The small data challenge for big business

Great customer service is what all businesses should aspire to, and this means being able to meet customer needs intuitively — be it the kopitiam uncle who remembers exactly how you like your coffee, or the business-class air stewardess who knows when to bring you a cup of tea.

Understanding why a purchase was or was not made is critical to getting inside the mind of the customer. This is why so-called Big Data plays such an important role in contemporary marketing.

Businesses want a better understanding of customers in order to be able to improve their product range to meet customers’ changing needs.

This push towards collecting and processing ever more data is why we receive emails reminding us of a particular product we once looked at online. It is why we find adverts in our Facebook feeds for hotels in destinations we Googled. To some consumers this might seem intrusive, but it is all in the name of improving service.

Say you are headed to the airport on a trip. Your insurance firm might text you with an offer for travel insurance, by knowing your location and detecting when you enter Changi Airport. Instead of a pushy sales offer, the text might be a useful reminder, just before you take off.

Data — or more precisely data analytics — is transforming the way we shop and how we, as consumers, interact with businesses. The mistake many businesses make is that they have a compartmentalised view of the data they collect — intelligence is not useful unless it leads to action.

In Singapore, two apps — both by the Land Transport Authority (LTA) — show the difference between raw data and actionable intelligence.

In 2014, LTA released the Taxi-Taxi app. Like Grab and Uber, it showed available cabs near the user — but that was all the app offered. Knowing the location of the cabs was useless, without being able to hail the cab or identifying the best areas to hail a cab off the street.

Contrast this with LTA’s Beeline, launched in 2015: A bus service platform with crowdsourced routes. Users can book seats on established routes or suggest new routes. By giving the users and bus service operators useful intelligence and the ability to act, the Beeline platform has continued to grow while creating value for both sides.

Traditional brick-and-mortar retailers, banks, telcos and the like may claim to have Big Data, but scratch the surface and most will find that the data they have is only in terms of financial transactions.

Restricted to this limited view, they will never achieve the breadth of data they need to understand what drives customers and their decision-making.

MAKING DATA COUNT

The financial industry is one sector that has become complacent in the illusion that the data it owns is valuable. Like telcos, banks know who their customers are and what their banking transactions are like, but, crucially, they do not have precise information as to how or why their behaviour may change.

Traditional retailers have a similar problem: They understand their customers only in terms of a few basic metrics — for example, how much of a product is sold each a week and which brand is most popular. This data might be “interesting”, but provide no insight that can be turned into action — such as why a customer preferred one item and not another, or why customers browsed but left the store without buying anything at all.

Contrast these with giant e-commerce firms such as Amazon or Alibaba, who are in pole position to harvest the widest and most complete data, and to capture the most opportunities from it. Beyond just the “who” and the “what”, they get answers to the critical questions of “how” and “why”.

This allows them to delve upstream into the customer journey, building up profiles that give insight into what drives sales, enabling them to anticipate and better serve their customer’s needs. By offering free gift-wrapping options, for example, an online retailer gains greater intelligence on which products are commonly gifted, and when.

By asking customers to fill in a free greetings note to the receiver, they can intimately understand why the item was purchased.

Amazon, for example, has used this intelligence to move into manufacturing — with more complete, broader data, it is able to build a better product than the original manufacturer. As a result, Amazon’s AmazonBasics brand now sells more batteries than Duracell and almost as many diapers as Pampers.

Alibaba, meanwhile, has been able to open up a hugely successful finance arm, Ant Financial, because it saw an easier way for customers and merchants to transact. Last year Ant cleared some US$1.7 trillion (S$2.31 trillion) in transactions, making the firm, which originated from AliPay, reportedly worth an estimated US$75 billion. By becoming the retailer, manufacturer and the payment gateway, Alibaba and Amazon are locking consumers deeper into their ecosystem and making it harder for competitors to catch up.

All this makes for a perilous time for traditional businesses. With data-driven global competitors eroding profits, not clearly understanding customer needs is a business killer — look no further than the fast-emptying malls of Orchard Road.

That does not mean, however, that traditional businesses have no recourse. Technology has magnified the benefits of collaboration, and firms across sectors would do well to explore the potential for data integration to bring them greater width and hence better intelligence. Cooperation between a bank, a telco and a retailer, for example, can help all parties delve into how, why and when customers make purchase decisions. Likewise, opportunities exist for cooperation between traditional and online firms.

Here in Singapore, for example, property developer CapitaLand recently sealed partnerships with Alibaba and Lazada to create an integrated shopping experience for consumers online and off. While some traditional firms may see this as making a pact with the devil, with a wider pool of data, businesses can better understand their customers and the number of possibilities and opportunities grows.

Plenty of software and services exist to do this, yet many traditional business remain stuck in their silos and set ways of thinking. Firms that have been led for years by gut instinct find it hard to give up the notion that they know best what their customers want.

Moving away from this means understanding the real value of Big Data, looking beyond simple quantity to actually deliver actionable business intelligence.

ABOUT THE AUTHOR:

Keith Carter is an associate professor at the National University of Singapore (NUS) School of Computing. He will be a panellist at the upcoming NUS Business School/TODAY forum “Dollars, Digits and Data: Trends and Challenges in Digital Marketing” on Wed. Find out more at www.bschool.nus.edu.