What does shopping on-the-go and big data have in common?

The evolution of technology has without a doubt, altered the way in which many lead their lives. This includes the way we carry out our daily routines to the way we foster relationships. You can no longer severe yourself from the wired landscape of the Internet of Things. This is especially evident in this digital age that we live in where technology is so readily available to us. Or rather, technology has seamlessly integrated into a norm that not only increases efficiency in the way we do things but also in turn, become increasingly productive.

Similar to the evolution of technology is the fast-changing retail landscape in Singapore. Given the aggressive rise in the appeal of the e-commerce sector, brick-and-mortar retailers are also diminishing at a faster rate. A study from Google and Singapore’s Investment Firm – Temasek Holdings, predicted the region's internet economy to grow to $200 billion by 2025, driven mostly from growth within e-commerce.

What is the future for the e-commerce sector?

Big data and analytics are two key tools to facilitate the sector in gearing towards a more customer-centric focus. The ability to track volatile changes in patterns and behaviours of customers is made possible and more importantly, easier with the use of big data and its analytics.





The big players in the field

RedMart, Lazada and Zalora are three locally famous examples who have heavily invested in the technology of big data in an attempt to improve the efficiency and productivity of their business.


Big data has helped its company to improve their logistics’ supply chain. Beyond the ability to study buying patterns of consumers, the embedded technology has also helped to predict when products will be likely to be sold out, or the number of days left before a particular item runs out.

When a brand is able to provide an optimised and unique consumer experience, the likelihood of customer engagement in turn increases too. This boosts the relationship between the brand and its consumers and increases brand loyalty.  

Lazada Singapore

Aligned with RedMart’s customer-centric objectives, Lazada Singapore has also leveraged on technology in big data to incentivise its consumers in their repurchase. Lazada currently plans to use data science to help its merchants customise offers for specific customer groups based on age, gender and other preferences.

"The data that we collect allows us to better understand the shoppers' profiles and general habits. From here, we are able to streamline how shoppers find products through targeted marketing and offers, better product recommendations, and more relevant and interesting products and product mix on display; which results in a better user experience," Martell Hardenberg, Executive Vice President of Lazada said.

He added that the big data team in Lazada is responsible for handling data science, data engineering, as well as search and data tools. Despite being a neophyte in this tool, Hardenberg has added that they have been able to discover a wealth of insights about their customers through big data.

Zalora Group

Similarly, Abhishek Vats, Regional Associate Director Business Intelligence & Payments of the Zalora Group has mentioned that 40% of its visitors utilise mobile devices to access its store. Capitalising on the presense of big data, it focuses on a myriad of ad-hoc projects with some brands to help them understand their customers based on data.

Zalora’s revenue comes from tier-1 countries such as Singapore, which has a mature market consisting of people with higher purchasing power. Big data is then used to focus on targeted online and offline marketing. Dynamic pricing—the ability to judge page views according to products and thereby adjusting prices accordingly to entice consumers to purchase – is yet another avenue that they are looking into with analytics and algorithms.


Who is able to analyse big data?

While immense growth awaits these flourishing companies, a talent drought persists with struggles of sourcing data analysts and engineers. 

To analyse and make use of the analytics behind the technology in big data, this can easily translate to individuals who have at least 7 years of experience in a technical role – with at least 2 years of experience using big data technologies. As such, the demand of these roles will only get steeper, especially those with knowledge in web programming languages and experience with other software frameworks. Other skill sets such as cloud computing, proficiency in Hadoop Architecture and Design are all part of an increasing demand that is able to provide analytical solutions.

Despite the imminent talent crunch, Lazada remains positive.

Singapore has a great university system and corresponding STEM (Science, Technology, Engineering and Mathematics) programmes, which produces a pool of highly-qualified STEM graduates. Many data scientists are really attracted to the complex challenges that e-commerce provides.

While the youths gear themselves up with the relevant skills, individuals within the workforce should also engage in training and development courses that are relevant. Companies who wish to invest within technology for big data are also encouraged to foster development programmes to soften the strain on the lack of tech talent.

Data engineering – which includes collecting and processing data, as well as operationalising results – are other roles which should not be overlooked as they ensure sustainability of businesses in the future.

What’s in it for the future?

The government’s plan to increase spending within the local start-up ecosystem will most likely increase within the technology sector later this year. As such, we are expecting to see an increase of investments within the technology scene including the security and governance components surrounding enterprise systems given the rise of cyber-attacks. 

The use of Artificial Intelligence (AI) is also likely to increase within retailers to not only take into account consumer behaviour, but to map, compute, analyse and predict data in real time.

To find out more about these technologies and the landscapes that are evolving, do contact us via the form below or follow our LinkedIn page for more industry insights.

Sources: CNBC, MIS Asia, Paypal, Singapore Business Review, Dailysocial.com

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