Today, several businesses, not just the first movers and tech giants, are adopting powerful technologies like AI, ML and automation. We live in the era of Digital Darwinism where businesses that hold onto traditional business models, legacy technology, rudimentary methods or simply wait around are well on the path to extinction. And the past couple of pandemic years have amply underscored the fact that if you don’t evolve, you perish.
Artificial Intelligence (AI) is truly revolutionizing the world around us and the e-commerce industry is no exception. In this article, we delve into some of the key ways in which businesses are leveraging AI to thrive in e-commerce in the era of relentless transformation.
Current Trends in The E-Commerce Industry
The e-commerce industry was growing at a steady pace even before the pandemic. Post-pandemic, however, the industry has seen a boom in terms of size and sales volumes. Reasons – the countrywide lockdowns and Covid restrictions meant brands needed to provide the digital and direct channels to customers in addition to their brick-and-mortar stores. Even when the restrictions were lifted, owing to the changing perception of people towards e-commerce made a lot more people stick to online channels to shop. So, despite the physical shutdowns, new digital-native businesses have sprouted all across the globe.
But challenges were and are aplenty in the e-commerce space. Firstly, businesses need to provide intuitive and seamless online shopping experiences, regardless of the level of tech-savviness of the customer. Secondly, establishing trust among customers is challenging as data breaches and cyberattacks grow rapidly. Thirdly, e-commerce businesses need to keep optimizing their operations to remain competitive in the day and age of relentless transformation. And AI holds the key to these challenges and more.
Accordingly, there is a steady flow of investments into creating more hassle-free, secure and unobtrusive customer experiences for all. Powerful and innovative AI use cases are boosting up sales and revenues for all businesses in the competitive marketplace.
In What Ways Can You Leverage AI to Thrive in E-Commerce?
Personalized and Contextual Recommendations
Recommendation engines were one of the earliest and primary use cases of AI in e-commerce nearly till 2019. Brands and e-commerce platforms have been leveraging AI-powered recommendation engines to offer highly personalized and contextual product recommendations. When used correctly, this has helped e-commerce companies to cross sell, upsell and explore new opportunities, thus accelerating their sales and revenues.
The recommendation engines take a data-centric approach and use AI and Machine Learning (ML) to offer relevant product suggestions to them. They analyze customer data, predict behavior and make the right recommendations from among hundreds of thousands of products in the catalog, thus, improving conversions.
Brands can go beyond generic categories to choosing attributes that matter most to customers. For instance, a fashion e-retailer can use granular categories such as hemline, neckline, silhouette, etc. in making finetuning recommendations, rather than relying on typical categories like patterns, colors, past purchases, page views, etc.
Personalized Experiences at Scale
Despite the advantages such as efficiency, ease of access and comfort, one of the major drawbacks in the early years of e-commerce was the generic, impersonal and broken experiences. The use of AI in e-commerce provided the much-needed breakthrough.
Through the use of AI, brands can customize offers, recommendations, discounts, ads, campaigns, etc. to match up with the needs, context and journey of every customer. Through AI capabilities such as making smart predictions, the algorithm predicts customer behavior and alters the experience for every customer. For instance, the AI model can be trained to provide different offers to different customers based on their preferences and journey to boost conversions.
This kind of customization makes the customer feel like the experience has been tailored just for them. With AI, brands can craft such integrated, authentic and personalized experiences at scale, even when they are having thunderous traffic surges on their platform.
Few brands did have AI-powered tools and apps for customers to try products virtually. But the Covid-19 pandemic led more brands to deploy offline customer activation strategies such as virtual trial, fitting, etc. in their online channels. This has enhanced customer engagement and experiences.
Simplifying Search and Making It More Effective
One of the critical pain points for customers while using e-commerce platforms is the arduous search process. They end up spending several hours searching for the right product and sometimes unsuccessfully. The process is time-consuming and ineffective. The application of AI is enabling e-commerce platforms and brands to make search – both image and semantic search – intuitive, hassle-free and seamless for customers.
With AI-powered search, customers can locate what they are looking for in seconds and minutes, beyond generic and mechanical parameters. Search tools that are equipped with Natural Language Processing (NLP) can convert search queries in natural language and return sharp and relevant product results with a good understanding of the intent and context. Further, AI search products are also equipped with computer vision to enable easy and quick image search.
AI-powered engines can return both exact matches from the product catalog and similar products, improving product discoverability. Essentially, this AI-based functionality enables customers to widen or narrow down their search based on their need.
