Stockland uses complex analytics to change retail mix in its shopping centres

Stockland is using data analytics to change the mix of retail and services in its shopping centres in response to broader customer behavioural changes brought about by the pandemic.

National customer analytics manager Jenny van Zyp told the Melbourne Business School’s business analytics conference that the company is combining its own first-party data - that is, data it collects - with external sources, with a purposeful aim to create a “competitive advantage for Stockland, [and] something that’s not easy to copy.”

“Our ability to compete in this new world really depends on our ability to adapt and respond to customer needs,” van Zyp said.

“To be able to do that you need to have a deep understanding of your customers - who are they, what do they value, how do they behave - so we can predict what they’re going to do and respond in a meaningful and profitable way.

“For us at Stockland it’s really been about building out our data portfolio beyond our first party data, and I think that’s really important.”

Last month, Stockland unveiled one piece of this strategy with a $2.5 million investment in smrtr, a data aggregator that holds consumer behavioural information on about 16 million Australians and provider of as-a-service data science tools.

Van Zyp said that Covid had led to consumer behavioural shifts, and there was a need to quickly understand to what extent these shifts are “temporary or transient, versus structural”, and to use this understanding to shape commercial decisions and business responses.

While Stockland’s shopping centres “fared reasonably well” despite the pandemic, van Zyp noted there was a “higher than normal vacancy rate” in the centres during 2020.

“We’ve identified that this is … actually an opportunity that we need to seize by understanding how customers have changed their shopping patterns,” she said.

“Things that people used to do in the CBD when they went to work every day they are now doing closer to home, like services for example. 

“Localisation is a huge term that we’re seeing, and we’re using the data to work out how we can take advantage of this trend.

“We’re facing a lot of decisions around what retailers we should be bringing in. Optimising centre mix and store location are great business problems to solve with customer analytics.”

Van Zyp said that Stockland’s ability to do this would be much more limited if it relied only on data it could source directly from customers.

“If we only were working with first-party data, our view of the world would be really limited,” she said.

“We need to understand who people are, build segmentation and predictive models on that, and use external datasets to give us the other pieces of the puzzle on what’s going on in the marketplace.”

Van Zyp also said that it took “a lot of creativity to use your own datasets as well as a wide variety of other datasets.”

“ I think many companies look to off-the-shelf solutions and those are precisely the expensive insights that everybody has access to so nobody has a competitive advantage,” she said.

“We’ve actually done a lot of work to get to the point where we have something that I think really differentiates our ability to understand our customers. 

“It’s not just some demographic segmentation and spend numbers. It’s actually a segmentation that we’ve built based on behaviour and that we leverage our own first party dataset to enrich and enhance, because that’s how you make it truly predictive.”