Zalora: Spurring sales with real-time personalization through Google BigQuery

About Zalora

Founded in 2012, Zalora is an online retailer that sells fashion to customers in Hong Kong, Indonesia, Malaysia, the Philippines, Singapore, and Taiwan. Zalora has about 26 million users of its websites and mobile applications in the region.

Industries: Technology
Location: Singapore
Products: BigQuery, API Analytics

Using Google BigQuery with Google Analytics, Zalora has increased sales and revenues by personalizing customers’ experiences on its websites and mobile applications.

Google Cloud Results

  • Enabled rapid querying of data associated with 16 million visits per week (each visit incorporated up to 10 events)
  • Democratized access to data throughout the business
  • Delivered a highly personalized customer experience
  • Helped position the business to take advantage of the likely surge in online retail in South East Asia

Helped eliminate need to add 5 more technology team members

The online retail market in South East Asia and elsewhere in the region is maturing, but has enormous unfulfilled potential. Zalora is strongly positioned to reap the rewards of an online retail boom in South East Asia and nearby markets.

Founded in 2012, the business sells fashion, footwear, and accessories to customers in Hong Kong, Indonesia, Malaysia, the Philippines, Singapore, and Taiwan through websites and mobile applications.

Headquartered in Singapore, Zalora is part of the Zalora Group with The Iconic, an online retailer that sells fashion to customers in Australia and New Zealand. By late 2017, Zalora grew to support about 26 million users across the markets it serves.

Targeting growth

“We aim to be South East Asia’s fastest growing online fashion destination,” explains Karthik Subramanian, Chief Technology Officer, Zalora. “Our value proposition is that you don’t need to go into a shopping mall to buy good clothes. Instead, you can go online and place an order that will be delivered in a day to a day and half, depending on your location. So it’s fashion at your fingertips.”

Understanding how a customer travels through its ecommerce conversion funnel—the transition from an initial interaction with its digital properties to completing a transaction—is key to the Zalora business model.

“We had been using a sample of the conversion funnel data we captured and extrapolated from that to make business decisions,” Subramanian explains. “However, this was not giving us the insights we needed to personalize our websites and applications to deliver a high-quality customer experience.”

Zalora also wanted to identify online retail trends early to seize new opportunities and adapt quickly to changing market conditions.

“Google BigQuery delivers the reliability and functionality that serves a mission-critical purpose for our business. This is not retroactive reporting—this is real-time decision-making.”

Karthik Subramanian, Chief Technology Officer, Zalora

Google BigQuery to complement Google Analytics

Zalora had used Google Analytics “from day zero” to track and report raw clickstream data from its websites and applications.

Zalora then decided to use Google BigQuery to extract information about users’ interactions and behavior on its websites and applications.

All Google Analytics data is now written by default into Google BigQuery. “We’ve been using Google BigQuery for nearly two years now,” Subramanian says. “It enables us to identify the drop-off rate at particular points during the checkout flow—for example, if a visitor to one of our websites or apps adds a product to a shopping cart and decides not to proceed, or views a product and opts not to add it to their cart. We can view this by individual visitor and at an aggregate level.”

Zalora uses this data to determine whether to tweak its websites or applications to correct any customer experience or product problems. “We may check whether there is an image sizing concern, or the quality of the image is not good enough to spur a purchase,” Subramanian says.

With the business now a mature ecommerce player, it typically intervenes only in the event of sizeable deviations from its average customer checkout and average bounce rates.

Zalora has also gained the ability to respond quickly to feedback on pricing decisions, such as the currency conversion rate on a particular product or market.

Delivering a personalized experience

Google BigQuery has helped Zalora determine how products are presented to customers on its websites or applications. Images of products that sell faster than others are promoted to lead positions on Zalora pages to improve conversion rates and grow revenues.

“The placement of product images is tweaked in real time based on business rules we’ve defined and the data coming out of Google BigQuery,” Subramanian says. “We built the clickstream pipeline that delivers this functionality from a combination of Google BigQuery and our own platform. Google BigQuery delivers the reliability and functionality that serves a mission-critical purpose for our business,” he adds. “This is not retroactive reporting—this is real-time decision-making.”

“With Google BigQuery, nobody in the business has to depend on an engineer or a technology team member to run a task or query—they can simply do it themselves.”

Karthik Subramanian, Chief Technology Officer, Zalora

Another key use case for Google BigQuery at Zalora is to track the performance of marketing optimization activities. “All that data comes in to Google BigQuery, and we use it to calculate our cost of customer acquisition and other key metrics,” Subramanian says.

The Google BigQuery pricing structure—based on the queries run rather than the volume of data stored in the Google BigQuery data warehouse—enables Zalora to control its costs effectively. The business must capture and manage the data associated with 16 million visits to its websites and applications per week, with each visit generating up to 10 events. “Google BigQuery allows us to query these large data volumes extremely quickly and act accordingly,” Subramanian says.

A lean technology team

Using Google BigQuery with Google Analytics also enables Zalora to maintain a lean technology team, with Subramanian estimating he would need to add another five members if he had to deploy infrastructure and manage the data himself. “We have effectively outsourced to an as-a-service model so internally we can focus on the value-added task of extracting conclusions from the data,” he says.

Democratizing data access

Google products are democratizing access to data throughout the business, and Subramanian is extremely pleased with the outcome. “Our marketing team constantly analyzes clickstream and marketing activity data through Google BigQuery without intervention from the technology team,” he says. “In fact, with Google BigQuery, nobody in the business has to depend on an engineer or a technology team member to run a task or query—they can simply do it themselves.

“My philosophy is if there is a use case you don’t need us to help you with, just do what you have to,” he adds. “Why should I insert myself between every idea, every information flow, or every decision-making process simply because a technology-dependent step is involved?”

Subramanian sees the key benefit to the company of this democratized approach as being “the ability to make decisions faster with buy-in from the right people. It also takes some of the pressure off the technology team,” he says.

“Google BigQuery and Google Analytics have enabled us to provide highly personalized experiences to our customers and positioned us to exploit the likely rapid growth in online retailing across South East Asia,” Subramanian concludes.

About Zalora

Founded in 2012, Zalora is an online retailer that sells fashion to customers in Hong Kong, Indonesia, Malaysia, the Philippines, Singapore, and Taiwan. Zalora has about 26 million users of its websites and mobile applications in the region.

Industries: Technology
Location: Singapore
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