Revolutionizing Service and Support Functions
AI has the most significant impact in the area of customer service and support. Through the use of AI-powered, self-learning chatbots and smart digital assistants equipped with NLP, computer vision and analytics capabilities, e-commerce platforms and brands have been able to solve the customer service conundrum.
Conversational AI is being leveraged in several customer touchpoints and customer engagement scenarios such as technical support, voice chats, website chat, shopping assistants, messaging platforms, social media platforms, etc. They can simplify the shopping experiences of customers by helping them find what they are looking for in the platform/ app/ site. Chatbots can also cross-sell and upsell relevant products.
These chatbots and digital assistants are equipped to build meaningful, personalized conversations with customers in natural language, provide contextual replies and resolve queries. They can handle large volumes of queries and service tickets on a 24x7 basis within a fraction of the time and effort that would otherwise be required. This also reduces the error rates in the service and support functions. They only hand off complex queries and service requests to human agents along with the conversation history.
The use of AI-powered dynamic pricing engines has enabled brands to dynamically adjust and match up the pricing with the customer’s willingness to pay. This psychological pricing strategy enables businesses to optimize sales and customer engagement.
Further, intelligent AI-powered pricing algorithms are being leveraged to dynamically decide prices to optimize sales and revenues. So, when the demand is high and inventory is limited, the engine automatically reflects a price surge. It can reduce prices automatically to bring in more sales and revenue, whenever necessary.
Brands can take a cross-channel approach for channel optimization and elevating customer experiences across all channels. Several fashion brands get customers to sign up for the app to gain additional benefits in their physical stores. By utilizing the data from the digital channels, brands restock, optimize inventory and forecast demand in their offline channels. They are also feeding the data to make manufacturing decisions based on trends, preferences and quantities.
Cataloging and tagging of items are processes that take any brand/eCommerce company weeks to complete, especially when they have large numbers of products with several tags to be uploaded. With AI-powered tools, cataloging can be intelligently automated, reducing time required for uploads and tagging to a few hours and days.
AI also helps achieve highest possible levels of accuracy and consistency in product data than manual cataloging and tagging. AI cataloging tools are scalable and minimize the need for manual cataloging efforts. They help generate product descriptions, alt tags, SEO tags, style notes and so with ease.
AI tools also enable businesses to improve the SEO relevance of products on the website/ platform by bolstering the deep tagging capabilities. Deep tagging strengthens the in-site discoverability of products by enriching the set of identifiable attributes.
Value Maximization in The Supply Chain
The supply chain is the backbone of the e-commerce industry, starting with suppliers and ending with the end-customers. While the past few years have seen rapid digitization of the e-commerce supply chain, it is AI that has ushered value maximization from the planning stages through sourcing to last mile delivery and handling returns. AI tools infuse transparency and visibility into eCommerce supply chain management and enables smarter decision making. They enable businesses to improve the efficiency and cost effectiveness while keeping errors and leakages to a minimum. Here are few ways in which AI is applied in the supply chain value maximization:
Insights That Matter
AI-led analytics enables brands and e-commerce platforms to unearth insights that matter by sifting through the voluminous data at the disposal of brands. From strategic planning to sales and marketing to customer experiences and support, AI-enabled analytics has powerful applications in the e-commerce industry. It enables businesses to gain a competitive and strategic edge.
Brands can forecast customer expectations, preferences and behaviors in real-time based on data such as past purchases, online viewing history, seasonal patterns, social media trends, search history and so on. Based on the real-time insights, brands can be better prepared for the future and pivot seamlessly if required in the fast-evolving market. Brands can also understand future inhibitors and drivers of customer experiences and accordingly, engage in course correction.
The eCommerce industry is frequently targeted by cybercriminals in a bid to gain access to the large volumes of sensitive customer data and financial information. And data breaches have devastating impacts on the business – financially, legally and reputationally. Financially speaking, data breaches cost USD 4.24 million on average that includes customer attrition, brand image erosion and reputational damage. Legally, data breaches lead to heavy fines and penalties. Reputationally, businesses are seen as being untrustworthy and careless and often causes irreparable damage to brand image and reputation.
AI-based security solutions enable eCommerce platforms and brands to ensure that their apps/ sites/ platforms are available round-the-clock to legitimate customers and that customer and business data are fully secure. These solutions can identify vulnerabilities proactively and protect them, provide effective defense against known and emerging security threats and keep the security risks in check.
AI holds the key to unlocking a sea of new opportunities in e-commerce, when applied properly. With partners like Streamoid, fashion brands can leverage AI to thrive amid the aggressive competition and increasing dynamism in the e-commerce space. Streamoid enables fashion retailers, brands and other business users to transform their value chain through the power of fashion intelligence and creative AI-led solutions.