By Praveen Thakur, Vice President Technology Business Unit, ORACLE ASEAN.
With more than 60% of the world’s population and some of the fastest growing economies, Asia has emerged as the most exciting and promising market for retailers around the globe.
According to recent industry research, Asia will remain as the main engine of global retail development with an average annual growth rate of 6% between 2011 and 2015; and Asia is also experiencing phenomenal progress in online retailing with an average growth rate of 20% per annum.
Today’s retailing experience is very different with a combination of multiple online and offline channels, product proliferation, globalization, easy comparison shopping, group-buying sites and individualized offers that can be delivered anytime, anywhere.
Modernized retail customers are always online, whether selective or social. This creates a new paradigm shift for marketers who must now learn to understand each customer better instead of individualizing them to a generic market segment. The target is to present a personalized, tailored offering, unique to the individual customer to improve on relevance and perceived customer value.
Mastering Big Data will help the retailers understand customer behavior segmentation better and what actions trigger behavioral attributes in different segments and channels thus improve the marketing execution at the time of purchase and the oyalty programs by revealing what factors truly impact customer loyalty and retention, such as customer experience, ease of use, value for money and the effects of rewards programs.
Improving Customer Experience and Gaining Competitive Advantages
In the war of acquiring, retaining and enhancing customers’ experience, retailers understand that improving customer satisfaction is vital. However, in many organizations, from sales to customer service, often work in separate silos and customer feedback is often not allowed to flow freely between the different operations, resulting in ineffective distribution channels.
As a result, retailers are beginning to compile more data on customers and their purchases than ever before, and build a single view of customers’ information to be shared across the board. This data provides a potential wealth of insight into the demographic attributes, tastes, preferences and buying patterns of the customer, which allows marketers to react quickly to the ever-changing demands of the market space.
For instance, merging structured with unstructured content to find underlying customer satisfaction issues allows enterprises to proactively monitor customer satisfaction levels.
Tracking the social media and analyzing feeds from Twitter and Facebook can help retailers find a correlation between product sales, support and customer voice to validate the true issues impacting customer satisfaction.
It becomes more prominent especially in combating customer churn, which has been a major problem for all retailers. With big data solutions, retailers can give insight not only on what the churn rate is, but also the reasons behind the churn, and how best to address them. Data sophistication enables pinpoint accuracy in developing targeted marketing approach aimed at specific customers to influence their paths to purchase and enhance their shopping experience.
The insights can be leveraged to optimize product offerings and promotions, give offers to specific customer segments or even precisely targeted customers and drive higher returns and greater customer satisfaction. Even competitors’ customers can be tracked and analyzed to understand industry trends and customer propensity to buy certain products or services.
Retailers also use Big Data solutions to streamline functions like merchandising and supply chain; and marketing can use this technology to reduce marketing spend, while keeping results the same or for a competitive advantage.
The ‘browse but not buy‘behavior is a well-known problem for retailers around the world. In light of this, new dynamic customer experiences driven by big data analytics is becoming relevant for building more cohesive loyalty on the basis of assessing customer need.
Today’s customers expect a seamless shopping experience across the multiple sales channels – web, mobile, and physical store location. While multi-channel management or connecting channels was the key issue in the past, omni-channel management is today’s challenge. The big data platform and predictive customer behavioral analytics are now under serious consideration of every retailer to develop a holistic view of customers in terms of interaction models, channels, behavioral segmentation, responses, marketing strategy, and marketing execution.
