Greenhouse Software is an enterprise talent acquisition suite that uses intelligent, data-driven guidance to automate the hiring process and shorten time-to-hire.
To get a better understanding of customer engagement the data scientists at Greenhouse were pulling information out of the product database running in PostgreSQL on AWS. With no centralized data repository, the process was time consuming and required writing back end code to parse the data—code that would need to be updated with each new parameter request.
Instead of hiring additional data engineers, Greenhouse turned to Datacoral, an AWS Advanced Technology Partner. Greenhouse used Datacoral to build an AWS-native data infrastructure that collects data from the Greenhouse production database as well as Jira, Zendesk and Salesforce, then combines and organizes them with events received from the Greenhouse website and mobile app into a Redshift data warehouse. Greenhouse then equipped their application and APIs using Datacoral’s instrumentation libraries and Events Slice, which gave them the ability to understand the behavior of customers using their product. Once all of the data was in one place and Greenhouse had established the needed dashboards, the data science team used their analyses to make the rest of the organization smarter by publishing the analysis to Totango, a customer success product. All of these processes illustrate the power and value of a fully functioning, end-to-end, data pipeline which not only supports ELT best-practices, but also runs as affordable, severless Lambda functions, secured within Greenhouse's AWS VPC, orchestrating and managing the flow of data into and out of Redshift even as schema changes and data anomalies threaten the flow.
Director of Engineering, Greenhouse
"The datacoral infrastructure manages our entire backend data flow from collection from many sources, to analysis, to publishing back to the organization, allowing our data science team to deliver value to internal and external customers without worrying about tedious data plumbing."
Thanks to the Datacoral implementation, the customer-facing division of Greenhouse now has access to information like churn likelihood and product usage. Executive and sales teams can see the big picture of product usage and customer engagement. By standardizing their data pipeline, and automating monitoring and provisioning, Datacoral frees the engineering team for low level coding, saving time, reducing costs, and streamlining operations. Greenhouse data scientists have observed that their time invested in data has increased from 20% prior to Datacoral to more than 80% afterward, allowing them to add real strategic value. Datacoral adoption will also help the organization scale their Redshift-based warehouse into an Athena-based data lake, without any interruption to their data consumption demands. With Datacoral, Greenhouse also gains full advantage of AWS-best practices and assurances for affordability, availability, security, scale, performance and regulatory compliance.