The Modern Data Stack: How Austin Capital Bank successfully leverages integrated data to power more insights and less complexity

For years, packaged CDPs were the solution to activate customer data. CDP vendors offered a single solution that did everything you expected the CDP to do at the time. Ingest data from many different sources, unify that data into a single customer profile, and activate those customer profiles into downstream marketing tools. 

According to Adam Ribaudo, Vice President of Data Activation at Brooklyn Data Co, a Velir Company, “This worked great for a while, but one thing was missing. The Data Coud. With the rise of the modern data stack, the Data Cloud needed to be the center of the data universe. Especially for customer data. And with an ever-evolving industry, you’re better off picking best-in-breed vendors for each solution you need rather than sticking with an all-in approach from a single vendor.”

Enter the composable CDP. 

In this blog, we’ll explore how Austin Capital Bank (CreditStrong) organically built a composable CDP. And how they’re successfully leveraging the tools in their tech stack to power their marketing and product strategy using Heap, Snowflake, Hightouch, and Iterable.

Unlocking the power of the composable CDP

The composable CDP enables teams to evolve beyond traditional ways of managing large, unwieldy data–by allowing best-in-breed tools in an existing tech stack to work together. Take Austin Capital Bank (CreditStrong), a leader in community banking providing digital credit building and protection products, as an example. 

Through their composable CDP, they’ve been able to:

1. Track the end-to-end user journey from marketing page to loan application

2. Send that data downstream to Snowflake

3. Activate it with Hightouch to perform advanced analysis

A flow that’s helped them achieve their goal of customer 360. 

1. Tracking the end-to-end user journey from marketing page to loan application in Heap

According to Hayden Cornwell, Senior Product Manager at Austin Capital Bank, “Understanding our customers throughout is really important for growing our company.” 

But looking at their available data, they realized the behavioral component was lacking. Everything leading up to the start of a loan application lacked insight like how many times a customer visits their marketing website, what channels they come from, and where they go once they get there. Data that’s critical in working towards a more optimal product for their customers.

But where to begin? Before working on customer retention, you have to have customers to retain. So, they looked at their onboarding process.

With multiple products to choose from and multiple ways to get to a credit application after choosing a product, the team at Austin Capital Bank wanted to find out which customer onboarding process was most successful. So they looked at two behavioral segments in Heap.

They found the bounce rate for segment one was almost half of segment two, making the conversion rate for segment one much higher. An Interesting discovery because it showed people preferred the route with concise information that showed the value-add of the product. 

They also had interesting secondary outcomes like determining an after-bid strategy for the different segments and changing CTA wording. Learnings they’ve been able to leverage in launching two new products, Magnum and FreeKick, where they set up onboarding funnels from day one to begin gathering insights to send downstream. 

2. Sending data downstream to Snowflake

With so much data, now including behavioral data from Heap, to gather and analyze, Austin Capital Bank next taps into their existing database: Snowflake. 

According to Ian Bass, Head of Data Analytics at Austin Capital Bank, “We pump the raw data in with Fivetran to Snowflake using DBT as our CICD layer and use queries to create clean versions of data tables and then modeled versions where we denormalize data and create templates and tables upon which we put our analytics stack. And in doing so, we’re also able to spin up new audiences in a matter of minutes.” 

And that’s where Hightouch comes in. 

3. Activating data with Hightouch to perform advanced analysis

In their composable CDP architecture, Hightouch has access to Snowflake, but only the specific views or tables they give it access to, and those then get sent back out to various marketing tools like Google Ads, Iterable, and Impact.

For Google Ads, they’ve been able to introduce automated conversion uploads and send similar audiences over for things like YouTube advertising and search and display. 

For email marketing, Iterable and Hightouch plus Snowflake have shortened their time to action using SQL to spin up a new view and define various target groups based on what they want to see with the data and how they want to interact with customers.

To gain new customers via affiliates, they use Impact and have been able to send data back to them using Hightouch's HTTP request connector, allowing them to avoid costly and lengthy testing and development times. 

The results? 

With this architecture, the results have been real for Austin Capital Bank. 

For starters, they now experience much faster deliverable times. Ian says, “We can meet with our email marketing manager, decide on a new audience to pursue or create, and we can have that spun up in under an hour.”

Next, they can pursue new ideas that may not have been possible, or the lift wasn’t worth the effort. “You don't know if something's going to be effective or not, but now we can experiment with low opportunity cost,” says Ian. 

With automated Google Ads uploads, they can now deploy on weekends to prevent disrupting Google’s algorithm as can happen when sending manually, which has allowed them to bring all their performance marketing in-house.

Finally, for Customer 360, the combination of Heap and Hightouch helps with not only a top-of-funnel understanding of the behavior of potential and existing customers but also long-term retention. With so much data already in their Data Cloud, it becomes a matter of bringing it all together under the composable CDP model to get a full picture of their customers’ behavior. 

Conclusion 

The benefits of the composable CDP architecture are beyond theoretical. They’re practical and tangible.

Take it from Austin Capital Bank. They had Snowflake as their Data Cloud. They identified a need to build segments and get that data to their email platforms, so they brought in Hightouch. Then they saw the benefit of bringing behavioral analytics to understand the funnels, so they brought in Heap. 

And in doing so, it dawned on them that they could tie all these things into a single unified system to build that customer 360 model. They simply did what was in the best interest of their business every step of the way, leading them to discover the power of the composable CDP. 

Interested in learning more about data-forward marketing strategies? Check out Snowflake’s 2023 Modern Marketing Data Stack Report.