As the might of online shopping looms large, brick and mortar retailers in Asia should look at analytics as a way to improve, enhance or expand customer loyalty since existing customers represent up to 80% of future revenue, says leading data and analytics company GlobalData.
The company estimates that with the onslaught of online shopping, up to 20% of outlets may close in next five years. But, IT-led transformation is what the industry should look to reset the ‘misalignment’ between buyers and sellers. The company forecasts that ICT spending within the Asian retail will exceed $31bn this year and grow at 5% per year.
Dustin Kehoe, Technology Research Director at GlobalData, says: “The stakes are high. The retail sector is moving IT spend from a ‘keeping the lights on,’ mode to one where investing in technology is essential to permanently and irreversibly change their business. Consumers will continue to shop online, but classic ‘bricks and mortar’ stores are reinventing themselves through technology. Data is at the heart of the strategy.”
The goal is to drive an integrated customer experience that is both relevant and personal, and aligns with the tempo of customer journey. Essentially high street retailers are changing the game by swapping out the architecture.
Kehoe continues: “With over 2.7 billion smart phones subscriptions projected in use across Asia by the end of 2018, mobility is the logical place to start. With cloud as the core platform, retailers should use mobile and Wi-Fi analytics to understand customer footfall, age, gender, demographics and time browsing in stores to reconnect with the odyssey of long lost shopper. These capabilities, especially in markets like Australia, Korea, Japan and China, can be overlaid with video analytics to bring more contexts.”
The use of open application programming interfaces allows analytics to be integrated into point-of-sale and CRM to improve ‘on the shelf availability.’ Location-based services with geo-fencing can help businesses to visualize traffic flow through stores, identify hotspots, chokepoints and predict the future revenue by shelf placements and promotions. The future use of artificial intelligence may even be able to detect patterns invisible to today’s systems.
Kehoe concludes: “While research shows a willingness of customers to provide personal details (within reasonable boundaries of privacy) as long as there is value in return. It will be imperative that data is protected at all costs, not shared with third-parties and collected in an aggregated way that safeguards privacy. This clearly explained and opt-outs are also visible. A retailer who can strike this balance will be the likely success stories.”
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