Eco-friendly cleaning system builds a holistic view of the customer, sees a 25% increase in retention and develops predictive analytics.
Customer retention jumps from 25% to 50% with highly targeted campaigns
With data in Tableau workbooks rather than disparate spreadsheets, focus shifts from manual data extraction to data strategy
A new data science hire develops machine learning models and predictive analytics
Destination: Google BigQuery
Business Intelligence: Tableau
Koh, launched in 2016 in Sydney, Australia, is one eco-friendly cleaning system for your entire home. With high demand and fast growth, the business has expanded operations to the UK.
Head of Growth Alex Simonovski is responsible for driving the data insights strategy for the company. When he started, the business was trying to keep up with the immense growth, focusing on filling orders rather than data strategy. He recognized the need for a data-driven approach to help the business scale.
“We got to a stage where decisions were based more on gut feeling and our data strategy was limited to disparate spreadsheets,” explains Simonovski. “To bring the company to the next level we really needed a structured data approach, so we looked for a solution that would allow us to bring our data in and begin using it in a quick and efficient way.”
Koh evaluated a number of pipeline solutions and selected Fivetran because of its ease of use compared to the open-source solution it evaluated, which required engineering resources to build and maintain. Simonovski didn’t have any expertise in this area so the business would have had to outsource the work or bring another employee on board to maintain the code:
The platform is super intuitive. Implementation was concise and straightforward – we set up our connectors and even had some of the historical syncs complete in a matter of minutes. We’ve been a happy Fivetran customer for over a year, which just points to the ease of use and reliability of the tool.
Because Fivetran is so easy, the business considers the availability of a Fivetran connector in evaluating new solutions for the business, says Simonovski:
One of our key criteria for choosing a new application is if Fivetran has a pre-built connector for it. We’re currently migrating to a new email marketing tool. We were down to a few contenders, but ultimately went with Klaviyo because Fivetran has the connector readily available.
The business chose Google BigQuery as its data destination because the cloud data warehouse fit seamlessly with its existing GSuite stack and didn’t require as much of a technical understanding as other warehouses. Similarly, Koh brought on Tableau for its data visualizations because of the intuitive nature of the tool compared to others that it evaluated.
Every morning, Simonovski starts his day by looking at a single workbook with all key indicators for the business. Previously, it would have taken days to export and join the data within spreadsheets for a report that would be stale by the time it was ready.
Koh now has comprehensive Tableau workbooks set up for almost every single marketing campaign, which are automatically updated when the data syncs. Previously, downloading a customer list from Shopify would take Simonovski about three hours, resulting in 17 zip files that had to be joined in Excel:
This stack has made a massive difference in almost every aspect of the decision-making process and everything we do. It has shifted how we run performance marketing and has changed our focus completely.
While prior culture was focused on revenue with little consideration of cost, it’s now about maximizing efficiency by looking at acquisition and retention costs, and audience segmentation and exclusion. What was once tedious and error-prone is now automated.
The new modern data stack coincided with a new trajectory for the business. While it had done a great job at acquiring new customers, the company hadn’t focused on retention. The modern data stack is helping the business understand customer behavior to run highly targeted campaigns throughout the year, reach customers on the right channel and at the right time, and drive retention. Simonovski shares the substantial increase in retention rates:
Our retention metrics are some of the most viewed in the company. In the past, we would have had a 25-30% repeat customer rate. In the space of a year we’ve grown this to well over 50% – and that’s all backed by data.
Having the ability to join different data sets using multiple Fivetran connectors enables Simonovksi to create a more complete customer profile. For instance, connecting purchase data from Shopify to data in Google Analytics to determine how a customer arrives at the site and how many sessions it took to convert:
Having the data tables and ERDs has been a life-saver for me. We can see where everything sits and easily join things together. It has brought an immeasurable amount of value to our business.
Koh had always planned on hiring a data scientist, but wanted to ensure it had the right architecture in place for such a high-demand individual to succeed. With the modern data stack implemented and a data scientist recently hired, the business can begin building a machine learning model. Simonovski is excited about having this individual on board to bring the analytics to the next level:
Our data scientist is building a machine learning model around our demand profile so we can be more efficient with our working capital, including at what point we should re-stock our product. We have four years worth of data that is now centralized in the warehouse that we can use to predict demand.
To learn more about how Fivetran can impact your marketing analytics and beyond, check out our resource center.
About Fivetran: Shaped by the real-world needs of data analysts, Fivetran technology is the smartest, fastest way to replicate your applications, databases, events and files into a high-performance cloud warehouse. Fivetran connectors deploy in minutes, require zero maintenance, and automatically adjust to source changes — so your data team can stop worrying about engineering and focus on driving insights.
About Google BigQuery: BigQuery is Google’s serverless, highly scalable, enterprise data warehouse designed to make all your data analysts productive at an unmatched price performance.
About Tableau: Tableau helps people see and understand their data. The Tableau platform provides the breadth and depth of capabilities that enterprises need, and adapts to your environment with unmatched flexibility and choice, while meeting the toughest governance and security requirements. People love using Tableau because it is both powerful and intuitive. Tableau leads the industry with the most passionate user community, over 86,000 customer accounts, and a commitment to customer-focused innovation.