GlossGenius democratizes access to their marketing, support, app, customer engagement and sales data across the organization with Fivetran’s fully-managed approach to data movement.
- Easily migrated from Stitch to Fivetran
- Data engineering team is able to meet SLAs for data uptime (daily) and issue resolution/latency with 99.9 percent confidence
- All teams now have greater access to the data products they need to run their business
- Pipeline: Fivetran
- Sources: transactional database, marketing sources, financial sources, engineering sources, customer support sources
- Destination: Snowflake
- Transformations: dbt Cloud
- Data Visualization: Looker, Hex
- Cloud: Google Cloud
GlossGenius is a platform that enables business owners to reach new heights by growing their business and maximizing their income. Their complete set of automated appointment scheduling, payment processing, same-business-day transfer, client management and built-in marketing solutions were designed to empower professionals to focus on being creators, not admins. They believe technology can help members of the beauty community reach their full potential of entrepreneurship.
Their platform has been a boon for the industry. They process more than $2 billion annually for more than 50,000 customers. This success has allowed them to raise $44 million in funding, and garnered them accolades such as Forbes' inclusion in the fintech 50.
To help them manage this growth in business, and data, the team hired Emily Hawkins in February 2023 to join a team of two data engineers as the new data engineering manager. They are now a team of four data engineers, and their mission is to empower all data consumers to use data to deliver high-quality data products, analysis, and decisions, by providing reliable, scalable, and secure data infrastructure and tools.
To enable that data democratization, GlossGenius recognized they needed a fully modern data stack that could handle their growing data. They needed better data available in a more timely manner, for analysis, business optimization and growth. And this data centralization needed to be done efficiently without sacrificing simplicity or trust.
In early 2022, the data engineering team was using Stitch for data ingestion. However, as the business grew, they found Stitch was not addressing their needs. They ran into a few key limitations:
- Stitch lacked the breadth of connectors they needed to centralize all of their data into their Snowflake instance
- The connectors they did support did not replicate all fields and were not fully documented via ERDs
- These connectors also often broke, requiring GlossGenius to engage support, as they couldn’t debug on their own
- While Stitch provided variable ingestion methods (e.g. log vs non-log based), a wrong choice led to data integrity issues and errors in reporting
- A lack of alerts and notifications meant the data engineering team was not always aware of new tables or columns being loaded
“Debugging issues in Stitch was sometimes challenging, either due to lack of details in logs, or ambiguous ownership of integration problems between Stitch and the data provider.” - Brian Hart, Head of Engineering, Service Lines
The data engineering team found they spent a substantial amount of time maintaining and QAing data. This detracted from their ability to provide the organization with the quality, timely data they needed. Moreover, it did not optimize the modern data stack they had set up with Snowflake, dbt™, Looker, Hex and Segment. They had invested money in their stack, but needed the best-in-breed data movement platform to unlock its full potential.
It was with this goal in mind that GlossGenius began evaluating other data ingestion tools. They considered AirByte and direct connectors into Snowflake, but wanted a fully-managed approach that didn’t require infrastructure maintenance on their end. They also wanted a solution that worked right out of the box.
That’s what they found when evaluating Fivetran. Fivetran was already a known entity to them and came up when they searched for low/no-code, fully-managed data automation. Fivetran perfectly aligned with their growth, automation and efficiency goals.
Given the breadth and ease of use of Fivetran’s connectors, GlossGenius was able to quickly migrate existing data sources from Stitch without missing a data point. Plus, they could begin planning for additional sources they had on their near term roadmap.
Data was moved with more integrity and efficiency thanks to Fivetran’s schema drift and CDC features. The number of errors and issues decreased, freeing up data engineering time to work on higher impact projects.
GlossGenius migrated the majority of their sources from Stitch to Fivetran and now use 12 connectors to move 25 million rows of data daily from SaaS and database sources into Snowflake. Those connectors vary across different teams and help solve various use cases, such as: marketing optimization, customer outreach and support, app performance and customer experience, and core GlossGenius business analysis.
This enables teams to more effectively meet their goals:
- Marketing and GTM teams have a view of how their campaigns lead to customer engagement. They then send that data using reverse ETL processes back into their CRM system to do audience segmentation and engagement analysis, ensuring their marketing budget is spent efficiently
- The Product team analyzes customer engagement and support data to optimize the customer experience and make it as smooth as possible. They can then more easily measure customer satisfaction thanks to the reporting enabled by the data.
- The Executive team now has accurate, trustworthy reporting with company performance metrics like conversions, gross revenue and GTV/GPV
Emily and the data engineering team are able to meet SLAs for data uptime (daily) and issue resolution/latency with 99.9 percent confidence. This, all while focusing on improving the data platform - like Snowflake organization optimization for self-serve usage - and implementing new security and governance protocols.
In Emily's words, "We now move data from all of our sources into one Snowflake instance in a standardized, secure manner. All teams that rely on data now have one source of truth that they can build off of. This ensures there are no data errors while also democratizing access to data in a more self-service manner. Teams can build the products that the business users require without having to rely on data engineering for pipeline build or maintenance.”
And Emily says there’s more to come with Fivetran. They plan to utilize more of Fivetran’s recent security and PII features to further build trust into the data stack. To definitively get a handle on alerts and notifications, they are setting up the Fivetran Log connector to better manage issues, utilization and increase visibility into costs.