Australian consultancy Customology uses CloverDX to turn huge amounts of raw transactional data into customer profiles for strategic, targeted marketing campaigns.
Customology blends data science with marketing strategy to analyze customer data and help their clients optimize customer loyalty. They came to CloverDX in search of a data integration platform that would improve on their existing homegrown ETL solution, which was becoming slow, cumbersome and difficult to scale.
A platform for data experts
Customology is a highly technical group with a team of developers and data scientists naturally averse to the confining nature of some data integration tools. They needed a platform that would not only standardize and transform incoming data for their core model, but would also enable them to augment the solution with their own expertise.
The data flowing into Customology’s systems:
- consists of large datasets, taking in every transaction from every customer
- is received at different intervals - sometimes in real time, sometimes from weekly backups
- and arrives in various states of data quality, often containing duplicates and lacking normalization
A modular, microservice framework
Implementing CloverDX has enabled Customology to build their ETL stack as a modular, microservice framework. They can easily schedule and manage their data integration processes, resulting in faster data processing, shorter time to market and increased scalability.
Michael Barnard, Customology’s General Manager, says that CloverDX helps accelerate their data workflow processes, while still providing the flexibility that their technical team needs:
CloverDXs versatility when massaging data affords us the freedom and creativity to design solutions in a more developer-minded way.
Michael Barnard, Customology General Manager
And because they no longer have to develop bespoke applications for each client, they can scale their activities more efficiently, get the data flowing quickly to where they need it, and deliver better insights to their customers.
Case Study: Marketing Strategy Meets Data Science Explore Topic: Business Intelligence and Analytics