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Cenique Case Study

2015

Founded in 2012, Hong Kong-based analytics company Cenique is revolutionizing the digital-signage industry by providing its clients with a cost-effective way to harness mobile and big data technology for in-store advertising and audience measurement. Cenique’s primary offering, the IntelliSense Audience Measurement tool, uses an in-store webcam connected to an Android-based media box to gather anonymous customer data across nine key metrics including age, gender, and time of day in the store. Using a convenient browser-based dashboard, clients can view location-specific metrics, and also select from advanced options, such as the automatic adjustment of their digital signage content based on the gender or age of shoppers. The digital signage content is streamed by the media box, which uses a quad-core processor to broadcast high-definition 1080p videos.

In 2013 Cenique won the Hong Kong ICT Best Business Product Award, and, in 2015, it received the Hong Kong ICT Gold Award for Best Smart HK - Big Data Application. Cenique operates in 16 countries and employs a small team of about 20 associates, with headquarters in Hong Kong and additional offices in the United States and India.

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We’re optimistic about the future, and our confidence is largely thanks to the stability, security, and speed that AWS provides.”

Shylesh Karuvath
Cofounder and CEO, Cenique

The Challenge

“Every startup hopes for growth,” says Shylesh Karuvath, cofounder and CEO of Cenique. “But it’s wise to start small in order to see how the market responds to your products.” When Cenique began operations in 2012, its initial rollout of a few hundred media players was supported by three local servers in Hong Kong and Singapore. As the business expanded and its operations moved farther into Asia and the United States, downtime and sluggish connection speeds became a significant problem. For a company trying to establish itself in the competitive, new field of real-time analytics, service delays that restricted growth and delayed the delivery of a great customer experience were unacceptable.

IntelliSense requires information generated from customers’ media boxes to be transmitted securely to remote servers, where it is analysed rigorously and converted into informational graphs made available to clients on a hosted dashboard. For customers who purchase context-triggered content, the results of the data analysis determine which media files are pushed from the server back to the in-store digital signage for maximum appeal to in-store shoppers. “It’s a complicated process and every fraction of a second counts,” says Shylesh. “We were committed to finding a provider that could provide us with sufficient speed and security, but also deliver a cost-effective solution that matched our budget.”

“Additionally, we needed a solution that would allow us to grow without worrying that our success would outstrip our infrastructural capabilities,” explains Shylesh. “We also saw the potential for the application of additional big data analysis tools – but this, of course, would require lightning-fast connection speeds.”

Why Amazon Web Services

“We evaluated Amazon Web Services (AWS) and Microsoft Azure,” says Shylesh. “We ultimately chose AWS because it offered a larger range of data analysis tools, better availability, and superior integration with our native Linux environment. We were certain that running analytics on AWS would be far quicker than running it on our on-site servers.”

Cenique’s IT staff was able to deploy the company’s new analytics solution on AWS in just one month without requiring assistance from Amazon or third-party partners. According to Shylesh, his team relied on online support documentation. “The transition was quite straightforward,” he says. “We found AWS to be very intuitive and didn’t experience any setbacks during the migration process.”

in-store cameras. In accordance with privacy laws, the anonymous audience data is extracted on site and sent via a secure connection to the AWS Cloud. Once in AWS, it is processed by up to five Amazon Elastic Compute Cloud (Amazon EC2) instances before being archived in an Amazon Simple Storage Service (Amazon S3) bucket. Cenique also uses Amazon S3 to store prerecorded advertisements, which are transmitted via Amazon CloudFront back to clients. Elastic Load Balancing and Auto Scaling are used to ensure that incoming traffic is evenly distributed across Cenique’s network.

Cenique uses the AWS Management Console and Amazon CloudWatch to monitor and control the network, which is securely contained within an Amazon Virtual Private Cloud (Amazon VPC) that contains several subnets. Importantly, the AWS architecture allowed Cenique to preserve its original network, which was built with Linux and Java, and included a large data warehouse.

“The versatility of AWS made it an obvious choice for us,” says Shylesh. “It integrated easily with our existing programs, which meant that we didn’t waste time restructuring our network during a critical phase of business growth.” Figure 1 demonstrates the Cenique infrastructure on AWS.

The Benefits

Freed from the ongoing costs of network maintenance, Cenique began to save money with AWS almost immediately. “For startups, every dollar matters,” says Shylesh. “With AWS, we’ve reduced our operational expenditure by 60 percent.” This has, in turn, allowed Cenique to invest more time and money into ideas that will help expand the business.

AWS has also freed Cenique from delays in data processing. Since moving to AWS, the company has experienced near 100 percent uptime. The company uses its own custom algorithms hosted in Amazon EC2 to explore and navigate large amounts of data extracted from the in-store cameras. Using AWS Auto Scaling, Cenique is able to run these analytics up to 40 percent faster than before.

Decreasing the amount of time it takes to complete calculations doesn’t just speed things up for Cenique’s customers—it has also encouraged the company to pursue business opportunities in Europe and Asia, confident that additional customers won’t result in unwanted network latency. In June 2014, for example, Cenique began operations in Japan. With AWS, the company was able to copy its U.S. environment and redeploy it in the Tokyo region. “In the past it would have taken at least a month to enter a new market,” says Shylesh. “But with AWS, it took only one week for us to establish ourselves in Japan.”

Developers are currently working on a plan to have Cenique’s digital signage appliances detect and analyze Bluetooth and Wi-Fi networks. This data will allow Cenique to provide deeper insights into what sort of shoppers enter a particular store and how long they stay there. With this information, Cenique’s retail customers will be able to evaluate and optimize sales and merchandising strategies. “AWS understands that data is often unstructured, and comes in various formats,” says Shylesh. “Because of this, we can expand into new areas of data analysis with the confidence that using AWS will help us to identify and exploit previously undetected interrelationships.”

Finally, Cenique has also been able to enhance the security of its network, protecting both its own data and that of its clients. “We’ve taken advantage of our ability to create expiring URLs in Amazon S3, which allows us to control the availability of time-sensitive data,” says Shylesh. “We’ve also used Amazon S3 to encrypt our archived data.”

Cenique now has 10 times more customers than it did when it first started using AWS, and its growth shows no sign of slowing down. “We’re optimistic about the future,” says Shylesh. “And our confidence is largely thanks to the stability, security, and speed that AWS provides.”

Cenique IntelliSense Architecture on AWS

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About Cenique

Founded in 2012, Hong Kong-based analytics company Cenique is revolutionizing the digital-signage industry by providing its clients with a cost-effective way to harness mobile and big data technology for in-store advertising and audience measurement.


AWS Services Used

Amazon EC2

Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers.

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Amazon DynamoDB

Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale.

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Elastic Load Balancing

Elastic Load Balancing automatically distributes incoming application traffic across multiple targets, such as Amazon EC2 instances, containers, IP addresses, and Lambda functions.

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Amazon S3

Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance.

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Auto Scaling

AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost.

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Amazon EMR

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.

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Amazon Kinesis

Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information.

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Amazon RDS

Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud.

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