Using A.I to Cope in the Era of Coronavirus
COVID-19 is having serious implications for businesses in Singapore across the globe, as they adapt to the ‘new normal’ of operating an organisation remotely. We state down six business functions at risk and the AI solutions that could help.
Growing Sales & Realigning Priorities
Now, even more evident than ever in our current unprecedented history, the world’s business interactions and engagements have shifted and evolved to occupy the online space. Especially so given the rampant effects of COVID-19, and where physical meetings and sales may not be the preferred mode of operation any longer. The boon for digital and internet marketers alike is that there never has been a greater marked importance in the role of online marketing and advertising.
But truth be told, this approach is not new – given the Industrial Revolution 4.0. Gone are the days when marketing decisions were guided by intuition and gut-feel. Important marketing decisions are now determined by big data. Now, what is Big Data?
Put simply, big data is larger, more complex data set, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address business and marketing problems humans wouldn’t have been able to tackle before.
These figures generate insights that can lead to better business decisions and strategic moves. The application of the right technology then improves the quality of decision making and detailing processes for users.
How Does This Apply to Marketing and Advertising?
Advertising platforms give us lots of data to work with, including measurable impressions, click-through rates, bid levels, demographics, and more.
Humans certainly have the ability to produce good advertising, measure that advertising, and improve ads based on what they learn. But, digital advertising across search, content, and social media channels, gives us an almost unlimited ability to generate data on what works and what doesn't.
That's what makes advertising at scale tricky – almost impossible – for humans. And this is what makes Artificial Intelligence (A.I) a natural fit for advertising.
“With the right data, AI-powered ad tools can detect patterns at scale in your advertising data, then predict what changes to campaigns will improve performance against a specific KPI. This can all happen in seconds, rather than the hours, days, or weeks it might take a human to analyse, test, and iterate across campaigns.”
Advertising costs a ton of money, especially if you're selling a product or service that doesn't produce an immediate return.
AI for advertising has the ability to increase your return on ad spend (revenue) and reduce the amount of money you spend on staff time and ineffective ad budget.
But, AI can actually go one step further.
Also AI-powered advertising system actually helped a brand discover and convert new customers they didn't even know existed.
Designing Effective Marketing Campaigns
In addition, Big data also enables companies to better target the core needs of customers by developing rich and informative content. Let’s understand how it helps companies collect data about customer behaviors. One example is through cookie files. They collect information about customers’ activities as they browse the internet, generating and capturing quite alot of personal data.
Campaigns that use big data are thus far more effective than aggregative advertising used in the past. The good thing about using big data for creating marketing campaigns is that it takes the guesswork out of determining what customers want. Marketers can develop different buyer personas using data like customer behaviour, purchasing patterns, favourites and background. For example, they may find that women are more likely to respond to email campaigns, use coupons and engage in bargains and deals, and shape their digital marketing campaign from there.
Demand and Supply
Companies are interested in matching demand and supply, and that’s going to be really critical coming out of this crisis,” says Davenport at Babson College. “The good news is there’s more and more external data available on demand.” A big steel company, for example, has information about the various factors that might influence demand for steel, such as the demand for automobiles. These demand measures depend on external data that’s used to match up to what their supply chains can produce. “So that you’re not producing more than you need to satisfy demand and you’re not leaving unfulfilled demand out there,” he says.
“The COVID-19 crisis has put unprecedented pressure on NHS staff as public health has taken centre stage. Medical services have been terribly shaken and our beloved NHS may be near a coup de grâce.”
AI solutions can analyse this external data. But, as Davenport points out, AI typically relies on data from the past, while the COVID-19 crisis is unprecedented. Therefore, companies have to ensure they use data that is representative. He says: “I suspect that in some industries, the past will be a better guide to present and future activity than it is in others.”
Document and Identity Verification
AI can work on identity and document verification, says Dr Terence Tse, associate professor of finance at ESCP Business School. Think of a bank, for instance, that needs to verify its customers for onboarding and compliance. This is often done by human checkers, who check payslips or driving licences. “It’s a very costly, inefficient process,” says Tse.
Instead, AI can be used to “quickly identify the type of ID document captured, determine if the security features of the ID are present, perform face-matching – comparing the picture in the ID to the person in the selfie – and even help determine whether the person is physically present”, says Robert Prigge, chief executive at Jumio.
“For the past few years, digital account opening has been at the top of the list of technologies organisations intend to add or replace, but COVID-19 is pushing this element of digital transformation to the front of the line,” says Prigge.
Back Office Tasks
A.I Powered cognitive assistants can perform a company’s back-office tasks. This includes ordering new credit cards, issuing refunds or cancelling orders, says Faisal Abbasi, UK managing director at Ipsoft. He notes: “When the cognitive assistant is unable to handle a task due to its complexity, this can be seamlessly handed over to human agents to manage. This ensures the time of those team members is spent solving the most challenging problems and focused on value-add activities.”
This process is often referred to as robotic process automation (RPA) and is increasingly combined with machine-learning. It spans all sorts of back-office service operations, as long as they are structured tasks, such as automating the claims processes of insurance companies or banks.
But he notes that if the current COVID-19 crisis leads to a severe recession, which seems likely, companies will use it to replace workers. “My guess is that it’s going to contribute to substantial job losses or at least slower growth of employment after the recession because companies will have automated a fair amount of work,” he says.
Medical Support
The COVID-19 crisis has put unprecedented pressure on NHS staff as public health has taken centre stage. “Medical services have been terribly shaken and our beloved NHS may be near a coup de grâce,” says Dr Alex Ribeiro-Castro, data scientist and senior teaching fellow at Imperial College Business School in London.
He says health tech may offer a temporary buffer to allow non-critical ailments to be treated, leaving clinics and hospitals free to focus on critical cases. An example is Doctorlink, which provides online doctor’s appointments and has algorithms that can provide medically endorsed diagnostics. Another is Babylon Health, which is building an AI-based health app that can help diagnose patients’ issues. It’s effectively a chatbot that can “translate layman’s language into medical terminology and deduce what may be causing the pain”, says Ribeiro-Castro.
Dinesh Venugopal, president at Mphasis Direct & Digital, says: “AI-based chatbots and robot-advisory services can very well be useful in relieving the administrative burden on extremely busy and under-resourced healthcare staff, automating processes such as screening patients for symptoms and recording necessary information.” By reducing the amount of face-to-face interaction between patients and hospital staff, this goes a long way to lessening the risk of spreading infection, he says.
Staff Demand, Supply & Infrastructure
Given that many employees may have to self-isolate during the COVID-19 outbreak, AI can analyse the number of staff needed. “AI companies get requests from their clients to identify if they are likely to even have enough workers to staff a railroad,” says Davenport at Babson College. In this case, AI can help to match demand and supply, but from a labour standpoint. “If companies are laying off people, they’d like to know it’s the right number of people. Making sure you have enough people to staff a particular train or a production shaft could be quite difficult.”
Transportation companies represent a significant component of a country’s infrastructure. “They are faced with an unfortunate Catch-22 situation: we, as a society, need to keep critical infrastructure and its employees healthy, however not all of them can manage critical infrastructure remotely,” says Ribeiro-Castro at Imperial College Business School.
What’s more, semi-automation is already implemented in certain forms of public transport. Ribeiro-Castro cites Navya, a company that designs and manufactures autonomous vehicles, such as shuttle buses at airports or theme parks. “AI is already being used more generally in the transportation sector to do things such as increase passenger safety, reduce traffic congestion and accidents, lessen carbon emissions, and also minimise overall financial expense.”
