Coupa accelerates its S3 Data Lake with Fivetran

The Business Spend Management company uses Fivetran’s data integration solution to better understand customer behavior on its SaaS platform
“The rich analysis that we enable provides real, actionable insights that matter — and this is critical to company growth." – Anna Lisboa, Senior Engineer, Coupa

Key results:

  • Coupa simplified its data integration workflow, enabling engineers, designers, and data scientists to readily identify opportunities
  • Fivetran reduces time-to-value for Coupa from 3-6 months to a matter of weeks
  • Fivetran connectors give Coupa complete 360-degree Analytics
  • Ability to continuously improve customer experience based on data-driven insights
  • 4x the number of data users and adoption with Fivetran
  • 3x the data and integrations to Coupa’s S3 Data Lake with Fivetran

Data Stack:

  • Pipeline: Fivetran
  • Connectors: Marketo, Salesforce, Netsuite, Jira, Coupa, Pendo, Custom API endpoints
  • Destinations: AWS RDS, AWS S3, Snowflake
  • Cloud Platform: AWS
  • BI: Tableau, Einstein Analytics, Anaplan, Athena / Presto for power users

Technical Challenges:

  • Pull and sync data from multiple applications and platforms in the cloud
  • Ensure data is accurate, reliable and up to date
  • Create and manage integrations without requiring engineering resources
  • Scale list of integrations to meet constantly evolving customer needs

The Situation

Coupa is a Business Spend Management (BSM) company that gives companies around the world the visibility and control they need to spend smarter and safer. Its cloud platform digitizes and consolidates spending information across travel and expense management, procurement, and invoicing — creating actionable insights into spending behavior. As a software-as-a-service (SaaS) platform, Coupa combines behavioral data with other data sources to improve the user experience. But just as Coupa’s BSM platform helps its customers by breaking down data silos across procurement, finance, treasury, and supply chain, Coupa’s own data about its platform and customer usage faced silos that were impeding better insights and better decisions. Collecting this data and getting it into the hands of the people who can take action is a complex, costly and resource-heavy process.

The Problem  

Coupa made a strategic decision by investing in a data team to get a better handle on its data. Thomas Rasmussen, Director of Technology, came to Coupa with more than a decade of experience and set out to reengineer Coupa’s data architecture from scratch. Thomas’ goal was to pull data from the Coupa app, Marketo, Salesforce, Netsuite and Jira into a single place where it could be used to create actionable insights into customer behavior and purchase patterns.

The problem was that the analytics strategy was immature and largely consisted of ad hoc procedures. If a UX designer wanted to know how customers were interacting with a particular feature or module in the Coupa platform, they’d have to make a request with the engineering team to build a script from scratch — a process that could take weeks. By then, the opportunity likely would have passed or the customer behavior might have changed.

“Customer information was spread out across the company in data silos, and there was no way to get a clear, holistic view of each customer and how they were interacting with the app,” Thomas said. “We had all this valuable data, but we couldn’t do anything with it. I knew on day one that we needed to build a new data pipeline that could break down these silos, consolidate the appropriate information and feed it into the business analytics engine where we could put it to good use.”

The Solution

Understanding that a business analytics data lake is only as good as the data that you feed into it, Thomas sat down with senior engineer Anna Lisboa to figure out the best way to pull the relevant information into the company’s warehouse. Anna introduced Thomas to Fivetran: a data integration solution that would allow Coupa to automatically create connectors from various data sources.

Rather than relying on an engineer to custom-build a script to interact with APIs from Salesforce or Netsuite, Thomas and Anna could simply enter their credentials in the Fivetran console and immediately start ingesting the data to Coupa’s data warehouse. Data analysts using the company’s business intelligence tool could then apply transformations to the data, and create actionable insights to inform critical business decisions.

“It was a revelation,” Thomas said. “Once I saw what Fivetran could do, I knew we were on the right track with solving our data problem. I just wish I had found Fivetran earlier in my career. It would’ve been so helpful with many other projects I had helped manage.”

Thanks to data ingested by Fivetran, analysts within Coupa can now make data-based recommendations to improve the capabilities and design of the business’ digital assets. Product engineers and UX designers can use this information to tweak and improve experience based on real interactions and trends — ultimately optimizing customer outcomes — and they can do so rapidly and iteratively enough that customer experience now improves rapidly.

“My job title says data architect and integrations, but what I really do is ensure customer success,” Anna said. “The rich analysis that we enable provides real, actionable insights that matter — and this is critical to company growth.”

Fivetran's Coupa-certified connector is available to Coupa customers on its App Marketplace, and reflects the open approach Coupa has taken to developing its platform and ecosystem.

Coupa is also a part of Fivetran's connector ecosystem, allowing companies to pull business spend insights from Coupa into their warehouse to be joined with data from other applications. This allows Coupa’s customers to better understand their business spend data, increase usage of the application and ultimately drive product growth.

“It is a really rich partnership,” says Anna. “The Fivetran team was great about reacting to feedback and making changes to the connector. It’s working really well.”

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