How the most profitable shopping centre in the Nordics is analysing user behaviour?

Viru Keskus (AKA the Viru Centre) is by number of visitors the biggest shopping and entertainment centre in Tallinn, Estonia attracting about 16 million people yearly.

It is also the most profitable shopping centre in the Nordics.

According to Colliers International, the revenue per square meter of the Viru Centre substantially exceeds those of the five highest-performing centres in Helsinki and Riga.

The centre measures 70,000m2 and holds a capacity of 2000 people.

When the inner gut feeling is not enough. How pandemic affected footfall?

During the pandemic and as a result of the lockdowns, the Viru Centre experienced a reduction in footfall attracting fewer visitors than pre-pandemic levels. It wanted the intelligence to understand the extent of the problem, to assess the impact on shopping centre behaviours (visitor demographics, footfall, dwell time, traffic flow, adherence to social distancing measures) and to determine how to best to deal with the thinner visitor margins.

Due to falling revenues, retail tenants were seeking rent reductions claiming visitor numbers were down by 80% and the Centre wanted to obtain a fuller picture of the situation to support their own investigations and subsequent decision making.

Collect empirical data from your existing video feed and make data-based decisions

The Centre connected five of its existing security cameras to the Fyma platform. The cameras were located on the ground floor, covering the main entrances and the busiest areas. In terms of coverage, the cameras covered approximately a third of the total shopping centre footprint.

100% GDPR compliant

Fyma has worked with the Estonian Data Protection Inspectorate to ensure their solutions are GDPR compliant and doesn’t track any biometric data (e.g. face detection, gait identification etc).

Fyma’s core tenet is to deliver computer vision powered AI without infringing on people’s privacy or security. Its privacy-by-design approach prevents facial recognition, anonymising all data and protecting the sensitive information obtained from any given number of video sources. Read more about how Fyma protects your privacy.

Real-time foot counter and detailed visitor profiles

The data gathered enabled the Centre to disprove the reports from retailers claiming that visitor numbers were down by 80%. The data showed the Centre was still attracting high levels of traffic at 70% of normal levels and allowed for a more fruitful rent negotiation with tenants.

Through drilling deeper into key demographic data points such as age and gender, Fyma was also able to offer more detailed visitor profiles. And when combined with behavioural tracking (PoS receipts) was able to determine the proportion of visitors making purchases based on a number of variables – gender, age, day of the week.

The Centre was able to count and capture behavioural insights such as where customers went once they entered the building and whether they were adhering to social distancing rules.

Improved experience for visitors with mobility restrictions

An unexpected benefit of the solution was gaining insights into the movement of visitors with mobility restrictions. The data enabled the Centre to evaluate the configuration of the shopping centre layout (location of facilities, lifts, escalators) in relation to these customers and is helping them to identify how best to improve the utilisation of the space for all visitors and Centre workers irrespective of their mobility.

Future plans
Fyma’s AI will continue making the Viru Keskus system smarter as it learns from a wider data set. This will also enable the client to set up trigger events – customisable events to assist centre staff and prompt teams to act accordingly.

For example, the AI can be given a task to identify from the video feed a security concern such as unaccompanied packages or alert cleaning services once a certain number of visitors enter a bathroom or eating area. With continued use, the Fyma software will begin to add predictive behavioural patterns which can allow for pre-emptive actions to improve the overall customer experience.

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