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IBM > Case Studies > DLF Ltd. Mobile technology and cloud-based analytics used to understand and influence customer behavior
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DLF Ltd. Mobile technology and cloud-based analytics used to understand and influence customer behavior

Technology Category
  • Analytics & Modeling - Real Time Analytics
  • Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
  • Retail
Applicable Functions
  • Business Operation
  • Sales & Marketing
Use Cases
  • Real-Time Location System (RTLS)
  • Retail Store Automation
Services
  • Cloud Planning, Design & Implementation Services
  • Data Science Services
The Challenge
DLF Ltd., one of India's largest commercial real estate developers, wanted to enhance the mobile shopping app of the DLF Promenade mall to deliver insights about customers that retailers could use both to enrich the shopping experience and to influence customer behavior. The mall, located in an upscale community of over 100,000 residents in the Delhi National Capital Region (NCR) of India, occupies more than 4.6 million square feet of real estate and features many high-end international brands. The challenge was to help retailers develop a higher conversion ratio of visitors to buyers by providing them with valuable insights about customer behavior.
About The Customer
DLF Ltd. is one of India’s largest commercial real estate developers. DLF Promenade, one of the premier retail properties of DLF Ltd., is a premium-brand, fashion-themed shopping mall in Vasant Kunj, an upscale community of more than 100,000 residents located in the Delhi National Capital Region (NCR) of India. The mall occupies more than 4.6 million square feet of real estate and features restaurants, cinemas, an expansive children’s playground and fashionable shops representing many high-end international brands.
The Solution
DLF Promenade uses intelligent, location-based technology, device-resident mobile data and cloud-based near-real-time analytics to gain valuable insights about onsite and in-store customer behavior. By performing deep analytics on data extracted from sensors embedded in visitors’ smartphones, the mall lets retailers develop a contextual portrait of customers in near-real time, enabling them to offer effective and timely promotions to help drive sales. The solution drives increased sales by matching a customer’s location to relevant shopping venues, enabling retailers to push near-real-time promotions to influence shopper behavior. It also helps optimize marketing efforts by providing near-real-time insights about which promotions are most attractive to shoppers.
Operational Impact
  • The solution drives increased sales by matching a customer’s location to relevant shopping venues, enabling retailers to push near-real-time promotions to influence shopper behavior.
  • It helps optimize marketing efforts by providing near-real-time insights about which promotions are most attractive to shoppers.
  • By tracking customer movement and heat-mapping areas of high congestion, the solution facilitates more effective footfall management throughout the mall.

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