Management consultant and author Geoffrey Moore is quoted as saying: “Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”
As organisations start to delve deeper in the use of data analytics, in part driven by suggestions that they become data-driven organisations, concerns are rising to the fore as to what extent are organisations allowed to use customer data.
The entry of artificial intelligence and machine learning into the business vocabulary may have also opened the doors to concerns around the ethical use of customer data, and the boundaries that mark what constitutes as open data and personal data.
One area of analytics that may draw the most concern is behavioural analytics – an area of data analytics that focuses on providing insight into the actions of people, usually regarding online purchasing.
Behavioural analytics is not necessarily new. It has been consistently used in e-commerce, gaming, social media, and other applications to identify opportunities to optimize in order to realize specific business outcomes.
The challenge for most organisations, however, may lie in how each individual defines and applies behavioural analytics to his or her particular role. For instance, in the area of marketing, behavioural analytics is the analysis of how customers interact with brands across the channels that are used to engage each customer.
Consider each time you go to Amazon or Lazada to shop, or when you browse travel booking sites like Booking and TripAdvisor, these sites have algorithms that identify you, and based on your behaviour during the web visit, make inferences about your preferences and buying behaviour.
Behavioural analytics has also found its way in risk management practices, particularly fraud detection. Behavioural analytics techniques and technologies are being applied to differentiate actual fraudulent activities from suspicious ones.
You can’t steal behaviour
According to Sandeep Puri, regional director at Gurucul, you can steal someone’s identity but you can’t steal their behaviour.
“Machine learning algorithms monitor user and entity behaviour in real-time they detect and stop anomalous behaviour before a breach happens,” he commented.
Misconception
There is growing concern about the use and abuse of consumer data, fanned in part by films such as Ex Machina, A.I. Artificial Intelligence, and Her. (Click here for a more complete cyber hacking movie listing)
To be clear the application of data analytics is still relatively young for many businesses in Asia (and elsewhere in the world). Part of the challenge lies in the complexity of the task at hand, its use, the evolving technology landscape, and the lack of skilled, experienced professionals to help organisations wade through the myriad operational, technical and ethical issues that embroil the technology.
“The size, complexity, distributed nature of data, speed of action and the continuous intelligence required by digital business means that rigid and centralized architectures and tools break down,” said Donald Feinberg, vice president and distinguished analyst at Gartner.
With the growing media coverage around data breaches and ethical debates around the use of data, it is natural that consumers will equate the use of behavioural analytics with invasion of privacy – a misconception that Gurucul’s Puri is quick to dismiss.
“It’s all about number and analytics. We use machine learning to detect anomalous behaviour [in an effort to detect fraud],” Puri explained.
Correct steps in the use of behavioural analytics
Click on the link below for helpful tips on the use of behavioural analytics.
Indeed, as organisations move to become even more data-centric, it is important that organisations not only be familiar with the data they have in store, who has access to it, and what is the purpose for which access to the data is granted.
“The story of data and analytics keeps evolving, from supporting internal decision making to continuous intelligence, information products and appointing chief data officers. It’s critical to gain a deeper understanding of the technology trends fuelling that evolving story and prioritize them based on business value,” said Rita Sallam, research vice president at Gartner at the Gartner Data & Analytics Summit in Sydney held in February 2019.
