CloverDX helped make handling multiple data sources more efficient, speeding up customer onboarding
Gain Theory is a global marketing effectiveness consultancy that empowers marketers and insight professionals to make faster decisions using data, technology and advanced analytics. The WPP consultancy exists to inspire marketing excellence by creating data informed cultures that drive business growth, profit and market share.
The company takes data inputs from clients' marketing efforts and transforms it all into their marketing analytics modelling templates.
Brian Suh, Transformation Practice Lead at Gain Theory, explained how "Our modelling outputs are standard, but because clients' marketing efforts are varied, the inputs we get are rarely, if ever, “standard”. So, we end up customizing our data processes to standardize the inputs for our marketing analytics models."
Read the full interview with Gain Theory's Brian SuhEven if the data’s perfectly clean there’s still more work to be done. The company has custom data processing and cleansing rules – all custom, for each dataset, for each client. Clients can have thousands of data feeds coming in, each with their own rules. There’s a huge variety to handle, and at speed to deliver decision making around marketing programs.
"Our use case is a lot about width. Each data source is not always going to be very complicated, but the fact that there’s thousands of data sources poses a challenge.”
Prior to using CloverDX, different parts of the organization were dealing with different client data, with everyone building their own technology - using different tools - to translate and standardize the data into a format suitable for each client.
The process was working, but as Brian said, "It doesn't translate that well into efficiency. If everybody’s using a different tool, then only people who know that tool can work on those particular projects."
Gain Theory believed that there was a faster, more efficient way to handle their data ingest and to speed up customer onboarding.
With CloverDX, they are able to standardize the data ingest process, making it more streamlined and consistent.
"It’s enabled us to standardize how we handle custom implementation, at speed." said Suh.
How CloverDX helped deliver a more efficient way to do things
- Single platform brings better collaboration, shorter time‑to‑delivery and unified approach
- Improved productivity as components can be created once and easily shared across teams
- Easier to add new data feeds into the centralized, automated process
- Faster troubleshooting thanks to replacement of undocumented Python scripts with visual representations of the process
