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Pivot From Survivor To Thriver: Data Warehousing For Retailers

But, how?

Photo by Brett Sayles from Pexels

By, Nilantha Brito

A once thriving sector in Southeast Asia where consumer spending was forecasted to reach US$1.38 trillion in 2025, retail is now one of the sectors most impacted by the current situation. 

In Singapore, retail sales fell by 13.3 per cent in March 2020, the biggest drop in 22 years. This has led to the likes of Esprit, previously a successful global retailer, closing all of its retail stores in Asia outside China, following a prolonged sales slump that was only exacerbated with the recent downturn of events. It also comes on top of the ongoing trend of physical stores losing market share to e-commerce, which is only expected to accelerate.  

To move beyond survival, retailers will need to refine their existing business models and find new ways to grow revenue opportunities – but how?

A suggestion comes from a new study from the University of Warwick, which proposes that future investments in flexibility, visibility and automation are necessary to adapt to any future crises. It also calls out that technologies, such as AI and machine learning (ML), will play a key role in helping retailers navigate future disruptions, whilst still helping meet customers’ expectations.

Data management for retailers in the digital age

This is sage advice. Already, retailers are using technology solutions embedded with artificial intelligence, ML and automation to make a difference, especially in the area of data. 

Data is being generated at every moment – from eyeballs on banner ads, to the moment someone enters your website or store to make a purchase or redeem loyalty points. And it can all be harnessed to drive business value and improve the consumer experience. The challenge is that so much data is now available internally and from third party sources that it can be hard to make sense of – but not impossible.

For example, Forth Smart provides over 120,000 vending kiosks across Thailand to allow users, many of whom don’t have a bank account, to shop online as well as to top up e-wallet apps, prepaid mobile phones and online games, pay bills and transfer money to friends and family quickly. 

These kiosks handle data from a stream of more than 2 million transactions a day. By leveraging the ML algorithms found in Oracle Autonomous Data Warehouse, the company has been able to generate real-time insights and better understand its customers’ behaviour, segment them to improve its targeting and predict how an offer will fare, resulting in doubling the ad conversion rate.  

A similar use of this autonomous technology has also helped PTG Energy Public Company Ltd, known for its rapidly expanding chain of over 1,609 petrol stations and a network of convenience stores and coffee shops across Thailand. Using advanced analytics, it can now bring data from multiple systems together easily and analyse everything from point of sale transactions and loyalty data across its chain of fuel and retail outlets, through to customer information. As such, they can now gather accurate data on customer behaviour in real-time, to tailor personalised, behaviour-based offers and better customer loyalty programmes. 

New lenses for old frames with modern data warehouses

Both of these examples clearly show that the right modern tools leveraging the cloud and emerging technologies like AI and ML enable retailers to improve the customer experience and drive e-commerce conversions, but they can also do much more.  

Autonomous technologies can also help automate manual IT tasks, reduce administrative work and operational overheads. They can help retailers to quickly migrate their data to the cloud and manage it on their own, even with limited technical backgrounds. 

And when all this information is stored on a centralised platform on the cloud, it facilitates collaboration across multiple channels within teams and between different retail partners. Business owners and employees can access information anywhere, anytime to make informed data-driven decisions across multiple channels and distributed supply chains – a must-have operation strategy to cope in the heightened remote working environment today.  

Keeping consumer confidence

Another clear advantage of adopting modern data warehouses is the security protection that comes along with it. 

From credit card information to personal addresses, retailers hold so much valuable information that can be susceptible to cyber-attacks if inadequate protection is not put in place. Modern data warehouses infused with AI and ML technologies enable the automatic detection of new cyber threats and support the development of strategies to ensure regulatory compliance and continued consumer confidence. 

Pivoting from survivor to thriver

While retailers across the region may be at different stages of maturity, the need to start a digital transformation journey is uniform. 

Although there is no clear roadmap for what lies ahead, with the right technologies to paint a 360-degree view of customer activity and preferences, retailers can much better track engagement and the success of marketing campaigns in real-time. They can then be agile, make changes, create opportunities for increased sales conversion, customer retention and brand loyalty and keep customers coming back for more. 

One thing is certain, data is the foundation of their business, and being able to see data in new ways can have a profound impact on business operations and revenue streams. And while the current environment has certainly thrown a spanner in the works, it gives retailers a window of opportunity to see data in new ways – to survive and eventually thrive in the new economy.

Nilantha Brito is a Senior Director, Technology Cloud at Oracle ASEAN

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