Smarter Savings with BetterSaver and Airbyte

Learn how BetterSaver set up data integration without data engineers.

BetterSaver gives NewZealanders personalized KiwiSaver fund recommendations based on information collected from reputable sources. Using Airbyte, BetterSaver tracks customer journeys and collects customer touchpoints from multiple sources, including Hubspot, Instagram, Intercom, and Facebook. Using Airbyte's APIs, BetterSaver's platform, hosted on Google Cloud Platform (GCP), combines data from different data sources into BigQuery to power Google Data Studio dashboards and Jupyter notebooks. Airbyte eliminates the risk of storing personally identifiable information (PII) in a third-party cloud. It's simple to set up, making it easy to use and access for data analysts without requiring to hire data engineers.

About BetterSaver

BetterSaver gives expert digital KiwiSaver advice that’s 100% personalized to an investor's profile. Since launching their innovative KiwiSaver comparison site in 2018, they have had the aim to generate transparency within the market. A first of its kind for Aotearoa, their ethical analysis holding providers to account caused quite a stir.

BetterSaver wants to simplify the process of finding the right KiwiSaver fund by empowering New Zealanders to make better decisions for themselves. BetterSaver built a platform to give equal access to KiwiSaver advice. BetterSaver wants New Zealanders to achieve their personal financial goals while being confident that their KiwiSaver fund is invested profitably and aligned with their world view.

The Business Problem

The goal of the BetterSaver team is to create an ecosystem where people have easy access to KiwiSaver recommendations to make sound financial decisions. As their platform grew, several fundamental business problems needed to be addressed.

Scattered customer experience data

Marketers and growth teams at BetterSaver had to map out their customers' journeys to gain a deeper understanding of the customer experience and discover what keeps them sticky to the platform. The challenge was that customer journey data was dispersed across many CRM platforms, from Hubspot and Intercom to Facebook and Instagram. To integrate this scattered data and measure marketing effectiveness, BetterSaver needed a better approach.

The problem that we're trying to solve is that we have a CRM, and we have a messaging service. We use messaging services like HubSpot and Intercom to obtain customer data and collect marketing analytics from Facebook and Instagram. Our marketing team wants to analyze this data holistically to determine whether the marketing budget is well-spent and how we can improve.

Bespoke architecture fails to meet new requirements

As a startup data company, BetterSaver relied heavily on bespoke python scripts and cron jobs to stitch and coordinate its data infrastructure together. Their old data architecture didn't meet their growing internal needs and had several issues. Mainly being able to scale the one dedicated person that was looking after the data infrastructure.

Lack of transparency for sensitive customer data

BetterSaver handles large amounts of data, including sensitive personally identifiable information (PII). As a result, BetterSaver felt that Airbyte provided a higher level of data transparency than other competitive tools. For instance, with other solutions, critical customer information had to be extracted, transferred to third-party servers, and then had to be pushed back to BetterSaver's database.

Our business deals with a lot of PII data, and we didn't want to waste hours trying to find out where and how third-party solutions are storing our data. If data is stored and processed on our GCP infrastructure, it is much easier to manage.

Transforming the architecture to meet the new requirements

BetterSaver has revolutionized financial planning in New Zealand by digitizing investment advice for over 3 million clients. As their platform grew, several fundamental business problems needed to be addressed.

Simpler customer experience data aggregation

For BetterSaver, bespoke python scripts combined with intercom weren't a viable solution to handle customer experience data. Airbyte provided a rich set of APIs enabling BetterSaver to quickly blend customer experience data from different sources and bring this data into Google Google BigQuery for analysis. With this solution, the marketing and product teams had complete visibility of the customer journey across the entire platform and could pinpoint more precisely where customers dropped off along the way. 

With Airbyte, we could just push a few buttons, allow API access and bring all the data into Google BigQuery. By blending all the different marketing and product data sources together, we can gain valuable insights. Now, we can easily tell how any customer entered our platform, how much they cost, and what their ROI is. The marketing team can easily figure out where money is spent on projects that don't yield results or at what point in the product journey customers are dropping off.

Seamless and repeatable data analysis

Before Airbyte, BetterSaver used bespoke python scripts to kickstart the daily analysis of customer data. They were custom-written and didn't work well with sources such as Intercom. By leveraging Airbyte's docker image and documentation, BetterSaver could get up and running quickly on a local machine and then deploy the solution into a compute instance in Google Cloud Platform.

With the Airbyte GUI, all we had to do was copy and paste the API key and fill in details to set things up. If there is a connector, simply create a connection, and it does the job. The docs and UI were approachable and easy to use, especially for someone from a non-technical background. The key is that everything is now repeatable, and if anyone wants to re-run a report, just push a button, and you get newer results and a new set of analysis.

Into the future with Airbyte

Airbyte has become an essential part of BetterSaver's platform. BetterSaver will continue to harness Airbyte's rich ecosystem of connectors as its product and marketing teams add more tools.

We had an excellent experience working with the Airbyte community. Typically, we post a question, and within 24 to 48 hours, we get a response. So, we are pretty comfortable using Airbyte for the long term. At least in the near future, we don't feel the need to hire a data engineer, and that's going to save the company money, which is especially beneficial for us as a startup.

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