From Door Counters to Mass Mobility and Spending Data: The Future of Retail Insights in Shopping Centres

As shopping centres evolve to meet the demands of a competitive retail landscape, data-driven insights have become a vital tool for managing tenant success and optimising leasing strategies. Traditional door counters have long provided a primary measure of foot traffic. Still, their limitations are increasingly apparent, particularly as they must distinguish between entry and exit counts, often leading to inaccurate traffic data. The latest advancements in mass mobility data, combined with anonymised credit data, have provided a much greater depth of understanding of footfall and consumer behaviour in shopping centres.

Moving Beyond Door Counters

Door counters have been a standard tool for tracking the number of visitors in a shopping centre. However, they come with notable limitations:

• Inability to Distinguish Entry and Exit Counts: Door counters cannot differentiate between people entering and leaving, often leading to an inflated view of foot traffic numbers.
  
  
• Lack of Journey Details: Door counters capture only the entry point, missing out on where visitors go, how long they stay, and which areas they frequent.
  
  
• No Insight into Visitor Demographics: Traditional counters don’t provide data on age, origin, or purchasing behaviours, leaving property managers with an incomplete picture of their customer base.
  
  
• Limited Impact on Decision-Making: With only basic traffic counts, door counters offer limited value in shaping tenant performance strategies or understanding visitor shopping habits.

As shopping centres face more complex challenges, managers and landlords need richer, multidimensional data to respond to market changes, optimise store layouts, and enhance tenant satisfaction. This is where mass mobility and anonymised spending data come into play.

Mass Mobility Data: A Comprehensive Look at Movement

Mass mobility data, gathered through anonymised mobile device tracking, Wi-Fi, and Bluetooth signals, provides a full picture of visitor movement patterns within and around shopping centres. Unlike door counters, mobility data reveals where visitors go, how long they stay, and how often they return. Here’s how it supports smarter retail decisions:

1. Mapping Visitor Journeys: Landlords can see where people spend time, which stores they visit, and the most popular areas in the centre. This insight allows managers to identify optimal store placements, guide customer flow, and create high-traffic zones that attract new tenants.
   
   
2. Dynamic and Real-Time Insights: Mass mobility data can be updated in real-time, helping managers track visitor behaviour dynamically during peak seasons or special events. Real-time insights allow immediate adjustments, such as enhanced staffing or targeted promotions.
   
   
3. Enhanced Leasing and Performance Metrics: By providing visibility into traffic flow and time spent in specific areas, mobility data helps landlords understand tenant performance beyond simple sales metrics, setting new benchmarks for lease negotiations.
   

Combining Mobility with Anonymised Spending Data: Deeper, Actionable Insights

Integrating mass mobility data with anonymised credit card data, such as CommBank iQ, elevates the insight available to shopping centre managers. CommBank iQ combines anonymised, aggregated data from Commonwealth Bank’s transaction data with analytics capabilities, providing a detailed view of spending patterns across different customer segments. This integration offers several key advantages:

1. Understanding Spending Patterns and Customer Demographics
   
   By analysing movement and transaction data, landlords can track how demographics engage with retailers, identifying high-value shoppers, repeat customers, and spending habits across categories. This supports optimal tenant selection and aligns the retail mix with customer demand.
   
   For example, if data shows high spending in health and beauty, the centre might prioritise leases for complementary retailers, meeting demand and enhancing the customer experience.
   
   
2. Evaluating Marketing Effectiveness
   
   Integrated data enables shopping centres to assess the impact of marketing efforts on foot traffic and sales. For example, they can track how a holiday promotion affects in-centre visits and spending patterns, refining future campaigns for stronger results.
   
   By understanding which events or promotions drive spending in certain stores or areas, managers can support targeted marketing that maximises return on investment.
   
   
3. Supporting Lease Negotiations with Accurate Sales Attribution
   
   Anonymised spending data helps landlords provide clear sales metrics for individual tenants, showing how foot traffic translates into actual sales. This insight aids in setting fair rental terms based on performance, creating win-win outcomes for tenants and landlords.
   
   With accurate sales attribution, landlords can benchmark tenant performance and adjust leases based on each tenant’s true economic impact within the centre.

Strategic Applications of Mobility and Spending Data

Shopping centres in Australia, such as Westfield Sydney and Chadstone Shopping Centre, are beginning to adopt this integrated data approach, leveraging movement and spending insights to refine operations and enhance tenant relations. Key applications include:

• Optimised Tenant Mix: By identifying which stores attract high traffic and generate strong sales, property managers can make more informed leasing decisions, choosing tenants that enhance the centre’s appeal and profitability.
  
  
• Enhanced Customer Experience: Knowing peak times, visitor flow, and spending behaviours enables more strategic allocation of amenities, signage, and crowd management, contributing to a better shopping experience.
  
  
• Predictive Analytics for Future Planning: The combined data offers predictive insights, helping managers plan future tenant placements, layout changes, and marketing strategies based on anticipated visitor trends and purchasing patterns.
  

Regulatory and Privacy Considerations

While mass mobility and credit card data provide valuable insights, respecting privacy standards and ensuring data is anonymised and aggregated is essential. Platforms like CommBank iQ adhere to stringent data privacy regulations, offering aggregated insights without compromising individual privacy. This focus on compliance and data protection is key to fostering trust and ensuring ethical data use.

Conclusion

The shift from door counters to integrated mass mobility and spending data marks a transformative step for shopping centres. It empowers managers to make data-driven decisions supporting tenant performance, optimising leasing, and enhancing customer experience. With tools like CommBank iQ providing in-depth insights into movement and spending, shopping centres can now understand their customers on a deeper level, supporting strategic decisions that align with the dynamic needs of today’s retail environment.