E-commerce giants are resorting to Artificial Intelligence (AI) to offset challenges in a variety of applications from adhering to social distancing measures, boosting sales and optimizing routes for fulfilment of delivery
As global economies wake up to new realities of the COVID-19 pandemic, e-commerce giants are resorting to Artificial Intelligence (AI) to offset challenges in a variety of applications from adhering to social distancing measures, boosting sales and optimizing routes for fulfilment of delivery.
Amidst concerns about the safety of workers in Amazon offices and warehouses, the company responded by using AI to determine safe distances and ensure adherence to prescribed standards. The Amazon AI system called Digital Assistant uses camera footages which highlight workers keeping safe distances in green and those not adhering in red. The system also identifies high-traffic areas to avoid route congestion for delivery.
Predictably Amazon’s bottomline has shored up during the first quarter of 2020—bumped up demand for essential items during the lockdown period—at USD 75.5 billion compared to USD 59. 7 billion in the first quarter, previous year.
BigBasket has been extensively using AI to manage operations efficiently and procure inventory of perishable goods such as fruits and vegetables. Based on predictive analytics, the company can accurately forecast demand and plan inventory to reduce storage period and eliminate waste which in turn help reduce expenditure significantly.
According to E-commerce Trends 2020, a report by Unicommerce, the overall e-commerce market in India has not just recovered but has witnessed an order volume growth of 17% as of June2020. This is in tandem with global trends where online purchases of clothing are up by 76.7% and online revenue up by 22.2% with online grocery seeing a 9% increase from May to June as people become comfortable buying online.
These trends are likely to continue post-COVID as many first-time buyers become comfortable using online and regularly shop essential items online. The Ecommerce Trends report indicate there is an increasing trend of consumers to buy directly from brands' websites and therefore retail brands are now strengthening the online capabilities and opting for different approaches to connect with consumers. Also 66% of total online consumer demand in India come from tier II and beyond cities and this share is expected to rise in coming years.
So what can e-commerce sellers do to optimize the shopping experience while boosting the bottomline?
For long, even though we have not paid attention, shopping experience on large online platforms, such as Amazon, Grofers, Big Basket, Myntra have been influenced by recommendation engines which are based on intelligent algorithms. According to a McKinsey report 35% of what consumers purchase on Amazon and 75% of what they watch on Netflix come from product recommendations based on such algorithms. While we may not be aware as Amazon never specifically talks about its recommendation engines but they clearly play a critical role in Amazon’s digital strategy and the product recommendations that appear on the browser’s page is the outcome of an intelligent collaborative-filtering process which takes into account a complex interplay of individual preferences, preferences of similar people, within groups in departments, industry, etc.
Another common and increasingly leveraged AI tool is chatbots which are highly effective to scale the ‘personalized shopping assistant’ experience. Based on questions of prospects, the underlying intelligent system immediately recognizes keywords, identifies the message and responds appropriately to the prospect. While personalizing the experience, chatbots also help save a lot on manpower to address first line of query.
E-commerce presents an exciting opportunity for entrepreneurs in that it leaves the digital footprint of buyers throughout the time spent on the website. This is in contrast with physical retailing where understanding the customer needs becomes a challenge and requires much effort. The key then is to capture customer information, mine it effectively, and map it with internal operations to impact business outcomes.
Going forward, deploying intelligent systems for online activities will no longer be an option but become a mainstream feature without which business competitiveness will be seriously undermined. In the Google report on Machine Learning, Fausto Ibarra, Director of Global Product Management for Google Cloud Platform, says “What is keeping business leaders awake at night is how to harvest and make sense of their data for competitive advantage. Machine learning is allowing companies to surface the untapped value in their data.”