Haven't you all secretly waited to push your favourite items from the cart to "Buy now" when the festive sales bring in great deals? But here's a thought - how much of that excitement was truly yours, and how much was subtly crafted by marketing strategies or even AI-driven algorithms?
Shiprocket, one of India's top eCommerce enablement platforms, recently shared insights on e-commerce growth during the festive season, highlighting the role of AI-driven recommendations and social media influencers. The report revealed that in fashion and beauty categories, 84% of consumers made purchases influenced by promotions or influencer suggestions.
In an exclusive conversation with AIM, Praful Poddar, chief product officer at Shiprocket, discussed how AI has evolved in shaping purchasing decisions. He noted that while in 2010, online shopping platforms used simple logic to show "similar products", this approach has advanced over the years.
Initially, product recommendations were generated through basic rules and Excel sheet-based logic, where items were mapped based on historical data. Today, machine learning algorithms consider multiple parameters, offering more personalised suggestions.
In recent years, machine learning has become mainstream, allowing platforms to analyse vast amounts of data in real time. Poddar explained that generative AI has further transformed the process by predicting user behaviour without the need for manually inputting parameters.
Aakash Anand, the co-founder of Unikon.ai, told AIM, "Our AI/ML-based peer-to-peer networking platform is leveraging recommendation algorithms to personalise users' journeys on the platform. We have also integrated semantic search, which basically understands the context of the query and responds accordingly."
When it comes to using AI in the platforms, Shiprocket focuses on two main areas: enhancing the buyer experience and helping small and medium businesses (SMBs) operate more efficiently.
For buyers, Shiprocket uses data from event streams, such as browsing behaviour, filters used, and items added to carts, to create buyer personas and improve personalisation. The platform's network effect also helps create larger buyer cohorts, enabling more targeted recommendations across its 2,000 websites.
On the buyer-facing side, the company uses AI to enhance the experience on its tracking page and MyShipRocket app, offering more personalised information than standard courier tracking services. This improves the overall user experience, making the process more tailored to individual preferences.
In the broader e-commerce industry, AI and ML are integrated into multiple areas, enhancing both operational efficiency and customer experience. Major players have leveraged AI to optimise cross-category searches, boost impulse purchases, and improve profitability.
Wayfair, a Boston-based e-commerce company that sells furniture and home goods online is currently undergoing a generative AI makeover. The company recently partnered with Google Cloud and has been working closely with them to optimise their operations on the platform.
"What's great about Google is the focus on AI, ML, and generative AI," said Fiona Tan, CTO at Wayfair, in an exclusive interview with AIM.
Similarly, Lowe's, a Fortune 50 home improvement retailer, has deployed 40-50 AI models across its platform to enhance customer experience and operations, and also built a SOTA omnichannel order management system internally.
Lowe's was one of the first to partner with OpenAI, that is even before ChatGPT was launched. Its data and AI team successfully fine-tuned the GPT-3.5 model to improve product data accuracy, reducing friction in online searches and boosting error detection rates by up to 60%, leading to a smoother and more efficient shopping experience.
Not to forget, Amazon pioneered the use of product recommendations on its platform nearly 20 years ago, setting the stage for AI-driven shopping experiences. When you browse Amazon, you've probably noticed suggestions like "recommended for you", "products you might like", or "customers also bought", all powered by Amazon's sophisticated recommendation engine.
It's one of the most effective AI strategies Amazon uses to drive sales.
Flipkart has tapped into AI in a different way, deploying advanced systems to combat fraud, especially when it comes to high-value returns, like smartphones.
Meanwhile, IKEA is using generative AI to enhance both customer experience and operational efficiency. It has an AI-powered personal design assistant for home furnishing, AI-generated seasonal advertising campaigns, and autonomous drones and robots optimising inventory and delivery systems. All this while focusing on the responsible use of AI and educating 3,000 staff members in ethical AI practices.
Target, on the other hand, has launched its generative AI chatbot, Store Companion, across 2,000 stores in the US to assist employees with process questions, coaching, and operations management. This marks the retailer as the first major player to offer generative AI tools to its service staff.
As part of a broader AI strategy, Target has developed 20 generative AI use cases, leveraging partnerships with Google, Microsoft, and OpenAI, while prioritising cybersecurity and moderation services to ensure safe and scalable AI deployment for both employees and customers.
Walmart has also been harnessing generative AI to enhance the shopping experience with features like voice ordering, text-to-shop, and AI-powered event planning. It also deploys tools like "Ask Sam" to assist employees with product locations and price checks.
The company's AI is also boosting e-commerce through cross-category searches, enhancing impulse purchases, and improving profitability. Walmart's AI tools help display accurate product images, aid supplier negotiations, and empower employees to suggest new AI use cases, setting industry standards in efficiency, customer service, and operational innovation.
Recently, Microsoft, expanding the capabilities of its Copilot platform introduced new autonomous agents that aim to enhance business processes across industries. The new autonomous agents in Dynamics 365 are built to help organisations drive business value by automating processes like lead generation, customer service, and supplier communication.
Further, as people seek out non-human solutions to problems, even giants like Salesforce are exploring AI agents. While companies like Oracle and Salesforce are adopting AI, its impact remains mostly limited to semi-autonomous tasks in specific areas.
In an exclusive conversation with AIM, Gautam Singh, business unit head of WNS Analytics, mentioned, "In consumer-facing industries like CPG and retail, AI is transforming the way people shop, with a shift towards ordering online instead of visiting stores. This trend extends to all B2C interactions between consumers and providers.
"While consumer-facing sectors may feel the impact sooner, AI is reshaping industries behind the scenes, offering opportunities for improvement and growth across the board."
Autonomous agents are just beginning to enter every industry. Experts predict that, in the future, customers will rely on AI agents' recommendations for purchase decisions just as much as they do on human suggestions.
