Who gets recommended by AI? What every online retailer should know about the AI-driven shift in shopping
When consumers can express their needs to AI in thousands of ways, traditional product search and interfaces evolve into a multichannel model with countless parameters. What does this mean for online retailers, and how can they prepare?
Changing consumer needs are nothing new, but the technologies responding to those needs are: Gartner predicts that within five years, up to half of online purchases will be made by machines.
In the near future, product searches will increasingly rely on free-form conversations with AI, helping consumers find the right products more easily.
“Free-form product searches can effortlessly incorporate a wide range of personal values, preferences, or even medical needs. The search results include exactly the right products for the consumer – without needing custom manufacturing,” says Jonas Pomoell, Lead AI Consultant at HiQ.
The shift in buying behavior is also bringing machine customers – autonomous agents that can compare products and make purchases based on hyper-personalized criteria. For consumers, this means more flexible search options; for online retailers, an improved customer experience.
As a result, product comparison, discovery, and need assessment become significantly easier. At the same time, retailers must prepare for an explosion in categories, interfaces, and business opportunities.
When speech is free, search parameters multiply from two to two hundred
From the consumer’s perspective, hyper-personalization means being able to have natural conversations with AI. Instead of listing precise criteria like age, height, or price, consumers can describe their needs or usage scenarios in their own words.
For retailers, the change is just as disruptive. Traditional product searches rely on specific keywords, but now the number of predefined parameters and categories can surge from a handful to hundreds.
“In children’s clothing, for example, age is typically a key purchase criterion. But with free-form searches, one customer might mention a disliked color, another describes a muddy playground, and a third might include a reference image of a desired design. Instead of uniform search terms, retailers must handle vast amounts of diverse text,” explains Samu Tapanen, Head of Digital Commerce at HiQ.
While AI may not always reduce selling costs, it certainly increases impact, as better customer experience and discoverability ultimately drive sales.
Hyper-detailed searches demand richer product data
Improving product discoverability and search functions offers a great opportunity to stand out from competitors. Beyond enhancing customer experience, it’s critical in competitive sectors like consumer electronics, where visibility and searchability directly affect sales.
To enable AI to handle complex searches, it needs access to more comprehensive and precise product descriptions.
“The typically concise style of Finnish product descriptions no longer suffices. For example, a customer looking for a sofa might need to find models with at least 13.5 cm of clearance for a robot vacuum. AI can deliver, if the product data includes accurate leg height information,” says Jonas Pomoell.
Enriching product descriptions and attributes is not just an investment in future AI-assisted buying, but also enhances current multichannel commerce.
“We’re in a transition phase with one foot in the world of smart machine customers, the other still using traditional search methods. The more BIM attributes or detailed product data available, the easier products are to find via conventional search engines too,” says Samu Tapanen.
Valuable insights can already be gained by identifying how much traffic your store gets via ChatGPT, and responding accordingly.
Consumers craving multichannel experiences are increasing the number of interfaces
We constantly seek more interactive and personalized shopping experiences. Since AI isn’t tied to a single interface, it can flexibly adapt to various purposes.
“Voice interfaces allow purchases without a graphical interface. For example, Amazon’s popular Alexa can order pizza with a simple voice command. Similarly, AI can make phone services more cost-effective by replacing human agents,” says Tapanen.
While AI may not always reduce selling costs, it certainly increases impact. The better the customer experience and discoverability, the more product views, longer time-on-site, and larger cart sizes – ultimately driving higher sales.
Gartner also notes that, in addition to multichannel experiences, consumers increasingly value quality-driven and ethical buying. This trend is reflected in a growing hunger for information before making purchase decisions.
“The current live shopping phenomenon is trying to meet this need. In the future, we might see fully AI-generated live shopping events, where an AI presenter provides real-time, detailed product information to consumers.”
Retailer, you have decisions to make! New buying behaviors create new business models
Multichannel experiences, hyper-personalization, and free-form need assessment are creating entirely new business models and opportunities. Instead of isolated online visits, purchasing decisions now span multiple touchpoints: a consumer may browse a website, visit a store, consult a salesperson, and ask for recommendations from their network before buying.
“Digital commerce can no longer be viewed through traditional interfaces alone. In the future, shopping might happen directly through AI platforms like Perplexity. Valuable insights can already be gained by identifying how much traffic your store gets via ChatGPT and responding accordingly.”
Choosing a digital commerce strategy thoughtfully is crucial and depends on whether your online store is a strategic sales platform or if it can offer experiences and added value. The choice is no longer just about the tech – it’s a business decision that defines where and how customers discover and purchase products.
How to prepare for the AI-driven transformation of buying
1. Experiment boldly with AI – search is key.
AI can assist with product data generation, support product managers, analytics, and content creation, but its biggest impact is in search. Optimizing search for machine customers lays the foundation for future AI adoption. It’s also where HiQ excels.
2. Rethink how you’d build your business today – without legacy constraints.
Questioning established models of operation is tough, for we’re used to adhering to traditions and human limitations. AI isn’t encumbered by either ones, therefore enabling entirely new approaches. If you were founding your company today, what would you do differently?
3. Stick your foot through the AI door – enrich product data and descriptions.
Single-word product descriptions won’t satisfy consumers’ hunger for information or free-form searches. High-quality, comprehensive product data and attributes not only support AI-readiness but also improve discoverability via traditional search engines.
You’ve just read part two of our series on the machine customer phenomenon.
Check out part one as well: “AI knows what you need and orders it for you – buying is changing, here’s how.”
