Why Greenhouse made the switch to ModeHow Python Notebooks, Helix, and a friction-free workflow enable Greenhouse to analyze and act on critical business insights
Greenhouse wanted a platform that balanced a powerful and flexible workflow with business stakeholders’ need for accessibility.
Mode enables Greenhouse to deploy the best infrastructure for each part of its data stack. Data scientists enjoy a frictionless workflow, while empowering all users to explore.
Greenhouse’s data science team builds predictive models for critical performance indicators. Using Helix, stakeholders can explore data on their own, saving the data science team hours every week.
From the very beginning, the team at Greenhouse knew that data-driven decision-making would be a core competitive advantage for the organization. As the company scaled, the appetite for data grew until senior data scientist Andrew Zirm was brought in to architect a new backend powerful enough to support the growing team. After test-driving the leading analytics platforms available today, Zirm chose Mode for its power, flexibility, and comprehensive approach to driving business value from data.
Choosing a flexible approach to building a data stack
Tasked with finding a platform that would create more data-influenced conversations, Zirm was disappointed to find that implementing many of the leading analytics platforms available today would require substantial changes to Greenhouse’s existing data stack. Tools like Looker, for example, do not allow for a modular approach, limiting a company’s ability to bring best-in-class tools into each part of its data architecture.
“You want to use the sharpest tool for each part of the stack,” he says. “Mode sits nicely on top of our existing infrastructure and is compatible with our backend. No other solutions were as aligned philosophically—or by cost structure—than Mode,” he added.
No other tools were as aligned philosophically—or by cost structure—than Mode.
Where data science and business intelligence meet
Andrew also wanted a platform that was completely aligned with SQL, his team’s preferred programming language. His data science team could write SQL directly in Mode and access their results in a native Python notebook with one click. This allowed them to share Python-powered reports with anyone, instantly.
Mode had access to data and had the Python notebook. Because of this, we could move quickly—it was low friction to get started.
“Mode had access to data and had the Python notebook. Because of this, we could move quickly—it was low friction to get started,” Zirm says. Not only could the data science team dive into ad hoc or exploratory analysis more easily, they could also use the same analytics platform to deliver dashboards and reporting to business partners, too. “This is not the case with other tools that are just using drag-and-drop technology,” he added.
Moving faster while doing more with Helix: Churn prediction
At Greenhouse, Mode makes data work easier for everyone. The company leveraged the platform to develop a system for predicting one of the most critical key performance indicators in B2B—customer renewal or churn rates. Mode made it easy to build a predictive model around that finding that now lives in a Python notebook the data team shared with customer success. The team can use the model to predict if customers are likely to churn well in advance of their renewal data so they can take action in the critical months before losing a customer.
Greenhouse’s early vision of having all of their teams empowered with data became a reality thanks to Mode. Now they can do even more, even faster with the addition of Helix, the first instant, responsive data engine that joins modern business intelligence and interactive data science. With Helix, data science teams no longer have to choose between shipping fast, one-off answers and building dashboards for broader coverage, while stakeholders can explore on their own.
Weeks of time saved on dashboard development
Because Helix enables Mode users to export findings in an explorable format, it has the power to save hours of time for data teams like the one at Greenhouse. For example, Greenhouse’s dashboards built in Mode often included numerous parameters to account for different views business stakeholders might request and the data team would re-run their queries every time a business user came back with a question. With Helix, that’s all self-service now.
“Helix is saving us weeks of development time because we can build new dashboards quicker than ever before,” says Zirm. “Marketers, PMs, and executives are also discovering new opportunities and asking new questions. Sometimes you don’t know what you’re looking for until you see it. ”
Helix is saving us weeks of development time because we can build new dashboards quicker than ever before.
These days, business units at Greenhouse can now explore self-service metrics with ease while the data team enjoys a frictionless workflow that enables deeper analysis—all on Mode’s single, powerful platform. This combination enables the company to answer critical questions that drive the business forward.
“We can predict the future better than our competitors,” Zirm says. “Mode offers the shortest path to value for anything data-related right now,” he added.
Mode offers the shortest path to value for anything data-related right now.