (SDLC).