It’s often said that AI is ushering in the fourth industrial revolution, and the technology’s impact on digital commerce has been immense. Personalized shopping experiences are no longer an aberration, but something customers expect. Digital optimization and automation tools have made it cheaper and easier for businesses to use customer data or third-party data, creating intelligent ecommerce sites. AI-enabled marketing and product discovery tools help facilitate customer engagement and retention, if deployed correctly.
Personalization
AI algorithms can analyze vast amounts of customer data, including browsing history, purchasing behavior, and demographic information to deliver personalized product recommendations and tailored shopping experiences. AI-based personalization surfaces goods a consumer is most likely to buy, reminds customers when it’s time to refill an order, and offers shopping experiences tailored to an individual’s preferences. These personalized shopping experiences can be deployed in several touchpoints including product pages, email campaigns, and during the checkout process.
Dynamic pricing
Dynamic pricing, most famously deployed by ride-share companies but increasingly used in other markets, allows retailers to adjust prices in real-time based on factors like demand, inventory levels, and competitor pricing. For some ecommerce businesses, dynamic pricing can help maximize revenue while remaining competitive in the market, though it’s crucial to carefully select the AI’s parameters to avoid unrealistic pricing structures that might deter new customers.
Chatbots and virtual assistants
According to Gartner, by 2027 chatbots will become, for as many as a quarter of organizations, the technology providing personalized customer support in natural language, answering questions, and addressing consumer concerns in real-time. As some researchers have cautioned (link resides outside of ibm.com), it’s imperative to find synergy between conversational AI-assisted customer service and the humans that manage it, to ensure customers have a productive online shopping experience from end-to-end.
Search and discovery
AI-powered search and recommendation engines use machine learning algorithms to better capture user intent, improve search relevance, and enhance product discovery. For example: Large retailers are engaging third-party AI (link resides outside of ibm.com) to make searching for products in natural language simpler, so shoppers can search by pattern or style and find the exact item they’re looking to buy.
The AI revolution has also facilitated the creation of new kinds of ecommerce brands that are built on the technology. In recent years, for instance, ecommerce companies based on a subscription model—like Blue Apron and BarkBox—have grown over 1,000% (link resides outside of ibm.com). Direct-to-consumer subscription brands like these often harness AI and advanced analytics to provide their customers with personalized product selections.
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