The holy grail of every mall owner is to understand what shoppers want. The continuous search for this intelligence has led to the birth of Fatti, a company that has provided behavioural analytics to numerous landlords over the past five years. For the first time ever, landlords, property managers, mall-marketing and strategic teams are geared with a vast amount of valuable data about their consumers, enabling data-driven decision-making. At the end of the day the retail industry should work towards one common goal – creating higher shopability in the South African market, motivating shoppers to visit more malls, enter more stores and spend more time inside these malls.  CEO Adrian Maguire and Head of Analytics Michelle Jooste demystify the magic.

Give us a quick summary of what Fatti offers its clients.
The simplest way to explain the Fatti value proposition is to imagine taking the roof off your mall and seeing a globular view of how shoppers move. The activity and interaction of shoppers inside a mall represents the health and heartbeat of the asset. Being able to monitor this heartbeat (activity, movement and motivation) has become invaluable for any shopping centre and mall owner. It is similar to online retailers that gather data on their customers and monitor their interests.

Originally malls had limited data (foot count and turnover) to base decisions on. However, to stay competitive, everything that happens in between these two counts have become vitally important. Data received from foot counters only identifies the number of feet through an entrance or area, and spend data is only available when it’s already too late. There is also no indication of those who did not spend. Fatti detects and analyses the full path and behaviour of the shopper, giving asset managers valuable insights on which more informed decisions can be made and to also create effective strategies.

Management teams used to create strategies around what they believe would interest and attract specific profiles. Now, with the increased pressure from new developments and online retail, bricks-and-mortar assets are forced to have a much better understanding of their consumer.

Atterbury was Fatti’s first customer in the retail environment; and you now have many more landlords using this data. Is this type of data only useful in malls?
We live in a new era where it is required of us to act faster and make more effective decisions. Having facts at our fingertips enable us to proactively monitor change and measure/test new ideas. The Fatti solution gained traction in several platforms, from ocean liners, universities and diesel depots, to retail warehouses and even public areas such as national parks.

How many Atterbury assets utilise the behavioural analytics – and is it only in SA, or elsewhere too?
Fatti has deployed infrastructure and software in 10 Atterbury malls in South Africa, Namibia, Mauritius and Cyprus.

I heard you say in an interview that you gather between 5 and 7 million lines of data in a shopping centre per day. What valuable insights do you look for in that massive volume of data?

Fatti specialises in turning big data into consumable reports with valuable insights. We have also recognised the need to feed asset managers data instead of relying on them to interpret it themselves. We have assisted multiple landlords and property managers in gaining insight before making any important decisions.

A few strategic questions include:

  • How shopability (motivation to shop) changes per entrance;
  • How destination shopping influences activity at malls;
  • The value of mixed-use developments surrounding your retail asset;
  • The impact and ripple effect of mall-wide marketing events;
  • The shopability of an entertainment-driven shopper;
  • Identifying & monitoring quiet and busy areas inside a mall on a real-time live platform;
  • The value of monitoring individual tenant performance;
  • How can analytics assist in leasing and lease-renewal strategies;
  • Should trading hours increase during festive holidays

Can you give us a recent practical example of info extrapolated from the data at a specific mall and how it was applied?
One of our malls explored the idea of increasing trading hours during the festive season.  Although the foot-count data increased during certain times, Fatti was able to identify the percentage of staff members responsible for the increase in the foot count. Fatti runs an algorithm at each mall which identifies staff members that spend a certain amount of time inside the mall. The decision was based on historical fact and the management team was able to make a more informed decision.

At another mall we noticed on the live dashboard that the dwell in a new food court was extremely low. We informed the landlord of our observations which enabled them to address the issue proactively. This food court area is now the busiest area inside the mall.

We have also assisted individual struggling tenants by means of identifying the profile of their customer by analysing shared store visits, interaction with other tenants, peak times in the specific store and so on. This info assisted them to make effective changes to their offerings.

Black Friday is the busiest shopping day of the year in many malls.  How does Fatti assist landlords to prepare for such a day?
Fatti monitors the activity of visitors in real-time which is invaluable on a day like Black Friday. Live monitoring assists with crowd management and understanding of quiet and busy areas. The analytics, on the other hand, allows us to put fact to general statements,  such as the difference between loyal and new visitors that visited on Black Friday, the peak times during the day, the number of stores entered, and the time spent across the mall and inside each tenant area.

The historical data gathered on previous Black Friday campaigns, successfully prepare Landlords and Asset Managers for future Black Friday and other similar campaigns.

What is next for Fatti, looking ahead to 2020?
Fatti aims to encourage management teams to base strategies on behavioural fact and to work alongside individual retailers to understand what customers really want. We also aim to feed our clients the right amount of information so that they are able to consume and process the most valuable insights.

At the end of the day we all aim to simplify and maximise the shopper journey in bricks-and-mortar environments. As a result, we hope to set the standard for shopper behaviour analytics by empowering property owners in making more informed, data-driven decisions.