Hanes Australasia: Improves product recommendations and revenue with Recommendations AI

About Hanes Australasia

Hanes Australasia is home to iconic Australian apparel and lifestyle brands including Berlei, Bonds, Bras N Things, Champion, and Sheridan. The business sells its products through its retail network of approximately 550 stores, its 14 websites, and its extensive wholesale network. Hanes Australasia (formerly Pacific Brands) was acquired by HanesBrands Inc in 2016. Headquartered in Melbourne, Australia, Hanes Australasia employs over 4,000 people and operates throughout Australia, New Zealand, South Africa, the United Kingdom, United States, China, and Indonesia.

Industries: Retail & Consumer Goods
Location: Australia

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With Google Cloud and Recommendations AI, Hanes Australasia is delivering personalized product recommendations to customers, improving engagement and experience. This is enhancing transaction conversion rates and improving revenue. The business is now well positioned to use additional Google Cloud machine learning products to further enhance customer experiences and grow across new and existing markets.

Google Cloud results

  • Provides personalized recommendations to customers, improving engagement and experience
  • Supports Hanes Australasia’s growth as a leading ecommerce retailer in Australia and New Zealand
  • Enables the business to obtain real commercial value from data

Delivers a double-digit uplift in revenue per session

Home to some of Australia’s best-known apparel and lifestyle brands—including Bonds, Bras N Things, and Sheridan—Melbourne- headquartered Hanes Australasia employs more than 4,000 people and operates across Australia, New Zealand, South Africa, United Kingdom, United States, China, and Indonesia. Owned by North Carolina-headquartered HanesBrands Inc. following acquisition of the then Pacific Brands in 2016, Hanes Australasia sells its products through its network of approximately 550 stores, its 14 websites, and its extensive wholesale network.

“We started as an exclusively wholesale business, but retail is now a large component of what we do,” says Peter Luu, Online Analytics Manager, Hanes Australasia. “Within retail, ecommerce is an important growth engine, and we invest heavily in development, resourcing, and engineering to build our online presence. Our vision is to deliver a world-class digital experience built on the next generation of web technologies and frameworks.”

“The product is extremely easy to use—Google Cloud has provided the expertise, functionality, and performance, so we do not need to be data scientists to make the most of it.”

Peter Luu, Online Analytics Manager, Hanes Australasia

Becoming data driven key to success

Hanes Australasia conducted a series of experiments that used historical customer data to tailor key touchpoints to individual customers’ needs. Based on these experiments, the business realized becoming data driven was key to understanding consumer behaviors and preferences and to driving revenue from its ecommerce investments.

Hanes Australasia turned to Google Cloud services—including scalable and serverless BigQuery data warehousing, the Firebase mobile development platform, Cloud Functions to build and connect cloud services, and Pub/Sub event ingestion and delivery—to deliver on these opportunities. The business collects detailed in-store transaction data, along with on-site transaction and customer event data that it then streams in near-real time into Google Cloud. It then feeds this data into marketing channels for targeting and optimization, in addition to using it to derive insights that help support wholesale partners.

Exploring machine learning

With its Google Cloud data architecture helping power Hanes Australasia into a leading position as an ecommerce retailer in Australia and beyond, the business started exploring how it could use machine learning to offer even more compelling, personalized customer experiences. In particular, it wanted to move away from a manual, labor-intensive way of recommending products to visitors to its websites. One team member would spend half a day a week updating recommendations across thousands of products using complicated spreadsheets. “We decided we could not continue with this legacy approach,” says Luu.

“When we A/B tested the recommendations from Recommendations AI against our previous manual system, we identified a double-digit uplift in revenue per session.”

Peter Luu, Online Analytics Manager, Hanes Australasia

Evaluating Recommendations AI

Luu and his team began looking at Recommendations AI, a Google Cloud AI product. Developed using the experience gained from delivering content across Google Ads, Google Search, and YouTube, Recommendations AI uses Google Cloud machine learning architectures to provide personalized recommendations based on customer behavior and changes to product ranges, pricing, and offers.

The business engaged with Google Cloud to optimize Recommendations AI for its needs. “We worked with the Google Cloud engineers at Mountain View in California once or twice a week during setup, and they showed a deep interest in how Recommendations AI could help improve the experience and revenue performance of our websites,” says Luu. “The experience was fun and also gave us deep insights into how Google Cloud builds its own products.”

Recommendations AI also provided an easy entry point into machine learning for a business that was still exploring the potential of the technology. “The product is extremely easy to use—Google Cloud has provided the expertise, functionality, and performance, so we do not need to be machine learning experts to make the most of it,” says Luu.

The business initially integrated Recommendations AI into pages for 10,000+ products for its popular Bonds, Bras & Things, and Sheridan brands, and was impressed. “We conducted our first A/B test of Recommendations AI on our Bonds website, using Optimize from the Google Marketing Platform, and the process, including the time needed for the machine to learn, took about a month to complete,” says Luu. “We moved onto our other brands once we achieved positive results.

“We found Recommendations AI does a very sound job of providing recommendations to consumers—even for newly available products as we load them online,” says Luu. “The machine learning architecture builds knowledge very quickly and provides relevant recommendations based on browsing history.

“In other words, Recommendations AI provides fresh and optimal recommendations, all day, every day.”

To create the recommendations engines for Hanes Australasia brands, Recommendations AI accesses the business’s product catalogs, including product titles, descriptions, stock availability and pricing, and end user behavior, including searches, views, and purchases. “We stream every single page or product view—plus events such as adding to bags and purchases—to Recommendations AI to help train the machine learning models that determine the products to present to users,” says Luu. The models base these determinations on the pages a user has viewed, optimized to maximize conversions. The more a consumer uses our site, the more these models get to know them and the more compelling and personalized the recommendations provided, increasing the customer’s propensity to purchase.”

“Recommendations AI delivers extremely good data execution and shows how Google Cloud can turn data into real commercial value.”

Peter Luu, Online Analytics Manager, Hanes Australasia

Extending personalization

Hanes Australasia is experiencing measurable improvements in transaction conversions and revenue on the product pages on which Recommendations AI is operating. “When we A/B tested the recommendations from Recommendations AI against our previous manual system, we identified a double-digit uplift in revenue per session,” says Luu. Based on its initial experience, Hanes Australasia plans to extend Recommendations AI to additional sites within its portfolio and to personalize the marketing emails it sends to customers.

Furthermore, as Hanes Australasia builds experience with machine learning, it plans to further explore Google Cloud AI and machine learning products. For Luu and the broader organization, Recommendations AI showcases the importance of data to growth and expansion. “Recommendations AI delivers extremely good data execution and shows how Google Cloud can turn data into real commercial value,” he says.

Ryan Wilson, Head of Online at Hanes Australasia, adds, “Recommendations AI has improved the online experience for Hanes Australasia customers and delivered material value to our business with compelling product recommendations. We can also use the product to provide insight into basket building and merchandising opportunities for our valued wholesale partners. We look forward to using Recommendations AI to further enhance outcomes for our customers and partners.”

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About Hanes Australasia

Hanes Australasia is home to iconic Australian apparel and lifestyle brands including Berlei, Bonds, Bras N Things, Champion, and Sheridan. The business sells its products through its retail network of approximately 550 stores, its 14 websites, and its extensive wholesale network. Hanes Australasia (formerly Pacific Brands) was acquired by HanesBrands Inc in 2016. Headquartered in Melbourne, Australia, Hanes Australasia employs over 4,000 people and operates throughout Australia, New Zealand, South Africa, the United Kingdom, United States, China, and Indonesia.

Industries: Retail & Consumer Goods
Location: Australia