From data deluge to data insight: Reaping the data dividend in retail

Dongbae Park, Director, Retail Industries, Microsoft Asia Pacific
Dongbae Park, Director, Retail Industries, Microsoft Asia Pacific

The retail industry in Asia has enjoyed healthy growth and remains a destination of choice for global retail chains. However, retailers are facing greater competition, higher operational costs and other challenges like slowing regional economies, high inflation and interest rates. 1Retailers need better insights in order to better manage their resources and connect with their customers.

Asian retailers have a lot of data about their customers; in fact, they’re drowning in it. From searching to purchasing, transactions constantly generate data. This data deluge could swamp retailers — or buoy them. According to a recent IDC study commissioned by Microsoft, retailers worldwide could gain US$94 billion in value over the next four years by improving their synthesis, analysis and use of the data they collect; we call this the “data dividend”.

It used to be that to analyze significant amounts of business data, retailers needed a data scientist using specialized tools — and creating jargon-heavy reports. But with business software available today, retailers can start small to plumb their data for better insight. Virtually any store manager can import, drag and drop data to analyze their displays, stock management, customer engagement and more.

Small projects are quicker to execute than large initiatives, so retailers can see immediate results — and dividends.

There are several ways retailers can leverage existing data and tools:

  • Cross the streams. Start by identifying your data silos — such as sales category data, supply data or campaign results — and finding ways to bring them together. How do specific product line sales compare across locations? How do loyalty card sign-ups correlate with preorders or returns? Assessing your data helps you formulate smarter questions about your business.
  • Zoom in. Broad demographic segmentation is giving way to microsegmentation — using more factors to create richer, more individually detailed target groups. Instead of a vast category of women 18 to 35, microsegmentation can give you women 25 to 29 who live in specific postal codes, listen to KPOP, shop five times per month, and drive one-third of sales for your top product. Such detail helps businesses personalize offers and service to increase sales.
  • Go public. Supplement your proprietary data with public data, much of which is available for free in formats that can be imported directly into spreadsheets or other applications. Weather data from local weather service providers plus daily sales by store can reveal how weather influences shopper behavior. Census data shows which customer segments are growing fastest in different parts of the country. And data from Twitter and Facebook can reveal customer sentiment and give early insight into trends — especially for new technology or product categories for which your past sales data simply can’t offer guidance.

An example of big data in action is restaurant chain Blackball, which specializes in Taiwanese tea and desserts. Blackball uses perishable components in its desserts, so it is critically important to get ingredients to the right place at the right time. By building a hybrid cloud solution with Fusionex that leverages Windows Azure HDInsight service, they are able to integrate sales data with regional weather patterns and social media feedback, allowing them to manage their stock more efficiently and better serve their customers2.

Retailers can tread water in the data deluge, or dive in to create data dividends. By starting small, with existing data and business tools, retailers can channel a productive data stream that brings insight, informed decision-making and ultimately profit.


This story was first published on Retail Tech Innovation on January 26, 2015.




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