Lendi makes data-driven decisions with Fivetran

Australian mortgage broker uses Fivetran to transform into a frictionless, data-driven business
“It’s so powerful to be able to go to our operations staff and say ‘we can get the data you need for your job much faster now.’ With Fivetran, we are able to focus our efforts on our core business data and not worry too much about moving data around.”
— Daniel Deng, Data Architect, Lendi

Key results:

  • Fivetran enables data-driven decision making for stakeholders throughout the company
  • Fivetran drives agile business model that allows the company to react quickly to market and competitor changes
  • Fivetran allows the Engineering team to focus on the core business rather than building custom data connectors on demand

Data Stack:

The Situation

With more than $12 billion AUS in home loan settlements, mortgage broker Lendi has helped thousands of Australians secure their property dreams. The company’s proprietary technology allows borrowers to search 2,000+ loan products from more than 40 lenders to find the best loan products for their needs. This unparalleled level of choice helps deliver the best possible customer outcomes while driving competition and transparency in the market. Despite the company’s technological advantages, the industry is fiercely competitive. The battle for customers is intense — and it’s almost entirely dependent on delivering the right experience to the right person at the right time on the right digital platform. This, of course, depends on reliable, accurate insights into borrowers’ needs and preferences.

The Problem  

Building an accurate profile of each customer requires tapping into behavioral data on third-party engagement platforms such as Facebook, Google and Bing. This data is readily available to Lendi, but the insights from each platform are siloed and don’t integrate very easily. Even when the data can be brought into the same repository, the data structure is often inconsistent, creating the need to clean the data before it can be put to use. Making sure stakeholders from across the company — marketers, accountants, brokers and customer service reps, for example — are able to analyze and create actionable insights from third-party data is the responsibility of Daniel Deng, Lendi’s Data Architect.

“My job is to make sure everyone has the information they need to create efficiencies, deliver superior experiences for customers and optimize their efforts,” Daniel said. “I need to make it as easy as possible to work with and analyze the data from various data sources.”

The Solution

Rather than ask engineering to build custom integrations with each third-party platform, Daniel relies on Fivetran, a data integration service with an extensive library of hundreds of connectors to Software as a Service (SaaS) platforms. Fivetran automatically pulls data from Facebook Ads, Bing Ads, Google Adwords, Google Analytics and other engagement platforms in near-real time, loading it into a data warehouse managed in the cloud by Snowflake. From there, Lendi marketers can pull the data into business analytics tools to measure and compare campaign success across platforms. Accountants, brokers, customer service representatives and other business units can also pull in data for analysis.

“Why would I pull engineering resources off our platform to build capabilities that another company has already mastered?” Daniel asked. “Fivetran allows us to connect to many popular third-party platforms and pull data reliably without significant upfront engineering effort. The quicker we get the data, the quicker we get the insights that the business needs for making a decision. Then the quicker our business operates and evolves.”

Fivetran enables Daniel’s extract-load-transform (ELT) strategy, allowing users to access and analyze raw data using the methodology and tools they are familiar with.

“Marketing obviously knows these platforms much better than I do,” Daniel said. “I don’t have to be a Facebook Ads expert. Or a Google Analytics expert. I just ensure they have a consolidated view of all their data streams and are able to self-service  the data any way they need to do their jobs.”

Setting up a new connector is easy. An employee makes a request, and a Jira ticket goes to Daniel’s team. A data engineer then enters the third-party platform credentials into Fivetran, sets some parameters about how often to fetch data, and sets up a test. Once successful, the connector can go live. The entire process takes less than 30 minutes start to finish. By comparison, having an engineer custom-build a connector can take a week to several weeks, which means Fivetran is helping Lendi realize significant time and cost savings. Multiply that by dozens of connections and the impact can be transformational.

The Outcome

Fivetran allows Lendi to be a data-driven company, giving stakeholders across the organization access to the information they need to create actionable insights to improve the business. This data-driven culture allows decisions to be based on data instead of gut feelings, creating better outcomes across the board. And thanks to Fivetran’s extensive library of connectors, nearly any data request can be filled within an hour.

Using Fivetran to do this instead of relying on internal resources allows engineers to focus on the core business — working exclusively on improving the company’s proprietary technology.

“It’s so powerful to be able to go to our operations staff and say ‘we can get the data you need for your job much faster now.” Daniel said. “With Fivetran, we are able to focus our efforts on our core business data and not worry too much about moving data around.”

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