Zip Delivers Personalized Customer Experiences in the Data Cloud

This digital credit and payments provider delights its more than 6 million customers with tailored, exceptional experiences.



Daily events streamed into Snowflake for timely product and marketing insights

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Snowflake Workloads Used
Story Highlights
  • A more personalized customer experience: Zip uses machine learning models to tailor shopping threads that customers see and deliver a more personalized experience across its entire platform.

  • Actionable product and marketing insights: With more than 250 million events streaming into the Data Cloud each day, Zip equips product and marketing teams with an immediate feedback loop so they can determine what’s working, what’s not and how to optimize their efforts.

  • Performance to meet ongoing data needs: With Snowflake’s performance, scale and cost-effectiveness, Zip has democratized access to data for teams across the organization. 

Video Transcript

ZIP is a digital credit and payments provider. We have over six million active customers across two regions, the United States and Australia, New Zealand. Our mission at Zip is to be the first payment choice everywhere and every day.

So Zip has two main stakeholders: our customers who use our product to transact and and spend across a range of merchants and also our merchant partnerships. And so we really wanna be with our customers at, you know, all of the moments through their journey in life. At the core to all of that is data and analytics. If we didn't have access to data and analytics, it's like asking me, what would I do without food and shelter? If Zip didn't have data, it wouldn't exist. A lot of the challenges that we had prior to Snowflake, I can summarize into three main areas. The first is around our technology and our scale. The second one is around trust in data, and then lastly is around accessibility and democratization of data to our users.

Why did we go with Snowflake? Obviously, performance and cost. I think when you're launching new technology having a great relationship with your partner and documentation to refer to, so you're not always bothering them, was a critical factor in our decision as well. The last one is really just how quickly we were able to establish the capability integrate with a range of the other tools that we were looking at on our journey to building our modern tech staff for data and analytics, and, you know, that was another game changer for us with the decision on going to Snowflake.

So since deploying Snowflake's data cloud, we've been able to do and deliver a range of outcomes for the business, delivering data in a has been a big mantra across the team. And so using the combination of Snowflake and a variety of other tools, we're able to send communications directly to our customers that day. When you're in the Zip app, you know, clients have the ability to stream through their shopping preferences.

And so using this capability, we've been able to drive machine learning models to personalize the shopping thread that people see and really drive that personalization home across the platform. I think the last notable use case has really been around enabling our product and marketing teams with near real-time insights. We're streaming over 250 million events a day into the cloud, which is powering a range of behavioral analytics capabilities that enable our product and marketing teams to make decisions that day, immediate feedback loop and measurement of what's working and what, and what's not is incredibly powerful for the business.

When I think about our partnership with Snowflake, and where we're going. I'm particularly excited about a range of topics: AI privacy, security and, you know, return on investment for some of here is that we're really excited about the partnership with Snowflake on. When we think about Snowflake, the thing that comes to mind is it just works.

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