Looking back at 2023, it has been a huge year for Artificial Intelligence (AI) with the launch of generative pre-trained transformers such as ChatGPT developed by OpenAI, Jasper AI, Adobe Firefly, and many other similar inventions. These tools were welcomed with excitement as well as uncertainty, as any new technology brings a bit of unknown.
From what we know so far, AI has changed the way we work across several industries, including e-commerce and provided new and exciting opportunities to make our lives easier and our jobs more efficient. In 2023, around 35% of all companies across all industries are using AI in their business. The highest adoption of AI includes: financial services, healthcare, retail and manufacturing. AI is a technology that will grow in strength in the years to come. According to Gartner's, Gartner Top 10 Strategic Technology Trends for 2024: "By 2026, generative AI will significantly alter 70% of the design and development effort for new web applications and mobile apps."
In this article, we will explore how AI advanced the e-commerce industry with some practical examples of how industry leaders are using artificial intelligence to streamline operations, improve customer experience and ultimately drive sales.
There are some fascinating ways AI has emerged and revolutionized the e-commerce industry and how businesses evolved in the digital marketplace. It has significantly impacted customer experience through:
All of these strategies are a game changer for companies in making data-driven decisions, reducing operating costs, improving efficiency, and, as a result, staying competitive in a rapidly evolving industry.
Product recommendations based solely on the customer segment or other generic assumption is a sure way to lose a sale! With all the data available to marketers these days, personalized product recommendations are here to stay. AI changed the way products are being promoted to customers, and to my delight — dynamic, real-time suggestions based on customer behavior and personal preferences is what drives sales and customer satisfaction (my unique fashion style is finally getting noticed by fashion companies!). For instance, Amazon’s recommendation uses AI to analyze browsing and purchasing history before making any product suggestions tailored to the buyer’s interest and intent.
AI-powered voice recognition has redefined the shopping experience in e-commerce, making it even more intuitive and convenient for customers. Shopping while driving? It’s possible now with voice assistants such as Amazon’s Alexa or Google Assistant that offer consumers a hands-free and user-friendly interaction with their favorite brands. This might be an extreme example, but on a serious note, these technologies have helped immensely people who have certain disabilities and might struggle or find it impossible to work with a mouse or keyboard enabling a whole new world of possibilities.
On the other hand, image recognition empowered shoppers with another way of product recommendation by uploading a photo of items they want to purchase. So far, the best application of this feature was adopted by Pinterest’s “Shop the Look” which enables users to click on the “pinned” image to find similar ones available in stores. In addition, ASOS, the UK’s biggest online fashion retailer, launched “Style Match,” which allows users to snap a photo of an outfit and explore similar outfits from their inventory.
Optimizing supply chains while reducing waste and boosting efficiency — here are only a few ways AI technologies improve inventory management. No one likes shopping in a store only to find out that your size is no longer available. Well, with AI this should never happen as the algorithm can predict demand for various products (successfully launched by Amazon). But also, Walmart has taken this to the next level, while using AI for real-time inventory tracking, helping store managers to restock items before they run low.
Are these technologies only available to big players? Luckily, with Shopify's AI-driven inventory management tools, small businesses can follow this trend and ensure they meet customer expectations, reduce waste and optimize inventory.
Have you ever found yourself searching for affordable flights on desired dates to eventually book the exact same flight 20% more expensive a few days later? Or trying to book an Uber and getting it one minute later for a higher price? Well, that’s now possible for e-commerce businesses (let’s hope for a rather downward trend!). Online retailers can effectively adopt AI for real-time pricing strategies ensuring they remain competitive and maximize profitability. For example, Media Markt adopted dynamic pricing offering the same TV at different prices during different times a day, however decided to partially refund customers up to two weeks after the purchase if the price was lower than when they bought the product.
Another space within e-commerce, which has not been omitted by AI is product information management (PIM). PIM solutions are handling massive amounts of data, hence the adoption of AI has been long awaited to bring some significant optimization across all channels of data management. Through machine learning algorithms, AI improves data quality by identifying and correcting errors, inconsistencies, and duplicates in product information.
Additionally, AI-driven PIM solutions streamline data enrichment processes by automatically tagging and classifying products based on attributes. Intelligent automation reduces manual efforts in updating product details, ensuring real-time accuracy. Predictive analytics within AI-powered PIM systems help businesses anticipate market trends and customer preferences, facilitating data-driven decision-making.
AI can significantly benefit the MACH (Microservices, API-first, Cloud-native, and Headless) architecture by enhancing its key principles. In the context of microservices, AI can optimize and automate service orchestration, ensuring efficient communication and collaboration among microservices. API-first design can leverage AI to enhance API management, ensuring seamless integration and data exchange. Cloud-native deployments benefit from AI-driven auto-scaling, resource optimization, and predictive maintenance, improving overall performance and cost efficiency. Headless architecture, with its focus on decoupled front-end and back-end, can leverage AI for personalized content delivery and user experience optimization.
Moreover, AI can analyze vast datasets generated by MACH systems to derive valuable insights, enabling data-driven decision-making. Overall, AI complements and enhances each aspect of the MACH architecture, fostering agility, scalability, and intelligence in modern digital ecosystems.
Despite the benefits, the AI raises valid concerns. Privacy becomes a paramount issue as these technologies gather and analyze vast amounts of user data. The absence of human interaction in customer service may lead to a less personalized experience, impacting customer satisfaction. Automation, while efficient, poses a risk to employment, with certain tasks susceptible to job displacement. As we navigate this tech-driven era, addressing these drawbacks becomes imperative to foster a harmonious coexistence between innovation and societal well-being.
In the dynamic landscape of e-commerce, AI emerges as a double-edged sword, offering unprecedented advantages while wielding potential pitfalls. On the bright side, it catapults efficiency, personalization, and user experience to new heights. However, shadowing this brilliance are concerns like privacy issues, the risk of job displacement, and the subtle erosion of the human touch in customer interactions.
Striking a balance between innovation and ethical considerations is the key to navigating this digital frontier. As we ride the e-commerce wave, let's ensure that AI's role is one of an invaluable assistant, not an accidental antagonist.
Author: Borgar Hestad, EVP Sales & Marketing, Bluestone PIM