Retail in Asia

In Telligence

Retailing through uncertainty: Leading with data

Asia leads digital retail market over Europe, US

By Donald Ong, Senior Vice President, Advisors, Data & Services, Mastercard Asia Pacific

This year, the internet economy in South East Asia soared to $100 billion – more than triple its size four years ago – and is expected to triple again by 2025. Along with this staggering pace of disruption, consumers’ tastes in the region are constantly evolving across styles, brands and price points.

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In response, many retailers are relying on new predictive analytics to help them stay ahead. For example, in August Nike announced its acquisition of Celect, a cloud-based predictive analytics platform that helps retailers make data-driven decisions to optimize their inventory.

Tools like these are even more crucial in Asia where economic growth is rapidly transforming the region’s complex and diverse societies. Every year retailers see surprising new shifts in consumer behaviour, sometimes confined to pockets within a country, sometimes nationwide. Assumptions that were reliable in 2018 can suddenly prove very wrong in 2020.

As a result, good internal data is table stakes and the ability to analyze that data a potential competitive advantage. But the key differentiator is the ability to bring multiple data sets (internal and third-party) together and make accurate predictive decisions. Those retailers who master this process will not only weather the current environment but emerge stronger as a result of it.

Having the right data

Just as the quality of a garment is determined by its fabric and stitching, the quality of a company’s predictive decisions is determined by its data inputs and the way in which they’re woven together.

The challenge for retailers begins with identifying the right data to analyze. Many have an abundance of their own consumers’ purchasing data, but this backward-looking information may not reflect incoming trends until they are already well-established. For adverse market movements, this may be too late.

This is where coupling retail data with third-party data sets comes in. Benchmarking one’s own data against broader industry trends can help retailers read consumer signals sooner and respond faster. One such contextualizing tool is Mastercard SpendingPulse™, which reports on national retail sales across all payment types in select markets around the world, including Hong Kong, Japan and Australia. The findings provide up-to-date statistics for retail segments including online, apparel and grocery and help retailers understand how they may be performing vs. the industry, as well as how consumers are spending across segments. Spending Pulse reports are released ahead of advance sales estimates, with a strong correlation to government-published data, and hence can be valuable inputs to retailers’ strategic planning and forecasting efforts.

Retailers can further localize their benchmarking using Mastercard’s Retail Location Insights (MRLI). With this tool, retailers can zero-in on specific geographies and understand how they’re doing in terms of overall sales, ticket size, transactions, stability and growth. These insights can help a retailer evaluate their stores relative to the retail health and category health of a specific local area. The tool can also help identify which retail areas are experiencing growth or decline, and where there may be opportunities to identify untapped opportunities for outreach and expansion.

Finally, Mastercard’s Local Market Intelligence Platform provides retailers with an online dashboard that organizes and highlights store-level performance against nearby competitors. It focuses on three key areas: business performance, customer behavior, and competitive standing. With this information, retailers can understand whether new initiatives are working, or whether performance is simply fluctuating with the market. The resulting insights can help to drive some of the most important decisions a business can make about its customer acquisition and loyalty strategies, as well as operations, marketing and personnel.

Putting the numbers together

Getting hold of the data is only half the battle though. Interpreting it correctly is the bigger challenge. Mastercard-sponsored research with Harvard Business Review Analytics Services has found that only 18% of business leaders are happy with their return on analytics investment, due to analytics processes differing between departments, poor communications between teams, and results that are out-of-date by the time they are needed.

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Leaders need the ability to answer very specific questions about their own businesses such as: what’s the true causal impact of a sales promotion across channels, and how should store operating hours vary between locations to maximize profits? In many companies, the answers to these questions will depend on who you ask, and what methodology they have used.

One approach to answer these is to simply roll out a new strategy or marketing campaign across every location, or with every customer, and see how it goes. This is fraught with risk. While a promotion may seem to be effective when measured in terms of redemptions, it may actually end up cannibalising sales of other items or other channels, or simply pull-forward sales that would have happened anyway. How can leaders know how best to target a campaign before rolling it out?

Mastercard’s Test & Learn® software helps leading retailers across Asia solve this problem by empowering them to leverage its scientific method of understanding the relationship between cause and effect at scale.

First, retailers can use the platform to identify a subset of stores (including online) or customers that are representative of their entire network. This is particularly important in Asia, given the dramatic differences between regions in countries such as China and India. Assumptions made about retail patterns in Chennai will not necessarily hold true in Delhi.

After introducing a new initiative in this subset, retailers can then use the Test & Learn® platform to compare the performance of these “test” stores or “test” customers to that of a highly-similar control group that did not receive the new initiative. By following this approach, retailers can accurately measure and optimize their marketing, merchandising, promotional, capital and operational initiatives.

Further, as a platform technology, Test & Learn® enables retailers to apply a robust and consistent methodology across all their tested initiatives, creating a ‘single version of the truth’ and eliminating internal arguments over data interpretations. The speed of Test & Learn® also allows retailers to run more experiments and derive results from them more quickly, enabling more accurate and timely decisions – from planning new stores, to optimizing them for specific markets, to strategizing for the future.

Finally, connecting all of the dots between internal and external data, predictive algorithms, and human experience is where advisory services come in. Partnerships with industry consultants can be a crucial part of enabling retailers to best understand and leverage data for their businesses. Mastercard’s advisory team works with corporations in the Asia-Pacific region to ensure they are aware of the power of the tools at their disposal, and derive maximum utility from the data and systems they have.

For more information, visit:

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About author:

Donald Ong is Senior Vice President, Advisors, Data & Services, Mastercard Asia Pacific and is responsible for building and scaling Mastercard’s Consulting, Insights, Analytics and Test and learn product lines across the region. Prior to this appointment, Donald was the Country Manager for Mastercard Thailand and Myanmar where he led the strategic development and expansion of the business in both markets.