Glimpse of the future: UAE scientists develop tool that predicts customer behaviour

It’s something that people in all walks of life would love to have – a way of telling us when a machine might break down, when a traffic jam might occur, or which new customer might prove to be the most profitable.

If it sounds like something that would only be possible with the uncanny ability to predict the future, think again.

Scientists at UAEU have designed and patented an invention that uses science to find out what may lie ahead.

Developed by Dr Jose Berenqueres, Assistant Professor at UAEU’s IT College, the tool – currently called System for Forecasting Future Events – uses data-mining algorithms to make forecasts based on historical information.

While its patent is targeted at the aviation industry and the growing focus of airlines on predicting customer behavior, the potential for it to be used for other purposes - including healthcare - is already clear.

The invention, as Dr Jose explains, capitalizes on the fact that data is now everywhere, and that it needs to be interpreted and put to good use in order to be of true value to businesses and to society in general.

"Reducing waste, increasing asset utilization rates, and increasing delivered value to customers are key activities of any organization with global aspirations,” he said.

“Now that collection of data from customers is economical and widespread, companies that keep doing nothing with that data will, basically, slowly die, because the companies that do something with it will be one per cent or two per cent more efficient.

“Amazon.com is a prime example, with its model predicting which customers will become ‘gold’ in a few months and which will not. With this information at hand, companies can better allocate their marketing resources and customer-relationship resources to the areas where they are more effective, and run on a lower budget while achieving the same results.”

With his team, Dr Jose built a tool related to airlines’ customer management and air-miles programs, containing two methods of processing data that allow a computer to make accurate predictions.

The first – dummy-variable generation – converts ‘categorical’ data, such as gender, into numbers that a computer can quickly understand.

The second employs a technique known as ‘blending’, reflecting the belief that the ‘average’ opinion will be closer to the truth if a larger number of opinions are analyzed.

As well as these methods, the team has also used ‘time-shifting’, where an airline passenger’s data stream – akin to an air-travel fingerprint, detailing the flights they have taken, their purchase history, website interactions and other information – is reset to the first time they used the airline, allowing behavioral trends and developments to be identified.

“The combination of these three techniques yielded such good results that, when we showed them to airline executives, they were stunned and even we were surprised,” said Dr. Jose.

"In this project, we spend about three months analyzing the business logic, and one month developing the mathematical model. But what usually takes more time is finding companies that have interesting problems to solve and the courage to share their data with research centers.”

There are ongoing discussions between the university and some well-known airlines in order to commercialize this technology and Dr. Jose says the interest it has attracted illustrates increasing attention surrounding data science.

“It is a high-growth job area, with companies paying top dollar for talent,” he said.

“The number of patents related to data science has exploded in the last five years, and developing skills in this area is a path to a great job for any new graduate.

“Since this project began, we have started helping other companies which have the same problem: a lot of data, but not the knowledge of how to analyze it. We have also published a paper in collaboration with Healint LLC in Singapore, the maker of a migraine-coping app called MigraineBuddy, and developed a model that predicts when someone will have their next migraine, exploring how environmental variables such as pollution affect migraine rates.”

"In business, sophistication means complex, and complexity is the enemy of profit,” said Dr. Jose.

“What is good about the method we are using for the airline industry is that it is computationally very simple while, at the same time, being 10 times more powerful than previous ways of estimating which customers will become high-value customers to the airline.

“Having this information in advance helps to focus marketing, air-miles and customer-relationship management resources to the areas where they are most effective, without losing the overall effectiveness of these resources.”

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