Big Data Tools Connect the Dots for CSC's Digital Marketing
- Lack of big picture perspective for marketing efforts and successes
- Difficulty in analyzing user data coming from more than 50 tools and components used daily
- Need for quick implementation and easy updates to meet changing industry trends
- Create a unified, 360-degree view of prospective customer actions by analyzing multiple data sources
- Undertake a 6-week Proof of Value using CSC Big Data Platform as a Service
- Incorporate use of open-source technologies on Amazon Web Services with high degree of automation
- Successfully implemented big data platform at reduced time and cost
- Improved understanding of audience segments and test marketing techniques with analysis of raw data in near real time
- Enabled team to freely experiment with new data science techniques at a low cost using open-source approach
On any given day, CSC’s digital marketing team interacts with clients and potential clients around the world through a variety of digital channels — from email campaigns, microsites and webpages to tweets, videos and blog posts.
Behind the sophisticated marketing effort are more than 50 tools — including Eloqua, Salesforce and Adobe Analytics — that have given the team many ways to communicate with clients and to get insight into their needs and interests. Until recently, though, the approach lacked a comprehensive view that could measure the impact of campaigns across the digital marketing ecosystem. The team realized that by building this broader view, with a big data service provided by CSC, it could manage data more efficiently and gain a more sophisticated understanding of its audience.
The challenges faced by CSC’s digital marketing team are no different from those faced by any company in this evolving world of modern marketing. How users interact and engage with webpages, social media and email campaigns is a need-to-know in this new environment. But the bigger picture can be elusive.
“There is a great depth of information in the data silos created by all the products we use,” says Nick Panayi, head of CSC’s digital marketing and global branding. “That’s useful if you wanted to study just one part of the customer’s behavior. … What you don’t have is a complete understanding of how all of that ties together to give you a 360-degree view of that customer.”
The CSC team realized that the broader view would not only reduce the amount of time spent manually wrangling data, but also improve understanding of visitor interests. And it would increase the team’s ability to rapidly test, assess and alter marketing tactics and messages to better match the interests of prospective clients.
CSC’s Big Data Platform as a Service proved to be the ultimate solution for the challenge. The group implemented the big data platform on Amazon Web Services, pulling in more than 80 different source files from about 10 isolated source systems, according to Sunil Samantaray, principal architect, Big Data & Analytics at CSC. “There were several source systems, which collected CSC marketing campaign data, sales opportunities data, Web content, emails, newsletters, different marketing contact information, page hits, Web visits — all sorts of information,” he says.
By gathering that information in one place, the system turns the once arduous task of sorting through data into “daily moments of joy,” says Chris Marin, senior principal, Digital Marketing Platform & Analytics.
“Generating audience segments and profiles of different clusters within our marketing is not something you can get from one system,” he says. “In the past, we’d dump raw data from the Adobe products we use, from Eloqua and from Salesforce. By the time you go through all those machinations, it might be months down the line, and the data may be updated by then. Now we do a simple query and get it in near real-time.”
Better yet, the platform can easily accommodate new data sources and “automatically ingest the data,” Samantaray says.
Ready for what's next
While a typical data warehouse implementation can take months or even years and require expensive hardware, CSC’s big data solution was ready to go in a fraction of that time and cost.
“It took us about a week to launch and test the platform and hand it over to the managed services team. It took us about 2 weeks to set up the automatic data ingestion and put the data processing framework in place before we actually started gaining insight from the data,” Samantaray says.
Panayi says the system has vastly improved the team’s ability to judge the impact of its efforts. “In marketing, segmentation is absolutely critical. It basically means that you have to understand how segments of customers or users are behaving, and the reason you want to understand that is so that you can better serve them,” he says.
Marin notes that CSC’s embrace of open-source components was a critical advantage over closed systems. “Data science is always developing new analytic techniques. Today, a popular technique for analysis is ‘deep learning,’ a way to build predictive models. If you followed the traditional approach, you’d have to wait for your vendor of choice to integrate that a year or two or three from now, or maybe not at all. With this open-source approach, you have access to a variety of tools. New techniques are available faster,” he says.
This is an aspect of future-proofing that Panayi believes to be especially valuable.
“There are questions we don’t know that we’re going to be asking tomorrow, but the amazing part of it is, I know I’m going to have an answer,” he says. “That’s the part that I love.”