Rejuvenating Retail

Big Data Analytics as the key ingredient in driving global retail location strategies

17 Nov 2020

Rejuvenating Retail

The 2020 pandemic has accelerated what CTOs and CDOs have been trying to push across their organizations for decades: competent digital and sales strategies that draw deep insights from big data analytics. Across developed nations and emerging economies, we are witnessing an unprecedented adoption and reliance on smart tech and data intelligence to offer a more accurate lens on complex consumer buying patterns in the new “phygital” normal.

Globally, the retail sector clocks revenues in excess of 24 trillion dollars.[1] As economies go through Covid-19 waves of infection and physical retail stores are forced to shut or make disruptive adjustments to their business models, we have identified a few critical areas to consider and take action on:

  • Rethink your store portfolios and networks
  • Revamp your omnichannel strategy
  • Radically realign your technology stack

Retailers are Finding Comfort in Big Data to Navigate Uncertainty

Big data – the insight into customer profiles, socio-demographic categorizations and spending patterns – is the engine that drives business intelligence. While common belief is that individual user information is collected, the reality is that anonymous data makes for more objective analysis and findings. Data that is harvested at a large enough scale reflects broad patterns that are needed for strategic and long-range decision making.  

Today, with the rapidly evolving business landscape, the challenges of understanding customers and keeping them engaged are of utmost importance for retailers across the globe. Retailers, irrespective of industry (fast fashion, luxury, grocery, food & beverage or home & electronics) and size (larger conglomerates, regional players or smaller mom-and-pop shops) are looking to leverage consumer data even more to guide their strategic location decisions.

A common practice for landlords and retailers has been to leverage data collected internally within a location – through WiFi services provided via registration, loyalty programs, or installation of movement trackers to better understand customer journeys and to customize personalized experiences. Additionally, there are third-party services or tools that collect a broader set of data to benchmark performance against competitors, which is more meaningful as it allows retailers to track consumer journeys beyond on-site locations.

Leveraging Big Data Unlocks Benefits Across Store Networks

Amidst the pandemic, retailers are revisiting locational strategies to future-proof their portfolios and digital network. Our data science specialists have been leveraging deep local market insights with big data on customer profiling, behavior and movements to power innovative solutions in three core areas:

  1. Reevaluating the customer base
  2. Redesigning omnichannel delivery networks
  3. Revamping retail portfolios to optimize coverage


[1] Statista Forecast 2020

Reevaluating The Customer Base

Retailers are now more than ever unaware of who their customers truly are and how their store locations will perform in the post Covid-19 world. To this effect, CBRE is helping retailers understand footfall levels across different store locations using mass mobile data and other socio-demographic insights. Given the historical nature of mass mobile data, retailers can compare footfall levels pre- and post-Covid. This insight is critical as it helps identify the key locations where footfall has remained resilient.

Additionally, heatmaps give a visual cue of the impact of Covid-19 on store locations. Footfall is segmented by month, day and hour to give retailers a sharp lens on how location performance evolves over time. In the sample output video on Queens Road Central in Hong Kong, we can visualize footfall heatmaps generated from January to September 2020. This indicates a strong correlation between lockdowns and visitor footfalls:  the months where measures were imposed to restrict gatherings and interactions, such as in April and August, saw significant drops in footfall.

Redesigning Omnichannel Delivery Networks

When restrictions on movements were put in place, consumers started travelling less and this severely impacted the catchment coverage of retailers. By understanding visitor catchments pre- and post- Covid, retailers can optimize their omnichannel delivery networks by tagging stores to specific catchments.

In addition to understanding mass mobile data, commute times by foot and automobile are key weightage factors for optimizing delivery networks. In the following video, we assessed the delivery network impact at Russell Street in Hong Kong where the catchment coverage changed dynamically in 2020. Similarly, the primary, secondary and tertiary catchments evolved significantly between January and September 2020.

Revamping Retail Portfolios To Optimize Coverage

While internal sales data, business intelligence and other streams of information are critical in driving decisions on retail portfolio optimization, there are other external factors that should be investigated. This is the reason why we have produced a 40-metric dashboard, backed by hard data, to help retailers across the region understand what separates the leaders (stores that perform the best in their networks) from the laggards (those which barely break even).

The Road Ahead For Retailers

If you find yourself asking the following questions, please reach out to Arpan Barua and Udit Sabharwal for a focused data-backed insightful review of your business:

  1. What is the ideal number of stores needed to maximize coverage in the city?
  2. Where are the potential whitespace locations for expansion?
  3. Which stores should be relocated or closed?
  4. What are the potential savings that can be generated from relocation or through store network optimization?

Our retail advisory and transaction services team in Asia, Vivek Kaul and Rebecca Pearson, will crunch the findings from our data analytics team to offer you feasible and fast-track solutions on:

  • Market entry and store roll out strategy
  • Site selection and negotiations
  • Partnership identification and selection
  • Renewals and disposals
  • Portfolio review and network optimization
  • Account and transaction management 

While the near future may not have flying cars, hoverboards and the colonization of Mars, a smarter approach to retail location strategy using data is the true need of the hour.

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