Vivaki Case Study
VivaKi is part of Publicis Groupe, a French communications company headquartered in Paris, France. Publicis Groupe is one of the largest communications companies in the world, providing a full range of advertising services through a global network of agencies.
The company is active in 104 countries on five continents and has more than 96,000 employees. Publicis Groupe formed VivaKi in 2008 to accelerate the digital transformation and expertise of Publicis Groupe and its agencies. VivaKi is based in Chicago, Illinois and specializes in developing services, tools and next-generation digital platforms.
AWS is a fantastic platform — I've been using AWS for more than three years and I'm loving it.”
Vice President, Infrastructure and Operations
Publicis Groupe has nearly 50 agencies in its worldwide network who create digital advertising campaigns to meet the goals that its customers define, including audience reach, impressions and conversation rates. VivaKi works with ad servers, publishers and data management platforms (DMPs) to pull data and provide daily campaign effectiveness summary to agencies. A campaign can last from a few weeks to a year. Agencies use the summary report to make spending and channel adjustments that achieves the most efficient return on investment for their clients.
Every ad server provides a set of summary reports that provide a high level of overview of a campaign’s spend versus conversion. However, these reports didn’t supply the level of detail that VivaKi needed. “Our customers have specific requests around audience groups and other targets that ad servers cannot provide,” says Vice President, Infrastructure and Operations, Zhong Hong. “Furthermore, gathering data to identify how effective campaigns are by geographic location is critical and this data isn’t available in the reports.”
Before Amazon Web Services (AWS), VivaKi used a proprietary solution built on a cluster of 200 in-house servers to process data. It would take almost six hours to produce a summary report with data from just one ad server. Additionally, the cluster wasn’t designed to manage spikes in traffic. “During holidays, like Christmas or Thanksgiving, our daily statistics are about ten times higher than normal,” Hong explains. “The system didn’t meet our peak power needs. As a result, we had lengthy processing times during peak periods that impacted our ability to deliver data on time.”
Why Amazon Web Services
After considering several solutions, VivaKi chose AWS because of the maturity of the AWS platform, operational scale, security and pricing. “From a business perspective, processing scale means a lot because the more you can process, the more you can service,” says Hong. “Furthermore, we had a lot of conversations with AWS and it was clear that AWS builds its services with customer security in mind. And of course, the pricing, which is a result of operational efficiency and proper management.”
Publicis has a team of mathematicians who need to work with large volumes of data to create advanced analytical models and VivaKi developed a suite of products that Publicis agency teams can use for analytics. The key product is a data management platform known as SkySkraper that consolidates data and enables deep analysis for business analysis insights.
In-depth data analysis
Using AWS, Hong and his team created a highly elastic, scalable architecture to run SkySkraper. AWS is the hosting environment for processing, data storage, and access to the data. Amazon Elastic Compute Cloud (Amazon EC2) provides the computing platform to process the data and Amazon Simple Storage Service (Amazon S3) is the mechanism that VivaKi uses to store the data in an economical and reliable way.
Amazon Elastic MapReduce (Amazon EMR) uploads log level data to Amazon S3 for use on Amazon Redshift. Amazon Redshift acts as the data warehouse. VivaKi pushes data into a 2XL cluster to process and organize the data into consumable data formats such as data cubes. A data cube provides an easy-to-use mechanism for querying data with quick and uniform response times that VivaKi’s analysts can use to run research projects and perform in-depth analysis.
“The summary-level data that we receive from an ad server like Google doesn’t have the critical geo data that we’re looking for,” explains Hong. “Now we can use Amazon Redshift to extract this information from log-level data.”
VivaKi keeps a floating window of six months of log level data in Amazon Redshift and can process the data to produce a summary-level report that includes geographical data. “The value of this data is twofold,” says Hong. “First, it provides data missing from the ad server summary and it also allows us to verify the accuracy of the ad server summary-level data. We can compare the data and have a higher level of confidence in our ad server partners.”
By using AWS, VivaKi improved its ability to process and deliver data to customers. Amazon Redshift pulls data into SkySkraper and runs daily processing to aggregate and link data and produce connected insights from the data. “We needed to load six months’ worth of data, about 10 TB of data, for a campaign,” says Hong. That type of load would have taken about 20 days with our previous solution. By using Amazon Redshift, it only took six hours to load the data.”
VivaKi estimates significant operational savings due to the efficiency of the AWS Cloud. “We support about 50 Publicis agencies worldwide,” says Hong. “If we were using a traditional data center, it would take a team of at least 40 people to support the infrastructure and services that we offer. With AWS, we have a team of 15 people supporting a global organization. That’s a 60 to 75 percent reduction in cost.”
“Efficiency is great but capability is even more crucial,” Hong continues. “We need to deliver what the business demands. With our previous infrastructure, we were limited in terms of what we could deliver. By using AWS, our team has delivered the products and services that the business needs, improved our solutions to keep up with growth, and managed the bottom line to stay profitable. AWS is a fantastic platform — I've been using AWS for more than three years and I'm loving it.”
VivaKi plans to use Amazon Redshift to establish a centralized data store for agency teams to hold data on all media types, including display, search, mobile, search, and video. Hong says, “The data volume will be huge. The flexibility and performance of Amazon Redshift will make this possible.”
Benefits of AWS
- Improved ability to process and deliver data to customers
- Estimates significant operational savings
AWS Services Used
Redshift powers mission critical analytical workloads for Fortune 500 companies, startups, and everything in between. Companies like Lyft have grown with Redshift from fast-growing startups to multi-billion dollar enterprises.
Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 reduces the time required to obtain and boot new server instances to minutes, allowing you to quickly scale capacity, both up and down, as your computing requirements change. Amazon EC2 changes the economics of computing by allowing you to pay only for capacity that you actually use. Amazon EC2 provides developers the tools to build failure resilient applications and isolate them from common failure scenarios.
Amazon EMR is the industry leading cloud-native big data platform, allowing teams to process vast amounts of data quickly, and cost-effectively at scale. Using open source tools such Apache Spark, Apache Hive Apache HBase, Apache Flink, and Presto, coupled with the dynamic scalability of Amazon EC2 and scalable storage of Amazon S3, EMR gives analytical teams the engines and elasticity to run Petabyte-scale analysis for a fraction of the cost of traditional on-premise clusters.
Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. This means customers of all sizes and industries can use it to store and protect any amount of data for a range of use cases, such as websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics.
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