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A mall knows how many people came in. Does it know where they went next?
The data a shopping centre already has tends to answer what happened. The question that pays is why.
Published
Ask a centre manager why the shops on the west side of level three are underperforming and you will get three answers from three departments. Marketing says level three footfall is low. Leasing says the tenant's range is wrong for the catchment. The tenant says nobody can find the wayfinding signs.
All three have data. None of it answers the question.
What is already collected, and what is missing
Most centres count people at the entrances. They have monthly sales figures from tenants, submitted to calculate turnover rent. They have car park data, and they have electricity consumption by zone.
What is missing is the join between them. The number of people through the north entrance on a Saturday afternoon says nothing about how many reached level three, and nothing about how many of those walked past a particular shopfront without going in.
The question that pays is not how many people came. It is which people walked past and did not enter — and whether they would enter if that shop sat beside a different neighbour.
What can genuinely be analysed
Movement. People counters at points along the walkways compose into a picture of how flow moves through the building. This does not need to identify anybody to be useful. Knowing that the route from basement two to the food hall carries three times the traffic of any other is already enough to change a layout decision.
Affinity between tenants. Two shops whose sales rise and fall together over the same periods are usually telling you something about a shared customer. A layout built around which tenants reinforce each other beats one built on product category alone.
Traffic forecasting. Long weekends, festivals, weather and local events all move the numbers. A good enough model lets operations plan staffing, cleaning rounds and energy ahead of the day rather than during it.
Settle this before you mount a camera
Analytics in a commercial space walks up to the privacy line quickly. Counting people past a point and recognising a face to know it is the same person who came last week are entirely different things, technically and legally.
Under Thailand's Personal Data Protection Act, biometric data is sensitive data requiring explicit consent. In practice, almost all of the value available to a shopping centre comes from anonymous counting, without touching sensitive data at all.
Choosing not to collect what you do not need is not only a legal position. It is a reduction in what you have to protect.
Tenants are the forgotten users
Retail property data systems are usually designed for centre management, even though the tenant is the one deciding whether to renew.
A tenant who can see footfall past their own frontage, which hours carry the most of it, and how their own performance compares with the zone average, is a tenant who understands what they are paying for. That is a very different renewal conversation.
What GIPSIC does here
We build tenant management platforms and space booking systems for commercial property operators. On one, lease paperwork fell by 91 per cent, from 96 hours a month to 8, and over 20 per cent of tenants opened a new branch on insight the platform surfaced.
What we usually propose first is joining up the data already scattered across separate systems. A handsome dashboard reading from a file somebody updates once a month changes nobody's decisions.
If you would like to talk about your property, get in touch.
About the author
Film — Wisit. A businessman who still does his own BA work more often than he probably should, and writes a fair bit of code, front and back. Runs two or three small businesses. Follows technology and business obsessively, in Thailand and everywhere else. Off the clock: physics, astronomy, DIY, and anything to do with networks. Music always on, though he cannot sing. Plays instruments anyway, badly. Plays a lot of sport, racket sports above all. Not much of a traveller by himself, but happy to take Mint anywhere in the world. A man who fears — sorry, loves — his wife. One flaw: he barely touches video games.
Written with Claude Opus 5