McKinsey: Data key to understanding diverse Asian consumers

16 Nov 2017

The Asian region is a unique mosaic of cultures and demographics. Home to a multitude of ethnicities, it has a rising middle class that will account for nearly 60 per cent of global middle-class consumption by 2030. Hence, it is no surprise that global companies are looking towards this region for business growth.

To successfully operate in Asia, companies must jettison a one-size-fits-all approach. A number of factors influence Asian consumer preferences, and organisations have to customise their products and business models to meet the complex needs of these diverse customer groups.

Ali Potia, head, Asia Consumer Insights Centre, McKinsey & Company
discusses why gaining in-depth insights into Asian consumers is critical for decision making, and how companies here are beginning to use such insights to achieve commercial excellence.

Ali Potia, head, Asia Consumer Insights Centre, McKinsey & Company

How important is Asian consumer data and what approaches are companies adopting to maximise the insights they get?

AP: With Asian economies likely to contribute more than half of all growth in global consumption by 2020, it underscores the importance of gathering detailed data on the Asian consumer landscape, where purchasing behaviours can vary based on culture, economic development and income levels. By leveraging sophisticated analytical tools to churn out insights from such data, global companies are better placed to tailor their offering to the preferences of consumers at a very local level.

While companies are still leveraging traditional quantitative market research techniques to generate preference datasets, these are increasingly being supplemented with actual behavioural data drawn from multiple sources; for example, anonymised telco data, retail point of sales data, social media listening, ecommerce purchasing data.

However, even as access to data sources and the volume of data are growing rapidly, companies are struggling with generating actionable insights from the data. We have seen companies where data scientists have built sophisticated models, but the link to actual business decisions is tenuous and they fall back to tried and tested quantitative surveys or rules-based heuristics.

Companies are, thus, deepening their qualitative insights to complement big data and advanced analytics techniques.

Qualitative research today helps bring customers to life. It illuminates their needs, their decision-making processes, and their reactions to companies and brands. For instance, design researchers spend a full day with shoppers to gain a comprehensive understanding of what is driving the shopping decision. This observational and iterative research enables them to understand the psyche of their varied customer base and unravel hidden insights that cannot be captured even through hardcore data crunching.

To maximise such insights from design-based research, MNCs are realising that they need to be closer to their customer segments. This has prompted many of them to relocate insights functions to regional and country-level offices across Asia.

As customers in many Asian markets expect a very wide variety of offerings and short innovation cycles, success now requires companies to not only understand regional and local tastes and preferences, but also to design products and services in Asia.

How has technology enabled better consumer insights, compared to the past?

Historically, companies conducted surveys and focus groups to deduce prevailing consumer trends. A major problem with these traditional methods is that they rely on customer memories and stated preferences, which might not necessarily reflect actual purchasing behaviours.

Technology-backed tools such as digital surveys and social media platforms on the other hand garner immediate consumer feedback, thereby not relying on consumer memories. Such tools also allow companies to access a treasure trove of actual behavioural data. For instance, behavioural patterns generated from online purchases reflect real-time consumer behaviours as opposed to stated preferences.

These newer technology-enabled research methods have helped companies to more realistically assess their customers and gather in-depth data.

How do you see companies in Asia deploying advanced data analytics to translate consumer insights into commercial excellence?

We have observed that organisations here, especially in the consumer and retail space, are keen to capitalise on analytical insights to enhance their business performance. We work alongside our clients to generate valuable consumer insights using advanced data analytical methods, which allow companies to make better, faster decisions in their day-to-day business and deliver improved performance.

For instance, we worked with an FMCG company looking to expand its product’s presence in an emerging Southeast Asian market. Using data analytics, we first looked at concentrated market data to derive the profile of the customers likely to purchase its product. This was followed by a heatmap showing where these target segments are likely to live and shop. We then overlaid this data with an exhaustive geospatial study of both small and large retail outlets. This extensive geospatial analytics helped the company gather rich insights on which stores to prioritise to maximise their revenues.

The final step, and one that many overlook, was to drive these insights to action. We developed simple app-based human-machine interfaces that allowed managers to prioritise salesperson routes and give them specific scripts/action steps for each type of outlet they would encounter that day.

In another instance, we worked with a retail client who was looking to optimise their store space. In the past, retail merchandisers relied on their market instinct and years of experience to decide on what stock keeping units (SKUs) to stock on their shelves. However, many merchandisers in Asia are now leaning towards analytical data insights to better gauge purchasing patterns.

Based on three years of a retailer’s sales data, we created customer decision trees and assigned scores to individual SKUs. This allowed us to analytically zoom into what SKUs the client must have on their shelves to attract customers. Simultaneously, by highlighting the less important SKUs – a powerful insight – we helped the merchandiser extract discounts from his supplier, thereby enabling better commercial decision making.

Why did McKinsey choose to set up your Asia Consumer Insights Centre in Singapore?

AP: Given its connectivity to Asia, established R&D infrastructure, well-educated workforce, and strong cluster of creative, branding and market research firms with regional mandates, Singapore is a natural hub for global companies wanting to understand and develop regional consumer insights. Many global companies, including our clients, have their regional headquarters here, and it served as a natural base to locate closest to our clients. The geographical connectivity allows us to quickly access a wide subset of Asian markets and acquire a nuanced understanding of different customer segments.

Lastly, the increasing number of digital companies establishing here also enables us to tap into the latest sources of data and consumer insights emerging from digital sources.

How do you expect the usage of consumer insights to evolve in the next three to five years?

AP: Constantly evolving consumer preferences and tastes will continue to propel the business need for high-quality analytical insights. Also, as analytical tools become more ubiquitous and data access becomes more affordable, it will become easier for more companies to weave in analytical insights into their decision making. We expect that frontline managers will have access to analytical tools in much the same way they have access to spreadsheets and word processors today. These analytical tools will enable more powerful insights-based decisions across both marketing & sales and operations.

Going forward, we can also expect existing users to develop more creative methods to extract deeper insights from their data. A case in point is the design-based research that I mentioned earlier. Expect more of such innovative approaches as consumer insights are used both widely and deeply by more and more businesses.