Going deep with consumer analytics

Going deep with consumer analytics

With a depth and breadth of consumer information and a powerful platform to process it, Quantium is realizing the true potential of big data.

Quantium has been processing data and conducting in-depth analytics since its formation in 2002, helping companies better understand their market and their customers. But until recently, most of that data came directly from its clients.

“We saw an opportunity to take a giant leap forward,” says Alex Shaw, head of technology operations at Quantium, Australia’s leading data analytics company, “by bringing our own data assets to the table.”

Retailers, insurers, healthcare providers, and financial services companies, to name a few, are eager for more knowledge about their customers. And any company with consumer-oriented products or pricing complexity can benefit from the analyses that Quantium provides. But the resulting insights are only as deep as the data being scoured.

“You can only go so far with in-store transactions,” explains Shaw, using the retail industry as an example. “But when you marry that data with online purchases and media consumption, you get a much more complete view of the customer. Those insights can be used for more targeted advertising, promotions, loyalty programs, inventory, product placement, you name it.”

  • To bolster its data resources, Quantium formed partnerships with media, banking, supermarket, and cable television providers in Australia.
  • The data it receives from those partners is extremely detailed, but anonymous to ensure full compliance with all privacy requirements.
  • The information provides deep insights into the spending habits, product preferences, and media consumption—both past and present—of Australians.

“We have a breadth and depth of consumer data that is unmatched in the region,” says Victor Bajanov, a member of Quantium’s senior leadership team. “Compliance and privacy are very important to us, so we don’t have individual names, addresses, or account information. Essentially, we hold no personal information but can analyze every credit card transaction and every line of a grocery store receipt. And when you combine and correlate data from multiple sources, you get a very granular picture of modern consumers.”

Reducing query time by 92 percent
Quantium’s pre-existing analytics engine couldn’t support its desire to process more data and conduct faster analytics, so the company decided to build a world-class big data platform from the ground up. After a rigorous selection process, Quantium chose the MapR Converged Data Platform running on the Intel® Xeon® processor-based Cisco Unified Computing System(Cisco UCS®).

“Our banking partner has more than two million customers who generate 14 million transactions per week. That’s a lot of data to crunch, and it’s just one source,” says Shaw. “We chose MapR because it had the best performance and Cisco UCS because it had the best management capabilities and lowest power consumption.”

  • The new platform has reduced query times by 92 percent, allowing Quantium data scientists and engineers to design complex queries that run against multiterabyte data sets—and get results in minutes.
  • The architecture is also built for multitenancy and scalability. Quantium can segment and safeguard client data while simultaneously giving clients access through a secure portal. And the clustered environment will be easy to expand as the business grows.

Flexing an “innovation center”
Beyond speed and scalability, the new platform is fostering innovation, helping Quantium develop new products and enter new markets.

“We have a lot of smart people who have been hamstrung by technology and its inability to implement their ideas,” says Bajanov. “Now they have a powerful platform at their disposal to test new scenarios quickly and cost effectively. It’s an innovation center that allows us to create new solutions and services for our clients.”

  • Quantium is already flexing the muscle of its new analytics engine for Woolworths, the largest supermarket chain in Australia.
  • The platform is crunching the data from nine million loyalty program members, 25,000 products, and 52 weeks of purchasing behavior to automate the selection of merchandise that is featured in weekly promotional emails to members.

“It’s a massive data set, and we are processing it weekly,” says Shaw. “If every person on the planet were doing the same calculation, we would all need to produce six decisions a second to keep up with our MapR and Cisco cluster.”

This is the true potential of big data. And it’s being realized Down Under. 

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