Tool to predict shopper behaviour in malls using AI tech wins Wits award

DataConvergance, an artificial intelligence solution for managing and monitoring foot count, social distancing and consumer behaviour in shopping malls, has won the coveted Wits Enterprise award.

Inventor Dominique Adams was awarded R100,000 worth of support from Wits Enterprise towards developing the business.

Adams and others were part of the Prospector@WITS course run by Wits Enterprise. The course works to develop entrepreneurial ideas and culminates with a pitch to the class with the winning pitch receiving the prize.

Development of the Wi-Fi-based solution began in 2020 during the Covid-19 pandemic which created the need for social distancing. 

Adams explained the concept: “Our innovation stemmed from an existing product for Wi-Fi signals to monitor social distancing in public spaces. We engaged with stakeholders in the retail space to determine whether there was a need for a solution that, with the application of AI technology, would give them valuable insights into consumer behaviour and help them make predictions.

“Combining Wi-Fi technology with AI, our tool allows mall managers to monitor the complex behaviour of people in real time as well as predict their future behaviour. This gives stores data-based intelligence while providing mall management teams with an additional tool for enhancing security.

“Our tool also allows shopping malls to monetise from the deployment of Wi-Fi, and importantly obtain intelligent foot count and other data for strategic planning and evidence-based decision-making.”

With the technology mall managers can measure the overall popularity of stores and see the length of time a shopper spends at a particular store.

Adams said the data gathered from these measurements is valuable for establishing shopper behaviour and for informed decision-making and planning.

The DataConvergance team is working under the leadership of Prof Bruce Mellado from Wits University’s School of Physics.

The team, consisting of data scientists and AI specialists Xifeng Ruan, Kentaro Hyashi, Finn Stevenson and Benjamin Lieberman, had to figure out how to harness the large amount of data available from Wi-Fi systems.

Adams said the biggest challenge the team faced was the reluctance of mall managers to assist with the market and needs analysis.

“It has been a huge team effort. Being awarded the seed funding is a huge achievement for me as well as our team, a great reward for all of the long hours spent. The knowledge gained through the Prospector@Wits Course and the valuable guidance from my mentor, Dineo Masokoane, were critical contributions to the successful outcome of the project proposal.”

Mellado said the technology was one of a few first pushes by AI into the retail sector.

“Given the small number of businesses contemplating or already adopting AI, there is a huge opportunity for this solution to be successful in the retail environment. If the solution is successfully implemented, DataConvergence could be a trailblazer in the deployment of AI in the retail sector.”

Director of innovation support at Wits Enterprise Ela Romanowska said this was another example of Wits University’s response to providing solutions to societal needs, and was a worthy winner of the Prospectro@Wits end of course pitch session.

Dineo Masokoane, innovation support manager at Wits Enterprise, said DataConvergence will enhance data collection by exploiting and deriving greater benefits from the Wi-Fi availability in malls.

“This approach enlarges the scope of information available to management and planners to monetise their investment in Wi-Fi as well as optimise in-store strategy development.”

Now Adams and his team are refining the prototype for the retail environment.

They will then develop a pilot in a real retail environment before full and large scale deployment in shopping malls.

TimesLIVE