Our lives will change after COVID-19, and AI can help the retail industry and provide opportunities to minimise the impact of the pandemic while respecting privacy and the ethical principles.
In the last two months, we have witnessed how the entire world has changed- from schools to factories, we all have replaced our usual practices and activities by pandemic-proof ones. We are now well aware of how we have to wash our hands, we have been instructed on how to secure our home network for homeworking and homeschooling and we are cautious when it comes to the use of our geolocation data by the Governments. One of the main industries that has been affected is retail, and AI can help to maximise the opportunities while respecting privacy and ethics.
What about the “new normal”? How our everyday life will look after COVID-19? We cannot predict it certainly, but we are quite sure that the AI will have a key role in defining it. In this article, we go through some uses of AI in retail which may become very relevant in the post-pandemic world, also considering how they should be applied ethically.
What changes will the retail industry face?
The COVID-19 pandemic is the first of its kind in the last hundred years. The effects of the disease will presumably result in changes in our habits: the way people buy, socialise, learn, work and set up their preferences will not be the same as before the COVID-19 outbreak.
How will this impact retail? Let’s think about what could be a common Friday in the UK or Spain. You get up, take the bus or the train to the office, then you have lunch with your workmates and go shopping in the afternoon looking for your brother’s birthday present. After that, you meet him and all your friends in a restaurant for the celebration party. It does sound normal, right? Well, maybe it does not any longer.
While, unfortunately, many people will lose their jobs because of the COVID-19 pandemic, some other will avoid spending much money due to the uncertainty. Economical dilemmas will not be the only pitfall in the retail industry though, as the risk of infection will also limit our movements widely. Getting back to our example above, maybe your brother would have decided to invite his friends home rather than to a restaurant, minimizing the contact with other people. And you may have bought the gift via online while working from home, instead of going to the shop as such.
It seems that our free time activities will move to an in-house fashion, which will also affect the type of products we buy. For example, premium food or beverages to consume at home may become more relevant, together with highest level appliances that make our lives easier in our “new normal”.
What changes may come from the reinvention of the industry and how can AI help?
There are two main categories of changes, that we have sorted into “physical” and “digital”. A third one may be the combination of both.
Retailers will need to make their clients feel pandemic-safe when shopping in their stores, which require the implementation of a wide range of measures, such as:
- Line management. AI may help to count the number of people which is inside the store, plus control their movements and manage the waiting times in the lines. An app may be designed for this purpose, based on spots booking and SMS notifications.
- Social distancing. Heatmaps may be useful when it comes to capacity control and minimum distance among the customers. AI could be helpful to identify those higher traffic areas and use the data to redesign the space.
- Temperature and symptoms control. Facial and emotion recognition plus temperature sensors may automate the identification of infected customers with the purpose of preventing their contact with other people.
- Logistics and delivery. Drones built with AI systems can autonomously deliver orders to the customers based on a “zero contact” policy.
- Self-payment. AI can definitely be key in the replacement of the traditional cashier staff by self-payment machines, or even payment with no checkout at all, using virtual cards via sensors and deep learning.
- Product disinfection. One of the main obstacles to in-store shopping is that COVID-19 may remain on surfaces for days, which includes products such as clothes. One of the solutions to this issue might be the use of virtual fitting rooms: combining AI and virtual reality (VR), customer can virtually try clothes on their own body with their personal 3D body avatar. This may apply both to ecommerce and in-store shopping.
Even though retailers will do big efforts to make their shops as much attractive as possible for their customers, online shopping will inevitably become more popular, which may be a detriment to physical stores. In this context, the industry will need to improve the ecommerce in order to properly respond to the market demand. To make the most of this “new normal”, retailers may focus on:
- Targeted advertising and offers. Considering there are few data about the new consumer habits, being able to tailor the offers individually becomes essential in order to survive in the “new normal”. Profiling is crucial to predict individual’s behaviour and maximise the chances to attract a customer to the business.
- Design and usability of their ecommerce pages. Practices like keeping navigation simple, automating the search or providing relevant recommendations make the costumer feel comfortable within the ecommerce page, therefore the purchase possibilities increase.
- Track and compare different markets. “Reinvent or die”. New times require adaptation, and where no enough historical data is available, using another techniques, such as comparing countries or matching data from other products or services, may be paramount for the purpose of drafting the new trend.
- Omnichannel marketing. Customer experience will be placed in the center of the business model, thus adjusting to the customer based on their behavior through the sales funnel is required to provide the ultimate personalized customer experience.
- Product placement. When it comes to advertising, there may be new spaces to consider, such as Netflix films or series, which may now be more profitable than the traditional outdoor means.
There is a very thin line between physical and digital in an interconnected world though. While some examples may be clear, other ones may be a combination of both. For example, smart billboards work with data gathered from our physical presence plus information from our devices our digital fingerprint.
In this context, relevant business opportunities may come from the proper analysis of the data with the aim of figuring out the new customer behavior. However, considering the temporary nature of this “new normal”, caused by a pandemic, flexibility should remain in the top of our minds because being able to adapt as fast as possible to any changes in the demand will make the difference, in one direction or another.
Can we achieve all these changes ethically?
It seems that AI will play a key role in the adaptation of the retail industry to the evolution of consumer habits. The purpose businesses pursue with the implementation of changes is maintaining the turnover they had before the crisis, or even improving the rate, which can only be achieved by instilling confidence in the clients.
All the measures described above relate to health risks management, but one should remember that, even though currently they may be the most important ones due to the COVID-19 outbreaks, there are also some other concerns that businesses should deal with, especially when the new measures may emphasise them. These are, among other, data protection, privacy and ethics concerns.
Customers will not be able to trust a business that uses AI which is not trustworthy. This is the reason why one should ensure that the AI systems are:
(1) lawful – respecting all applicable laws and regulations.
(2) ethical – respecting ethical principles and values.
(3) robust – both from a technical perspective while taking into account its social environment.
A Data Protection Impact Assessment should be run before implementing any changes using AI systems, considering both data protection and ethical dilemmas. It should help to verify the following requirements are met:
- Human agency and oversight. For example, a member of the staff should be able to intercede where a customer claims the price charged for a product in his virtual card is not correct.
- Technical Robustness and safety. For example, businesses should ensure that no physical violence is applied over a person by an AI system in order to block access to the shop where high temperature has been detected.
- Privacy and data governance. Full compliance with the GDPR and any other relevant laws should be guaranteed when using AI systems. For example, access to the data should be limited by user or role and pseudonymisation techniques should be applied where possible.
- Transparency. Traceability mechanisms should be provided and AI systems and their decisions should be explained. Customers need to be aware that they are interacting with an AI system, and must be informed of the system’s capabilities and limitations. For example, the controller should be able to explain the logic behind the access restriction to the store.
- Diversity, non-discrimination and fairness. Any type of unfair bias should be avoided, either in the training dataset, the creation of the algorithm or its application. For example, stores should make sure that no one is banned from entering for any reason other than temperature or symptoms. This could be the case where someone living in a low income neighborhood quite affected by COVID-19 is banned from accessing a mall just for coming from said area. This could address to the marginalization of vulnerable groups, or to the exacerbation of prejudice and discrimination.
- Societal and environmental well-being. AI systems in this context are not only used for improving businesses’ turnover, but also to prevent the spread of the virus for the sake of public health.
- Accountability. Business should have measures like civil insurance in place to ensure responsibility and accountability for AI systems and their outcomes.
Earlier this month the EU Parliament came up with research on AI new developments and innovations applied to ecommerce. We will go thoroughly through it and discuss their in-depth analysis in Part II.
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